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Bl(r),t=r.memoizedState,t!==null&&(t=t.dehydrated,t!==null)?((r.mode&1)===0?r.lanes=1:t.data==="$!"?r.lanes=8:r.lanes=1073741824,null):(x=l.children,t=l.fallback,m?(l=r.mode,m=r.child,x={mode:"hidden",children:x},(l&1)===0&&m!==null?(m.childLanes=0,m.pendingProps=x):m=Hs(x,l,0,null),t=gr(t,l,s,null),m.return=r,t.return=r,m.sibling=t,r.child=m,r.child.memoizedState=hc(s),r.memoizedState=uc,t):dc(r,x));if(d=t.memoizedState,d!==null&&(E=d.dehydrated,E!==null))return ox(t,r,x,l,E,d,s);if(m){m=l.fallback,x=r.mode,d=t.child,E=d.sibling;var P={mode:"hidden",children:l.children};return(x&1)===0&&r.child!==d?(l=r.child,l.childLanes=0,l.pendingProps=P,r.deletions=null):(l=Nn(d,P),l.subtreeFlags=d.subtreeFlags&14680064),E!==null?m=Nn(E,m):(m=gr(m,x,s,null),m.flags|=2),m.return=r,l.return=r,l.sibling=m,r.child=l,l=m,m=r.child,x=t.child.memoizedState,x=x===null?hc(s):{baseLanes:x.baseLanes|s,cachePool:null,transitions:x.transitions},m.memoizedState=x,m.childLanes=t.childLanes&~s,r.memoizedState=uc,l}return m=t.child,t=m.sibling,l=Nn(m,{mode:"visible",children:l.children}),(r.mode&1)===0&&(l.lanes=s),l.return=r,l.sibling=null,t!==null&&(s=r.deletions,s===null?(r.deletions=[t],r.flags|=16):s.push(t)),r.child=l,r.memoizedState=null,l}function dc(t,r){return r=Hs({mode:"visible",children:r},t.mode,0,null),r.return=t,t.child=r}function Rs(t,r,s,l){return l!==null&&Vl(l),qr(r,t.child,null,s),t=dc(r,r.pendingProps.children),t.flags|=2,r.memoizedState=null,t}function ox(t,r,s,l,d,m,x){if(s)return r.flags&256?(r.flags&=-257,l=sc(Error(i(422))),Rs(t,r,x,l)):r.memoizedState!==null?(r.child=t.child,r.flags|=128,null):(m=l.fallback,d=r.mode,l=Hs({mode:"visible",children:l.children},d,0,null),m=gr(m,d,x,null),m.flags|=2,l.return=r,m.return=r,l.sibling=m,r.child=l,(r.mode&1)!==0&&qr(r,t.child,null,x),r.child.memoizedState=hc(x),r.memoizedState=uc,m);if((r.mode&1)===0)return Rs(t,r,x,null);if(d.data==="$!"){if(l=d.nextSibling&&d.nextSibling.dataset,l)var E=l.dgst;return l=E,m=Error(i(419)),l=sc(m,l,void 0),Rs(t,r,x,l)}if(E=(x&t.childLanes)!==0,yt||E){if(l=Xe,l!==null){switch(x&-x){case 4:d=2;break;case 16:d=8;break;case 64:case 128:case 256:case 512:case 1024:case 2048:case 4096:case 8192:case 16384:case 32768:case 65536:case 131072:case 262144:case 524288:case 1048576:case 2097152:case 4194304:case 8388608:case 16777216:case 33554432:case 67108864:d=32;break;case 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l=r.pendingProps,d=l.revealOrder,m=l.tail;if(ct(t,r,l.children,s),l=Oe.current,(l&2)!==0)l=l&1|2,r.flags|=128;else{if(t!==null&&(t.flags&128)!==0)e:for(t=r.child;t!==null;){if(t.tag===13)t.memoizedState!==null&&Xf(t,s,r);else if(t.tag===19)Xf(t,s,r);else if(t.child!==null){t.child.return=t,t=t.child;continue}if(t===r)break e;for(;t.sibling===null;){if(t.return===null||t.return===r)break e;t=t.return}t.sibling.return=t.return,t=t.sibling}l&=1}if(Ie(Oe,l),(r.mode&1)===0)r.memoizedState=null;else switch(d){case"forwards":for(s=r.child,d=null;s!==null;)t=s.alternate,t!==null&&Ts(t)===null&&(d=s),s=s.sibling;s=d,s===null?(d=r.child,r.child=null):(d=s.sibling,s.sibling=null),fc(r,!1,d,s,m);break;case"backwards":for(s=null,d=r.child,r.child=null;d!==null;){if(t=d.alternate,t!==null&&Ts(t)===null){r.child=d;break}t=d.sibling,d.sibling=s,s=d,d=t}fc(r,!0,s,null,m);break;case"together":fc(r,!1,null,null,void 0);break;default:r.memoizedState=null}return r.child}function Ms(t,r){(r.mode&1)===0&&t!==null&&(t.alternate=null,r.alternate=null,r.flags|=2)}function xn(t,r,s){if(t!==null&&(r.dependencies=t.dependencies),dr|=r.lanes,(s&r.childLanes)===0)return null;if(t!==null&&r.child!==t.child)throw Error(i(153));if(r.child!==null){for(t=r.child,s=Nn(t,t.pendingProps),r.child=s,s.return=r;t.sibling!==null;)t=t.sibling,s=s.sibling=Nn(t,t.pendingProps),s.return=r;s.sibling=null}return r.child}function sx(t,r,s){switch(r.tag){case 3:Gf(r),$r();break;case 5:df(r);break;case 1:gt(r.type)&&ps(r);break;case 4:ql(r,r.stateNode.containerInfo);break;case 10:var l=r.type._context,d=r.memoizedProps.value;Ie(xs,l._currentValue),l._currentValue=d;break;case 13:if(l=r.memoizedState,l!==null)return l.dehydrated!==null?(Ie(Oe,Oe.current&1),r.flags|=128,null):(s&r.child.childLanes)!==0?Yf(t,r,s):(Ie(Oe,Oe.current&1),t=xn(t,r,s),t!==null?t.sibling:null);Ie(Oe,Oe.current&1);break;case 19:if(l=(s&r.childLanes)!==0,(t.flags&128)!==0){if(l)return Jf(t,r,s);r.flags|=128}if(d=r.memoizedState,d!==null&&(d.rendering=null,d.tail=null,d.lastEffect=null),Ie(Oe,Oe.current),l)break;return null;case 22:case 23:return r.lanes=0,$f(t,r,s)}return xn(t,r,s)}var Zf,pc,ep,tp;Zf=function(t,r){for(var s=r.child;s!==null;){if(s.tag===5||s.tag===6)t.appendChild(s.stateNode);else if(s.tag!==4&&s.child!==null){s.child.return=s,s=s.child;continue}if(s===r)break;for(;s.sibling===null;){if(s.return===null||s.return===r)return;s=s.return}s.sibling.return=s.return,s=s.sibling}},pc=function(){},ep=function(t,r,s,l){var d=t.memoizedProps;if(d!==l){t=r.stateNode,ur(en.current);var m=null;switch(s){case"input":d=vi(t,d),l=vi(t,l),m=[];break;case"select":d=Z({},d,{value:void 0}),l=Z({},l,{value:void 0}),m=[];break;case"textarea":d=bi(t,d),l=bi(t,l),m=[];break;default:typeof d.onClick!="function"&&typeof l.onClick=="function"&&(t.onclick=hs)}Ga(s,l);var x;s=null;for(B in d)if(!l.hasOwnProperty(B)&&d.hasOwnProperty(B)&&d[B]!=null)if(B==="style"){var E=d[B];for(x in E)E.hasOwnProperty(x)&&(s||(s={}),s[x]="")}else B!=="dangerouslySetInnerHTML"&&B!=="children"&&B!=="suppressContentEditableWarning"&&B!=="suppressHydrationWarning"&&B!=="autoFocus"&&(a.hasOwnProperty(B)?m||(m=[]):(m=m||[]).push(B,null));for(B in l){var P=l[B];if(E=d?.[B],l.hasOwnProperty(B)&&P!==E&&(P!=null||E!=null))if(B==="style")if(E){for(x in E)!E.hasOwnProperty(x)||P&&P.hasOwnProperty(x)||(s||(s={}),s[x]="");

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r.flags&65536?r:null}return(r.flags&128)!==0?(r.lanes=s,r):(l=l!==null,l!==(t!==null&&t.memoizedState!==null)&&l&&(r.child.flags|=8192,(r.mode&1)!==0&&(t===null||(Oe.current&1)!==0?qe===0&&(qe=3):Ic())),r.updateQueue!==null&&(r.flags|=4),at(r),null);case 4:return Qr(),pc(t,r),t===null&&Hi(r.stateNode.containerInfo),at(r),null;case 10:return Wl(r.type._context),at(r),null;case 17:return gt(r.type)&&fs(),at(r),null;case 19:if(Ae(Oe),m=r.memoizedState,m===null)return at(r),null;if(l=(r.flags&128)!==0,x=m.rendering,x===null)if(l)no(m,!1);else{if(qe!==0||t!==null&&(t.flags&128)!==0)for(t=r.child;t!==null;){if(x=Ts(t),x!==null){for(r.flags|=128,no(m,!1),l=x.updateQueue,l!==null&&(r.updateQueue=l,r.flags|=4),r.subtreeFlags=0,l=s,s=r.child;s!==null;)m=s,t=l,m.flags&=14680066,x=m.alternate,x===null?(m.childLanes=0,m.lanes=t,m.child=null,m.subtreeFlags=0,m.memoizedProps=null,m.memoizedState=null,m.updateQueue=null,m.dependencies=null,m.stateNode=null):(m.childLanes=x.childLanes,m.lanes=x.lanes,m.child=x.child,m.subtreeFlags=0,m.deletions=null,m.memoizedProps=x.memoizedProps,m.memoizedState=x.memoizedState,m.updateQueue=x.updateQueue,m.type=x.type,t=x.dependencies,m.dependencies=t===null?null:{lanes:t.lanes,firstContext:t.firstContext}),s=s.sibling;return 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B=lt;if(Ls=x,(lt=P)&&!B)for(ne=d;ne!==null;)x=ne,P=x.child,x.tag===22&&x.memoizedState!==null?dp(d):P!==null?(P.return=x,ne=P):dp(d);for(;m!==null;)ne=m,cp(m),m=m.sibling;ne=d,Ls=E,lt=B}up(t)}else(d.subtreeFlags&8772)!==0&&m!==null?(m.return=d,ne=m):up(t)}}function up(t){for(;ne!==null;){var r=ne;if((r.flags&8772)!==0){var s=r.alternate;try{if((r.flags&8772)!==0)switch(r.tag){case 0:case 11:case 15:lt||Ds(5,r);break;case 1:var l=r.stateNode;if(r.flags&4&&!lt)if(s===null)l.componentDidMount();else{var d=r.elementType===r.type?s.memoizedProps:Wt(r.type,s.memoizedProps);l.componentDidUpdate(d,s.memoizedState,l.__reactInternalSnapshotBeforeUpdate)}var m=r.updateQueue;m!==null&&hf(r,m,l);break;case 3:var x=r.updateQueue;if(x!==null){if(s=null,r.child!==null)switch(r.child.tag){case 5:s=r.child.stateNode;break;case 1:s=r.child.stateNode}hf(r,x,s)}break;case 5:var E=r.stateNode;if(s===null&&r.flags&4){s=E;var P=r.memoizedProps;switch(r.type){case"button":case"input":case"select":case"textarea":P.autoFocus&&s.focus();break;case"img":P.src&&(s.src=P.src)}}break;case 6:break;case 4:break;case 12:break;case 13:if(r.memoizedState===null){var B=r.alternate;if(B!==null){var G=B.memoizedState;if(G!==null){var Y=G.dehydrated;Y!==null&&Oi(Y)}}}break;case 19:case 17:case 21:case 22:case 23:case 25:break;default:throw Error(i(163))}lt||r.flags&512&&gc(r)}catch(q){je(r,r.return,q)}}if(r===t){ne=null;break}if(s=r.sibling,s!==null){s.return=r.return,ne=s;break}ne=r.return}}function hp(t){for(;ne!==null;){var r=ne;if(r===t){ne=null;break}var s=r.sibling;if(s!==null){s.return=r.return,ne=s;break}ne=r.return}}function dp(t){for(;ne!==null;){var r=ne;try{switch(r.tag){case 0:case 11:case 15:var s=r.return;try{Ds(4,r)}catch(P){je(r,s,P)}break;case 1:var l=r.stateNode;if(typeof l.componentDidMount=="function"){var d=r.return;try{l.componentDidMount()}catch(P){je(r,d,P)}}var m=r.return;try{gc(r)}catch(P){je(r,m,P)}break;case 5:var x=r.return;try{gc(r)}catch(P){je(r,x,P)}}}catch(P){je(r,r.return,P)}if(r===t){ne=null;break}var E=r.sibling;if(E!==null){E.return=r.return,ne=E;break}ne=r.return}}var dx=Math.ceil,Os=L.ReactCurrentDispatcher,wc=L.ReactCurrentOwner,Lt=L.ReactCurrentBatchConfig,xe=0,Xe=null,We=null,nt=0,Pt=0,Jr=An(0),qe=0,io=null,dr=0,Fs=0,xc=0,oo=null,vt=null,bc=0,Zr=1/0,bn=null,js=!1,Sc=null,Fn=null,Bs=!1,jn=null,Vs=0,so=0,kc=null,Ns=-1,zs=0;function ut(){return(xe&6)!==0?Ve():Ns!==-1?Ns:Ns=Ve()}function Bn(t){return(t.mode&1)===0?1:(xe&2)!==0&&nt!==0?nt&-nt:Q0.transition!==null?(zs===0&&(zs=id()),zs):(t=Te,t!==0||(t=window.event,t=t===void 0?16:fd(t.type)),t)}function $t(t,r,s,l){if(50<so)throw so=0,kc=null,Error(i(185));Ai(t,s,l),((xe&2)===0||t!==Xe)&&(t===Xe&&((xe&2)===0&&(Fs|=s),qe===4&&Vn(t,nt)),wt(t,l),s===1&&xe===0&&(r.mode&1)===0&&(Zr=Ve()+500,ms&&Mn()))}function wt(t,r){var s=t.callbackNode;Qw(t,r);var l=Yo(t,t===Xe?nt:0);if(l===0)s!==null&&td(s),t.callbackNode=null,t.callbackPriority=0;else if(r=l&-l,t.callbackPriority!==r){if(s!=null&&td(s),r===1)t.tag===0?G0(pp.bind(null,t)):Jd(pp.bind(null,t)),H0(function(){(xe&6)===0&&Mn()}),s=null;else{switch(od(l)){case 1:s=nl;break;case 4:s=nd;break;case 16:s=qo;break;case 536870912:s=rd;break;default:s=qo}s=Sp(s,fp.bind(null,t))}t.callbackPriority=r,t.callbackNode=s}}function fp(t,r){if(Ns=-1,zs=0,(xe&6)!==0)throw Error(i(327));var s=t.callbackNode;if(ei()&&t.callbackNode!==s)return null;var l=Yo(t,t===Xe?nt:0);if(l===0)return null;if((l&30)!==0||(l&t.expiredLanes)!==0||r)r=Ws(t,l);else{r=l;var d=xe;xe|=2;var m=gp();(Xe!==t||nt!==r)&&(bn=null,Zr=Ve()+500,pr(t,r));do try{mx();break}catch(E){mp(t,E)}while(!0);

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Error(i(329))}}}return wt(t,Ve()),t.callbackNode===s?fp.bind(null,t):null}function Tc(t,r){var s=oo;return t.current.memoizedState.isDehydrated&&(pr(t,r).flags|=256),t=Ws(t,r),t!==2&&(r=vt,vt=s,r!==null&&Ec(r)),t}function Ec(t){vt===null?vt=t:vt.push.apply(vt,t)}function fx(t){for(var r=t;;){if(r.flags&16384){var s=r.updateQueue;if(s!==null&&(s=s.stores,s!==null))for(var l=0;l<s.length;l++){var d=s[l],m=d.getSnapshot;d=d.value;try{if(!Nt(m(),d))return!1}catch{return!1}}}if(s=r.child,r.subtreeFlags&16384&&s!==null)s.return=r,r=s;else{if(r===t)break;for(;r.sibling===null;){if(r.return===null||r.return===t)return!0;r=r.return}r.sibling.return=r.return,r=r.sibling}}return!0}function Vn(t,r){for(r&=~xc,r&=~Fs,t.suspendedLanes|=r,t.pingedLanes&=~r,t=t.expirationTimes;0<r;){var s=31-Vt(r),l=1<<s;t[s]=-1,r&=~l}}function pp(t){if((xe&6)!==0)throw Error(i(327));ei();var r=Yo(t,0);if((r&1)===0)return wt(t,Ve()),null;var s=Ws(t,r);if(t.tag!==0&&s===2){var l=rl(t);l!==0&&(r=l,s=Tc(t,l))}if(s===1)throw s=io,pr(t,0),Vn(t,r),wt(t,Ve()),s;if(s===6)throw Error(i(345));return t.finishedWork=t.current.alternate,t.finishedLanes=r,mr(t,vt,bn),wt(t,Ve()),null}function Pc(t,r){var s=xe;xe|=1;try{return t(r)}finally{xe=s,xe===0&&(Zr=Ve()+500,ms&&Mn())}}function fr(t){jn!==null&&jn.tag===0&&(xe&6)===0&&ei();var r=xe;xe|=1;var s=Lt.transition,l=Te;try{if(Lt.transition=null,Te=1,t)return t()}finally{Te=l,Lt.transition=s,xe=r,(xe&6)===0&&Mn()}}function Cc(){Pt=Jr.current,Ae(Jr)}function pr(t,r){t.finishedWork=null,t.finishedLanes=0;var s=t.timeoutHandle;if(s!==-1&&(t.timeoutHandle=-1,U0(s)),We!==null)for(s=We.return;s!==null;){var l=s;switch(Fl(l),l.tag){case 1:l=l.type.childContextTypes,l!=null&&fs();break;case 3:Qr(),Ae(mt),Ae(ot),Ql();break;case 5:Kl(l);break;case 4:Qr();break;case 13:Ae(Oe);break;case 19:Ae(Oe);break;case 10:Wl(l.type._context);break;case 22:case 23:Cc()}s=s.return}if(Xe=t,We=t=Nn(t.current,null),nt=Pt=r,qe=0,io=null,xc=Fs=dr=0,vt=oo=null,cr!==null){for(r=0;r<cr.length;r++)if(s=cr[r],l=s.interleaved,l!==null){s.interleaved=null;var d=l.next,m=s.pending;if(m!==null){var x=m.next;m.next=d,l.next=x}s.pending=l}cr=null}return t}function mp(t,r){do{var s=We;try{if(zl(),Es.current=_s,Ps){for(var l=Fe.memoizedState;l!==null;){var d=l.queue;d!==null&&(d.pending=null),l=l.next}Ps=!1}if(hr=0,Ye=$e=Fe=null,Ji=!1,Zi=0,wc.current=null,s===null||s.return===null){qe=1,io=r,We=null;break}e:{var m=t,x=s.return,E=s,P=r;if(r=nt,E.flags|=32768,P!==null&&typeof P=="object"&&typeof P.then=="function"){var B=P,G=E,Y=G.tag;if((G.mode&1)===0&&(Y===0||Y===11||Y===15)){var q=G.alternate;q?(G.updateQueue=q.updateQueue,G.memoizedState=q.memoizedState,G.lanes=q.lanes):(G.updateQueue=null,G.memoizedState=null)}var te=Nf(x);if(te!==null){te.flags&=-257,zf(te,x,E,m,r),te.mode&1&&Vf(m,B,r),r=te,P=B;var re=r.updateQueue;if(re===null){var oe=new 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9{if(v){v=!1;return}const N=f(),j=N.state[Yn]-p.state[Yn],z=j===1,$=j===-1,U=!z&&!$||y;y=!1;const Q=U?"GO":$?"BACK":"FORWARD",ae=U?{type:"GO",index:j}:{type:$?"BACK":"FORWARD"};if(w)w=!1;else{const fe=c();if(typeof document<"u"&&fe.length){for(const pe of fe)if(await pe.blockerFn({currentLocation:p,nextLocation:N,action:Q})){v=!0,n.history.go(1),W.notify(ae);return}}}p=f(),W.notify(ae)},V=N=>{if(b){b=!1;return}let j=!1;const z=c();if(typeof document<"u"&&z.length)for(const $ of z){const U=$.enableBeforeUnload??!0;if(U===!0){j=!0;break}if(typeof U=="function"&&U()===!0){j=!0;break}}if(j)return N.preventDefault(),N.returnValue=""},W=Ib({getLocation:S,getLength:()=>n.history.length,pushState:(N,j)=>R("push",N,j),replaceState:(N,j)=>R("replace",N,j),back:N=>(N&&(w=!0),b=!0,n.history.back()),forward:N=>{N&&(w=!0),b=!0,n.history.forward()},go:N=>{y=!0,n.history.go(N)},createHref:N=>h(N),flush:A,destroy:()=>{n.history.pushState=i,n.history.replaceState=o,n.removeEventListener(Zp,V,{capture:!0}),n.removeEventListener(Jp,F)},onBlocked:()=>{g&&p!==g&&(p=g)},getBlockers:c,setBlockers:u,notifyOnIndexChange:!1});return n.addEventListener(Zp,V,{capture:!0}),n.addEventListener(Jp,F),n.history.pushState=function(...N){const j=i.apply(n.history,N);return W._ignoreSubscribers||L("PUSH"),j},n.history.replaceState=function(...N){const j=o.apply(n.history,N);return W._ignoreSubscribers||L("REPLACE"),j},W}function Ab(e){let n=e.replace(/[\x00-\x1f\x7f]/g,"");return n.startsWith("//")&&(n="/"+n.replace(/^\/+/,"")),n}function ka(e,n){const i=Ab(e),o=i.indexOf("#"),a=i.indexOf("?"),c=eh();return{href:i,pathname:i.substring(0,o>0?a>0?Math.min(o,a):o:a>0?a:i.length),hash:o>-1?i.substring(o):"",search:a>-1?i.slice(a,o===-1?void 0:o):"",state:n||{[Yn]:0,key:c,__TSR_key:c}}}function eh(){return(Math.random()+1).toString(36).substring(7)}function li(e,n){const i=n,o=e;return{fromLocation:i,toLocation:o,pathChanged:i?.pathname!==o.pathname,hrefChanged:i?.href!==o.href,hashChanged:i?.hash!==o.hash}}var Rb=class{constructor(e,n){this.tempLocationKey=`${Math.round(Math.random()*1e7)}`,this.resetNextScroll=!0,this.shouldViewTransition=void 0,this.isViewTransitionTypesSupported=void 0,this.subscribers=new Set,this.isScrollRestoring=!1,this.isScrollRestorationSetup=!1,this.startTransition=i=>i(),this.update=i=>{const o=this.options,a=this.basepath??o?.basepath??"/",c=this.basepath===void 0,u=o?.rewrite;if(this.options={...o,...i},this.isServer=this.options.isServer??typeof document>"u",this.protocolAllowlist=new Set(this.options.protocolAllowlist),this.options.pathParamsAllowedCharacters&&(this.pathParamsDecoder=sb(this.options.pathParamsAllowedCharacters)),(!this.history||this.options.history&&this.options.history!==this.history)&&(this.options.history?this.history=this.options.history:this.history=_b()),this.origin=this.options.origin,this.origin||(window?.origin&&window.origin!=="null"?this.origin=window.origin:this.origin="http://localhost"),this.history&&this.updateLatestLocation(),this.options.routeTree!==this.routeTree){this.routeTree=this.options.routeTree;let g;this.resolvePathCache=Po(1e3),g=this.buildRouteTree(),this.setRoutes(g)}if(!this.stores&&this.latestLocation){const g=this.getStoreConfig(this);this.batch=g.batch,this.stores=bb(Lb(this.latestLocation),g),db(this)}let h=!1;const f=this.options.basepath??"/",p=this.options.rewrite;if(c||a!==f||u!==p){this.basepath=f;const g=[],y=iy(f);y&&y!=="/"&&g.push(xb({basepath:f})),p&&g.push(p),this.rewrite=g.length===0?void 0:g.length===1?g[0]:wb(g),this.history&&this.updateLatestLocation(),h=!0}h&&this.stores&&this.stores.location.setState(()=>this.latestLocation),typeof window<"u"&&"CSS"in window&&typeof window.CSS?.supports=="function"&&(this.isViewTransitionTypesSupported=window.CSS.supports("selector(:active-view-transition-type(a)"))},this.updateLatestLocation=()=>{this.latestLocation=this.parseLocation(this.history.location,this.latestLocation)},this.buildRouteTree=()=>{const i=eb(this.routeTree,this.options.caseSensitive,(o,a)=>{o.init({originalIndex:a})});return this.options.routeMasks&&Qx(this.options.routeMasks,i.processedTree),i},this.subscribe=(i,o)=>{const a={eventType:i,fn:o};return this.subscribers.add(a),()=>{this.subscribers.delete(a)}},this.emit=i=>

9{this.subscribers.forEach(o=>{o.eventType===i.type&&o.fn(i)})},this.parseLocation=(i,o)=>{const a=({pathname:f,search:p,hash:g,href:y,state:v})=>{if(!this.rewrite&&!/[ \x00-\x1f\x7f\u0080-\uffff]/.test(f)){const T=this.options.parseSearch(p),A=this.options.stringifySearch(T);return{href:f+A+g,publicHref:y,pathname:co(f).path,external:!1,searchStr:A,search:yr(o?.search,T),hash:co(g.slice(1)).path,state:qn(o?.state,v)}}const w=new URL(y,this.origin),b=vu(this.rewrite,w),S=this.options.parseSearch(b.search),k=this.options.stringifySearch(S);return b.search=k,{href:b.href.replace(b.origin,""),publicHref:y,pathname:co(b.pathname).path,external:!!this.rewrite&&b.origin!==this.origin,searchStr:k,search:yr(o?.search,S),hash:co(b.hash.slice(1)).path,state:qn(o?.state,v)}},c=a(i),{__tempLocation:u,__tempKey:h}=c.state;if(u&&(!h||h===this.tempLocationKey)){const f=a(u);return f.state.key=c.state.key,f.state.__TSR_key=c.state.__TSR_key,delete f.state.__tempLocation,{...f,maskedLocation:c}}return c},this.resolvePathWithBase=(i,o)=>ob({base:i,to:Zu(o),trailingSlash:this.options.trailingSlash,cache:this.resolvePathCache}),this.matchRoutes=(i,o,a)=>typeof i=="string"?this.matchRoutesInternal({pathname:i,search:o},a):this.matchRoutesInternal(i,o),this.getMatchedRoutes=i=>Db({pathname:i,routesById:this.routesById,processedTree:this.processedTree}),this.cancelMatch=i=>{const o=this.getMatch(i);o&&(o.abortController.abort(),clearTimeout(o._nonReactive.pendingTimeout),o._nonReactive.pendingTimeout=void 0)},this.cancelMatches=()=>{this.stores.pendingMatchesId.state.forEach(i=>{this.cancelMatch(i)}),this.stores.matchesId.state.forEach(i=>{if(this.stores.pendingMatchStoresById.has(i))return;const o=this.stores.activeMatchStoresById.get(i)?.state;o&&(o.status==="pending"||o.isFetching==="loader")&&this.cancelMatch(i)})},this.buildLocation=i=>{const o=(c={})=>{const u=c._fromLocation||this.pendingBuiltLocation||this.latestLocation,h=this.matchRoutesLightweight(u);c.from;const f=c.unsafeRelative==="path"?u.pathname:c.from??h.fullPath,p=this.resolvePathWithBase(f,"."),g=h.search,y=Object.assign(Object.create(null),h.params),v=c.to?this.resolvePathWithBase(p,`${c.to}`):this.resolvePathWithBase(p,"."),w=c.params===!1||c.params===null?Object.create(null):(c.params??!0)===!0?y:Object.assign(y,$n(c.params,y)),b=this.getMatchedRoutes(v);let S=b.matchedRoutes;if((!b.foundRoute||b.foundRoute.path!=="/"&&b.routeParams["**"])&&this.options.notFoundRoute&&(S=[...S,this.options.notFoundRoute]),Object.keys(w).length>0)for(const z of S){const $=z.options.params?.stringify??z.options.stringifyParams;if($)try{Object.assign(w,$(w))}catch{}}const k=i.leaveParams?v:co(Up({path:v,params:w,decoder:this.pathParamsDecoder,server:this.isServer}).interpolatedPath).path;let T=g;if(i._includeValidateSearch&&this.options.search?.strict){const z={};S.forEach($=>{if($.options.validateSearch)try{Object.assign(z,ca($.options.validateSearch,{...z,...T}))}catch{}}),T=z}T=Ob({search:T,dest:c,destRoutes:S,_includeValidateSearch:i._includeValidateSearch}),T=yr(g,T);const A=this.options.stringifySearch(T),R=c.hash===!0?u.hash:c.hash?$n(c.hash,u.hash):void 0,L=R?`#${R}`:"";let F=c.state===!0?u.state:c.state?$n(c.state,u.state):{};F=qn(u.state,F);const V=`${k}${A}${L}`;let W,N,j=!1;if(this.rewrite){const z=new URL(V,this.origin),$=sy(this.rewrite,z);W=z.href.replace(z.origin,""),$.origin!==this.origin?(N=$.href,j=!0):N=$.pathname+$.search+$.hash}else W=qx(V),N=W;return{publicHref:N,href:W,pathname:k,search:T,searchStr:A,state:F,hash:R??"",external:j,unmaskOnReload:c.unmaskOnReload}},a=(c={},u)=>{const h=o(c);let f=u?o(u):void 0;if(!f){const p=Object.create(null);if(this.options.routeMasks){const g=Yx(h.pathname,this.processedTree);if(g){Object.assign(p,g.rawParams);const{from:y,params:v,...w}=g.route,b=v===!1||v===null?Object.create(null):(v??!0)===!0?p:Object.assign(p,$n(v,p));u={from:i.from,...w,params:b},f=o(u)}}}return f&&(h.maskedLocation=f),h};return i.mask?a(i,{from:i.from,...i.mask}):a(i)},this.commitLocation=async({viewTransition:i,ignoreBlocker:o,...a})=>{const c=()=>{const f=["key","__TSR_key","__TSR_index","__hashScrollIntoViewOptions"];f.forEach(g=>{a.state[g]=this.latestLocation.state[g]});const p=Tr(a.state,this.latestLocation.state);return f.forEach(g=>{delete a.state[g]}),p},u=Qn(this.latestLocation.href)===Qn(a.href);let h=this.commitLocationPromise;if(this.commitLocationPromise=ui(()=>{h?.resolve(),h=void 0}),u&&c())this.load();else{let{maskedLocation:f,hashScrollIntoView:p,...g}=a;f&&(g={...f,state:{...f.state,__tempKey:void 0,__tempLocation:{...g,search:g.searchStr,state:{...g.state,__tempKey:void 0,__tempLocation:void 0,__TSR_key:void 0,key:void 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9{if(h){const y=this.history.location.state.__TSR_index,v=ka(h,{__TSR_index:i?y:y+1}),w=new URL(v.pathname,this.origin);f.to=vu(this.rewrite,w).pathname,f.search=this.options.parseSearch(v.search),f.hash=v.hash.slice(1)}const p=this.buildLocation({...f,_includeValidateSearch:!0});this.pendingBuiltLocation=p;const g=this.commitLocation({...p,viewTransition:c,replace:i,resetScroll:o,hashScrollIntoView:a,ignoreBlocker:u});return Promise.resolve().then(()=>{this.pendingBuiltLocation===p&&(this.pendingBuiltLocation=void 0)}),g},this.navigate=async({to:i,reloadDocument:o,href:a,publicHref:c,...u})=>{let h=!1;if(a)try{new URL(`${a}`),h=!0}catch{}if(h&&!o&&(o=!0),o){if(i!==void 0||!a){const p=this.buildLocation({to:i,...u});a=a??p.publicHref,c=c??p.publicHref}const f=!h&&c?c:a;if(ba(f,this.protocolAllowlist))return Promise.resolve();if(!u.ignoreBlocker){const p=this.history.getBlockers?.()??[];for(const g of p)if(g?.blockerFn&&await g.blockerFn({currentLocation:this.latestLocation,nextLocation:this.latestLocation,action:"PUSH"}))return Promise.resolve()}return u.replace?window.location.replace(f):window.location.href=f,Promise.resolve()}return this.buildAndCommitLocation({...u,href:a,to:i,_isNavigate:!0})},this.beforeLoad=()=>{this.cancelMatches(),this.updateLatestLocation();const i=this.matchRoutes(this.latestLocation),o=this.stores.cachedMatchesSnapshot.state.filter(a=>!i.some(c=>c.id===a.id));this.batch(()=>{this.stores.status.setState(()=>"pending"),this.stores.statusCode.setState(()=>200),this.stores.isLoading.setState(()=>!0),this.stores.location.setState(()=>this.latestLocation),this.stores.setPendingMatches(i),this.stores.setCachedMatches(o)})},this.load=async i=>{let o,a,c;const u=this.stores.resolvedLocation.state??this.stores.location.state;for(c=new Promise(f=>{this.startTransition(async()=>{try{this.beforeLoad();const p=this.latestLocation,g=this.stores.resolvedLocation.state,y=li(p,g);this.stores.redirect.state||this.emit({type:"onBeforeNavigate",...y}),this.emit({type:"onBeforeLoad",...y}),await Yp({router:this,sync:i?.sync,forceStaleReload:u.href===p.href,matches:this.stores.pendingMatchesSnapshot.state,location:p,updateMatch:this.updateMatch,onReady:async()=>{this.startTransition(()=>{this.startViewTransition(async()=>{let v=null,w=null,b=null,S=null;this.batch(()=>{const k=this.stores.pendingMatchesSnapshot.state,T=k.length,A=this.stores.activeMatchesSnapshot.state;v=T?A.filter(F=>!this.stores.pendingMatchStoresById.has(F.id)):null;const R=new Set;for(const F of this.stores.pendingMatchStoresById.values())F.routeId&&R.add(F.routeId);const L=new Set;for(const F of this.stores.activeMatchStoresById.values())F.routeId&&L.add(F.routeId);w=T?A.filter(F=>!R.has(F.routeId)):null,b=T?k.filter(F=>!L.has(F.routeId)):null,S=T?k.filter(F=>L.has(F.routeId)):A,this.stores.isLoading.setState(()=>!1),this.stores.loadedAt.setState(()=>Date.now()),T&&(this.stores.setActiveMatches(k),this.stores.setPendingMatches([]),this.stores.setCachedMatches([...this.stores.cachedMatchesSnapshot.state,...v.filter(F=>F.status!=="error"&&F.status!=="notFound"&&F.status!=="redirected")]),this.clearExpiredCache())});for(const[k,T]of[[w,"onLeave"],[b,"onEnter"],[S,"onStay"]])if(k)for(const A of k)this.looseRoutesById[A.routeId].options[T]?.(A)})})}})}catch(p){bt(p)?(o=p,this.navigate({...o.options,replace:!0,ignoreBlocker:!0})):pt(p)&&(a=p);const g=o?o.status:a?404:this.stores.activeMatchesSnapshot.state.some(y=>y.status==="error")?500:200;this.batch(()=>{this.stores.statusCode.setState(()=>g),this.stores.redirect.setState(()=>o)})}this.latestLoadPromise===c&&(this.commitLocationPromise?.resolve(),this.latestLoadPromise=void 0,this.commitLocationPromise=void 0),f()})}),this.latestLoadPromise=c,await c;this.latestLoadPromise&&c!==this.latestLoadPromise;)await this.latestLoadPromise;let h;this.hasNotFoundMatch()?h=404:this.stores.activeMatchesSnapshot.state.some(f=>f.status==="error")&&(h=500),h!==void 0&&this.stores.statusCode.setState(()=>h)},this.startViewTransition=i=>{const o=this.shouldViewTransition??this.options.defaultViewTransition;if(this.shouldViewTransition=void 0,o&&typeof document<"u"&&"startViewTransition"in document&&typeof document.startViewTransition=="function"){let a;if(typeof o=="object"&&this.isViewTransitionTypesSupported){const c=this.latestLocation,u=this.stores.resolvedLocation.state,h=typeof o.types=="function"?o.types(li(c,u)):o.types;if(h===!1){i();return}a={update:i,types:h}}else a=i;document.startViewTransition(a)}else i()},this.updateMatch=(i,o)=>{this.startTransition(()=>

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9s:a,parsedParams:c}=i;let{matchedRoutes:u}=i,h=!1;(o?o.path!=="/"&&a["**"]:Qn(e.pathname))&&(this.options.notFoundRoute?u=[...u,this.options.notFoundRoute]:h=!0);const f=h?jb(this.options.notFoundMode,u):void 0,p=new Array(u.length),g=new Map;for(const y of this.stores.activeMatchStoresById.values())y.routeId&&g.set(y.routeId,y.state);for(let y=0;y<u.length;y++){const v=u[y],w=p[y-1];let b,S,k;{const Q=w?.search??e.search,ae=w?._strictSearch??void 0;try{const fe=ca(v.options.validateSearch,{...Q})??void 0;b={...Q,...fe},S={...ae,...fe},k=void 0}catch(fe){let pe=fe;if(fe instanceof Ta||(pe=new Ta(fe.message,{cause:fe})),n?.throwOnError)throw pe;b=Q,S={},k=pe}}const T=v.options.loaderDeps?.({search:b})??"",A=T?JSON.stringify(T):"",{interpolatedPath:R,usedParams:L}=Up({path:v.fullPath,params:a,decoder:this.pathParamsDecoder,server:this.isServer}),F=v.id+R+A,V=this.getMatch(F),W=g.get(v.id),N=V?._strictParams??L;let j;if(!V)try{tm(v,L,c,N)}catch(Q){if(pt(Q)||bt(Q)?j=Q:j=new Mb(Q.message,{cause:Q}),n?.throwOnError)throw j}Object.assign(a,N);const z=W?"stay":"enter";let $;if(V)$={...V,cause:z,params:W?.params??a,_strictParams:N,search:yr(W?W.search:V.search,b),_strictSearch:S};else{const Q=v.options.loader||v.options.beforeLoad||v.lazyFn||uy(v)?"pending":"success";$={id:F,ssr:v.options.ssr,index:y,routeId:v.id,params:W?.params??a,_strictParams:N,pathname:R,updatedAt:Date.now(),search:W?yr(W.search,b):b,_strictSearch:S,searchError:void 0,status:Q,isFetching:!1,error:void 0,paramsError:j,__routeContext:void 0,_nonReactive:{loadPromise:ui()},__beforeLoadContext:void 0,context:{},abortController:new AbortController,fetchCount:0,cause:z,loaderDeps:W?qn(W.loaderDeps,T):T,invalid:!1,preload:!1,links:void 0,scripts:void 0,headScripts:void 0,meta:void 0,staticData:v.options.staticData||{},fullPath:v.fullPath}}n?.preload||($.globalNotFound=f===v.id),$.searchError=k;const U=this.getParentContext(w);$.context={...U,...$.__routeContext,...$.__beforeLoadContext},p[y]=$}for(let y=0;y<p.length;y++){const v=p[y],w=this.looseRoutesById[v.routeId],b=this.getMatch(v.id),S=g.get(v.routeId);if(v.params=S?yr(S.params,a):a,!b){const k=p[y-1],T=this.getParentContext(k);if(w.options.context){const A={deps:v.loaderDeps,params:v.params,context:T??{},location:e,navigate:R=>this.navigate({...R,_fromLocation:e}),buildLocation:this.buildLocation,cause:v.cause,abortController:v.abortController,preload:!!v.preload,matches:p,routeId:w.id};v.__routeContext=w.options.context(A)??void 0}v.context={...T,...v.__routeContext,...v.__beforeLoadContext}}}return p}matchRoutesLightweight(e){const{matchedRoutes:n,routeParams:i,parsedParams:o}=this.getMatchedRoutes(e.pathname),a=To(n),c={...e.search};for(const g of n)try{Object.assign(c,ca(g.options.validateSearch,c))}catch{}const u=To(this.stores.matchesId.state),h=u&&this.stores.activeMatchStoresById.get(u)?.state,f=h&&h.routeId===a.id&&h.pathname===e.pathname;let p;if(f)p=h.params;else{const g=Object.assign(Object.create(null),i);for(const y of n)try{tm(y,i,o??{},g)}catch{}p=g}return{matchedRoutes:n,fullPath:a.fullPath,search:c,params:p}}},Ta=class extends Error{},Mb=class extends Error{};

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jb(e,n){if(e!=="root")for(let i=n.length-1;i>=0;i--){const o=n[i];if(o.children)return o.id}return Er}function tm(e,n,i,o){const a=e.options.params?.parse??e.options.parseParams;if(a)if(e.options.skipRouteOnParseError)for(const c in n)c in i&&(o[c]=i[c]);else{const c=a(o);Object.assign(o,c)}}var Bb="Error preloading route! ☝️",hy=class{get to(){return this._to}get id(){return this._id}get path(){return this._path}get fullPath(){return this._fullPath}constructor(e){if(this.init=n=>{this.originalIndex=n.originalIndex;const i=this.options,o=!i?.path&&!i?.id;this.parentRoute=this.options.getParentRoute?.(),o?this._path=Er:this.parentRoute||Sn();let a=o?Er:i?.path;a&&a!=="/"&&(a=ry(a));const c=i?.id||a;let u=o?Er:aa([this.parentRoute.id==="__root__"?"":this.parentRoute.id,c]);a==="__root__"&&(a="/"),u!=="__root__"&&(u=aa(["/",u]));const h=u==="__root__"?"/":aa([this.parentRoute.fullPath,a]);this._path=a,this._id=u,this._fullPath=h,this._to=Qn(h)},this.addChildren=n=>this._addFileChildren(n),this._addFileChildren=n=>(Array.isArray(n)&&(this.children=n),typeof n=="object"&&n!==null&&(this.children=Object.values(n)),this),this._addFileTypes=()=>this,this.updateLoader=n=>(Object.assign(this.options,n),this),this.update=n=>(Object.assign(this.options,n),this),this.lazy=n=>(this.lazyFn=n,this),this.redirect=n=>oy({from:this.fullPath,...n}),this.options=e||{},this.isRoot=!e?.getParentRoute,e?.id&&e?.path)throw new Error("Route cannot have both an 'id' and a 'path' option.")}},Vb=class extends hy{constructor(e){super(e)}};function Nb(e){if(typeof document<"u"&&document.querySelector){const n=e.stores.location.state,i=n.state.__hashScrollIntoViewOptions??!0;if(i&&n.hash!==""){const o=document.getElementById(n.hash);o&&o.scrollIntoView(i)}}}function th(e){const n=e.errorComponent??nh;return 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a=o.instance;(!a||a.isConnected===!1)&&!o.snapshot&&(Ca(this.members,o),o.unmount())}n.scheduleRender()}remove(n){if(Ca(this.members,n),n===this.prevLead&&(this.prevLead=void 0),n===this.lead){const i=this.members[this.members.length-1];i&&this.promote(i)}}relegate(n){for(let i=this.members.indexOf(n)-1;i>=0;i--){const o=this.members[i];if(o.isPresent!==!1&&o.instance?.isConnected!==!1)return this.promote(o),!0}return!1}promote(n,i){const o=this.lead;if(n!==o&&(this.prevLead=o,this.lead=n,n.show(),o)){o.updateSnapshot(),n.scheduleRender();const{layoutDependency:a}=o.options,{layoutDependency:c}=n.options;(a===void 0||a!==c)&&(n.resumeFrom=o,i&&(o.preserveOpacity=!0),o.snapshot&&(n.snapshot=o.snapshot,n.snapshot.latestValues=o.animationValues||o.latestValues),n.root?.isUpdating&&(n.isLayoutDirty=!0)),n.options.crossfade===!1&&o.hide()}}exitAnimationComplete(){this.members.forEach(n=>{n.options.onExitComplete?.(),n.resumingFrom?.options.onExitComplete?.()})}scheduleRender(){this.members.forEach(n=>n.instance&&n.scheduleRender(!1))}removeLeadSnapshot(){this.lead?.snapshot&&(this.lead.snapshot=void 0)}}const wa={hasAnimatedSinceResize:!0,hasEverUpdated:!1},cu=["","X","Y","Z"],rP=1e3;let iP=0;function uu(e,n,i,o){const{latestValues:a}=n;a[e]&&(i[e]=a[e],n.setStaticValue(e,0),o&&(o[e]=0))}function uw(e){if(e.hasCheckedOptimisedAppear=!0,e.root===e)return;const{visualElement:n}=e.options;if(!n)return;const i=Av(n);if(window.MotionHasOptimisedAnimation(i,"transform")){const{layout:a,layoutId:c}=e.options;window.MotionCancelOptimisedAnimation(i,"transform",Ce,!(a||c))}const{parent:o}=e;o&&!o.hasCheckedOptimisedAppear&&uw(o)}function hw({attachResizeListener:e,defaultParent:n,measureScroll:i,checkIsScrollRoot:o,resetTransform:a}){return class{constructor(u={},h=n?.()){this.id=iP++,this.animationId=0,this.animationCommitId=0,this.children=new Set,this.options={},this.isTreeAnimating=!1,this.isAnimationBlocked=!1,this.isLayoutDirty=!1,this.isProjectionDirty=!1,this.isSharedProjectionDirty=!1,this.isTransformDirty=!1,this.updateManuallyBlocked=!1,this.updateBlockedByResize=!1,this.isUpdating=!1,this.isSVG=!1,this.needsReset=!1,this.shouldResetTransform=!1,this.hasCheckedOptimisedAppear=!1,this.treeScale={x:1,y:1},this.eventHandlers=new Map,this.hasTreeAnimated=!1,this.layoutVersion=0,this.updateScheduled=!1,this.scheduleUpdate=()=>this.update(),this.projectionUpdateScheduled=!1,this.checkUpdateFailed=()=>{this.isUpdating&&(this.isUpdating=!1,this.clearAllSnapshots())},this.updateProjection=()=>{this.projectionUpdateScheduled=!1,this.nodes.forEach(aP),this.nodes.forEach(fP),this.nodes.forEach(pP),this.nodes.forEach(lP)},this.resolvedRelativeTargetAt=0,this.linkedParentVersion=0,this.hasProjected=!1,this.isVisible=!0,this.animationProgress=0,this.sharedNodes=new Map,this.latestValues=u,this.root=h?h.root||h:this,this.path=h?[...h.path,h]:[],this.parent=h,this.depth=h?h.depth+1:0;for(let f=0;f<this.path.length;f++)this.path[f].shouldResetTransform=!0;this.root===this&&(this.nodes=new eP)}addEventListener(u,h){return this.eventHandlers.has(u)||this.eventHandlers.set(u,new hh),this.eventHandlers.get(u).add(h)}notifyListeners(u,...h){const f=this.eventHandlers.get(u);f&&f.notify(...h)}hasListeners(u){return this.eventHandlers.has(u)}mount(u){if(this.instance)return;this.isSVG=_h(u)&&!aE(u),this.instance=u;const{layoutId:h,layout:f,visualElement:p}=this.options;if(p&&!p.current&&p.mount(u),this.root.nodes.add(this),this.parent&&this.parent.children.add(this),this.root.hasTreeAnimated&&(f||h)&&(this.isLayoutDirty=!0),e){let g,y=0;const v=()=>this.root.updateBlockedByResize=!1;Ce.read(()=>{y=window.innerWidth}),e(u,()=>{const w=window.innerWidth;w!==y&&(y=w,this.root.updateBlockedByResize=!0,g&&g(),g=tP(v,250),wa.hasAnimatedSinceResize&&(wa.hasAnimatedSinceResize=!1,this.nodes.forEach(xg)))})}h&&this.root.registerSharedNode(h,this),this.options.animate!==!1&&p&&(h||f)&&this.addEventListener("didUpdate",({delta:g,hasLayoutChanged:y,hasRelativeLayoutChanged:v,layout:w})=>{if(this.isTreeAnimationBlocked()){this.target=void 0,this.relativeTarget=void 0;return}const b=this.options.transition||p.getDefaultTransition()||wP,{onLayoutAnimationStart:S,onLayoutAnimationComplete:k}=p.getProps(),T=!this.targetLayout||!aw(this.targetLayout,w),A=!y&&v;if(this.options.layoutRoot||this.resumeFrom||A||y&&(T||!this.currentAnimation)){this.resumeFrom&&(this.resumingFrom=this.resumeFrom,this.resumingFrom.resumingFrom=void 0);const R={...Sh(b,"layout"),onPlay:S,onComplete:k};(p.shouldReduceMotion||this.options.layoutRoot)&&(R.delay=0,R.type=!1),this.startAnimation(R),this.setAnimationOrigin(g,A)}else y||xg(this),this.isLead()&&this.options.onExitComplete&&this.options.onExitComplete();this.targetLayout=w})}unmount(){this.options.layoutId&&this.willUpdate(),this.root.nodes.remove(this);const u=this.getStack();u&&u.remove(this),this.parent&&this.parent.children.delete(this),this.instance=void 0,this.eventHandlers.clear(),Jn(this.updateProjection)}blockUpdate(){this.updateManuallyBlocked=!0}unblockUpdate(){this.updateManuallyBlocked=!1}isUpdateBlocked(){return this.updateManuallyBlocked||this.updateBlockedByResize}isTreeAnimationBlocked(){return this.isAnimationBlocked||this.parent&&this.parent.isTreeAnimationBlocked()||!1}startUpdate(){this.isUpdateBlocked()||(this.isUpdating=!0,this.nodes&&this.nodes.forEach(mP),this.animationId++)}getTransformTemplate(){const{visualElement:u}=this.options;return u&&u.getProps().transformTemplate}willUpdate(u=!0){if(this.root.hasTreeAnimated=!0,this.root.isUpdateBlocked()){this.options.onExitComplete&&this.options.onExitComplete();return}if(window.MotionCancelOptimisedAnimation&&!this.hasCheckedOptimisedAppear&&uw(this),!this.root.isUpdating&&this.root.startUpdate(),this.isLayoutDirty)return;this.isLayoutDirty=!0;for(let g=0;g<this.path.length;g++){const y=this.path[g];y.shouldResetTransform=!0,(typeof y.latestValues.x=="string"||typeof y.latestValues.y=="string")&&(y.isLayoutDirty=!0),y.updateScroll("snapshot"),y.options.layoutRoot&&y.willUpdate(!1)}const{layoutId:h,layout:f}=this.options;if(h===void 0&&!f)return;const p=this.getTransformTemplate();this.prevTransformTemplateValue=p?p(this.latestValues,""):void 0,this.updateSnapshot(),u&&this.notifyListeners("willUpdate")}update(){if(this.updateScheduled=!1,this.isUpdateBlocked()){const f=this.updateBlockedByResize;this.unblockUpdate(),this.updateBlockedByResize=!1,this.clearAllSnapshots(),f&&this.nodes.forEach(uP),this.nodes.forEach(vg);return}if(this.animationId<=this.animationCommitId){this.nodes.forEach(wg);return}this.animationCommitId=this.animationId,this.isUpdating?(this.isUpdating=!1,this.nodes.forEach(hP),this.nodes.forEach(dP),this.nodes.forEach(oP),this.nodes.forEach(sP)):this.nodes.forEach(wg),this.clearAllSnapshots();const h=dt.now();rt.delta=un(0,1e3/60,h-rt.timestamp),rt.timestamp=h,rt.isProcessing=!0,tu.update.process(rt),tu.preRender.process(rt),tu.render.process(rt),rt.isProcessing=!1}didUpdate(){this.updateScheduled||(this.updateScheduled=!0,Ch.read(this.scheduleUpdate))}clearAllSnapshots(){this.nodes.forEach(cP),this.sharedNodes.forEach(gP)}scheduleUpdateProjection(){this.projectionUpdateScheduled||(this.projectionUpdateScheduled=!0,Ce.preRender(this.updateProjection,!1,!0))}scheduleCheckAfterUnmount(){Ce.postRender(()=>{this.isLayoutDirty?this.root.didUpdate():this.root.checkUpdateFailed()})}updateSnapshot(){this.snapshot||!this.instance||(this.snapshot=this.measure(),this.snapshot&&!ft(this.snapshot.measuredBox.x)&&!ft(this.snapshot.measuredBox.y)&&(this.snapshot=void 0))}updateLayout(){if(!this.instance||(this.updateScroll(),!(this.options.alwaysMeasureLayout&&this.isLead())&&!this.isLayoutDirty))return;if(this.resumeFrom&&!this.resumeFrom.instance)for(let f=0;f<this.path.length;f++)this.path[f].updateScroll();const u=this.layout;this.layout=this.measure(!1),this.layoutVersion++,this.layoutCorrected||(this.layoutCorrected=Ke()),this.isLayoutDirty=!1,this.projectionDelta=void 0,this.notifyListeners("measure",this.layout.layoutBox);const{visualElement:h}=this.options;h&&h.notify("LayoutMeasure",this.layout.layoutBox,u?u.layoutBox:void 0)}updateScroll(u="measure"){let h=!!(this.options.layoutScroll&&this.instance);if(this.scroll&&this.scroll.animationId===this.root.animationId&&this.scroll.phase===u&&(h=!1),h&&this.instance){const f=o(this.instance);this.scroll={animationId:this.root.animationId,phase:u,isRoot:f,offset:i(this.instance),wasRoot:this.scroll?this.scroll.isRoot:f}}}resetTransform(){if(!a)return;const u=this.isLayoutDirty||this.shouldResetTransform||this.options.alwaysMeasureLayout,h=this.projectionDelta&&!sw(this.projectionDelta),f=this.getTransformTemplate(),p=f?f(this.latestValues,""):void 0,g=p!==this.prevTransformTemplateValue;u&&this.instance&&(h||wr(this.latestValues)||g)&&(a(this.instance,p),this.shouldResetTransform=!1,this.scheduleRender())}measure(u=!0){const h=this.measurePageBox();let f=this.removeElementScroll(h);return u&&(f=this.removeTransform(f)),xP(f),{animationId:this.root.animationId,measuredBox:h,layoutBox:f,latestValues:{},source:this.id}}measurePageBox(){const{visualElement:u}=this.options;if(!u)return Ke();const h=u.measureViewportBox();if(!(this.scroll?.wasRoot||this.path.some(bP))){const{scroll:p}=this.root;p&&(sn(h.x,p.offset.x),sn(h.y,p.offset.y))}return h}removeElementScroll(u){const h=Ke();if(qt(h,u),this.scroll?.wasRoot)return h;for(let f=0;f<this.path.length;f++){const p=this.path[f],{scroll:g,options:y}=p;p!==this.root&&g&&y.layoutScroll&&(g.wasRoot&&qt(h,u),sn(h.x,g.offset.x),sn(h.y,g.offset.y))}return h}applyTransform(u,h=!1,f){const p=f||Ke();qt(p,u);for(let g=0;g<this.path.length;g++){const y=this.path[g];!h&&y.options.layoutScroll&&y.scroll&&y!==y.root&&(sn(p.x,-y.scroll.offset.x),sn(p.y,-y.scroll.offset.y)),wr(y.latestValues)&&ya(p,y.latestValues,y.layout?.layoutBox)}return wr(this.latestValues)&&ya(p,this.latestValues,this.layout?.layoutBox),p}removeTransform(u){const h=Ke();qt(h,u);for(let f=0;f<this.path.length;f++){const p=this.path[f];if(!wr(p.latestValues))continue;let g;p.instance&&(Hu(p.latestValues)&&p.updateSnapshot(),g=Ke(),qt(g,p.measurePageBox())),cg(h,p.latestValues,p.snapshot?.layoutBox,g)}return wr(this.latestValues)&&cg(h,this.latestValues),h}setTargetDelta(u){this.targetDelta=u,this.root.scheduleUpdateProjection(),this.isProjectionDirty=!0}setOptions(u){this.options={...this.options,...u,crossfade:u.crossfade!==void 0?u.crossfade:!0}}clearMeasurements(){this.scroll=void 0,this.layout=void 0,this.snapshot=void 0,this.prevTransformTemplateValue=void 0,this.targetDelta=void 0,this.target=void 0,this.isLayoutDirty=!1}forceRelativeParentToResolveTarget(){this.relativeParent&&this.relativeParent.resolvedRelativeTargetAt!==rt.timestamp&&this.relativeParent.resolveTargetDelta(!0)}resolveTargetDelta(u=!1){const h=this.getLead();this.isProjectionDirty||(this.isProjectionDirty=h.isProjectionDirty),this.isTransformDirty||(this.isTransformDirty=h.isTransformDirty),this.isSharedProjectionDirty||(this.isSharedProjectionDirty=h.isSharedProjectionDirty);const f=!!this.resumingFrom||this!==h;if(!(u||f&&this.isSharedProjectionDirty||this.isProjectionDirty||this.parent?.isProjectionDirty||this.attemptToResolveRelativeTarget||this.root.updateBlockedByResize))return;const{layout:g,layoutId:y}=this.options;if(!this.layout||!(g||y))return;this.resolvedRelativeTargetAt=rt.timestamp;const v=this.getClosestProjectingParent();v&&this.linkedParentVersion!==v.layoutVersion&&!v.options.layoutRoot&&this.removeRelativeTarget(),!this.targetDelta&&!this.relativeTarget&&(this.options.layoutAnchor!==!1&&v&&v.layout?this.createRelativeTarget(v,this.layout.layoutBox,v.layout.layoutBox):this.removeRelativeTarget()),!(!this.relativeTarget&&!this.targetDelta)&&(this.target||(this.target=Ke(),this.targetWithTransforms=Ke()),this.relativeTarget&&this.relativeTargetOrigin&&this.relativeParent&&this.relativeParent.target?(this.forceRelativeParentToResolveTarget(),WE(this.target,this.relativeTarget,this.relativeParent.target,this.options.layoutAnchor||void 0)):this.targetDelta?(this.resumingFrom?this.applyTransform(this.layout.layoutBox,!1,this.target):qt(this.target,this.layout.layoutBox),Gv(this.target,this.targetDelta)):qt(this.target,this.layout.layoutBox),this.attemptToResolveRelativeTarget&&(this.attemptToResolveRelativeTarget=!1,this.options.layoutAnchor!==!1&&v&&!!v.resumingFrom==!!this.resumingFrom&&!v.options.layoutScroll&&v.target&&this.animationProgress!==1?this.createRelativeTarget(v,this.target,v.target):this.relativeParent=this.relativeTarget=void 0))}getClosestProjectingParent(){if(!(!this.parent||Hu(this.parent.latestValues)||Kv(this.parent.latestValues)))return this.parent.isProjecting()?this.parent:this.parent.getClosestProjectingParent()}isProjecting(){return!!((this.relativeTarget||this.targetDelta||this.options.layoutRoot)&&this.layout)}createRelativeTarget(u,h,f){this.relativeParent=u,this.linkedParentVersion=u.layoutVersion,this.forceRelativeParentToResolveTarget(),this.relativeTarget=Ke(),this.relativeTargetOrigin=Ke(),Oa(this.relativeTargetOrigin,h,f,this.options.layoutAnchor||void 0),qt(this.relativeTarget,this.relativeTargetOrigin)}removeRelativeTarget(){this.relativeParent=this.relativeTarget=void 0}calcProjection(){const u=this.getLead(),h=!!this.resumingFrom||this!==u;let f=!0;if((this.isProjectionDirty||this.parent?.isProjectionDirty)&&(f=!1),h&&(this.isSharedProjectionDirty||this.isTransformDirty)&&(f=!1),this.resolvedRelativeTargetAt===rt.timestamp&&(f=!1),f)return;const{layout:p,layoutId:g}=this.options;if(this.isTreeAnimating=!!(this.parent&&this.parent.isTreeAnimating||this.currentAnimation||this.pendingAnimation),this.isTreeAnimating||(this.targetDelta=this.relativeTarget=void 0),!this.layout||!(p||g))return;qt(this.layoutCorrected,this.layout.layoutBox);const y=this.treeScale.x,v=this.treeScale.y;yE(this.layoutCorrected,this.treeScale,this.path,h),u.layout&&!u.target&&(this.treeScale.x!==1||this.treeScale.y!==1)&&(u.target=u.layout.layoutBox,u.targetWithTransforms=Ke());const{target:w}=u;if(!w){this.prevProjectionDelta&&(this.createProjectionDeltas(),this.scheduleRender());return}!this.projectionDelta||!this.prevProjectionDelta?this.createProjectionDeltas():(rg(this.prevProjectionDelta.x,this.projectionDelta.x),rg(this.prevProjectionDelta.y,this.projectionDelta.y)),bo(this.projectionDelta,this.layoutCorrected,w,this.latestValues),(this.treeScale.x!==y||this.treeScale.y!==v||!pg(this.projectionDelta.x,this.prevProjectionDelta.x)||!pg(this.projectionDelta.y,this.prevProjectionDelta.y))&&(this.hasProjected=!0,this.scheduleRender(),this.notifyListeners("projectionUpdate",w))}hide(){this.isVisible=!1}show(){this.isVisible=!0}scheduleRender(u=!0){if(this.options.visualElement?.scheduleRender(),u){const h=this.getStack();h&&h.scheduleRender()}this.resumingFrom&&!this.resumingFrom.instance&&(this.resumingFrom=void 0)}createProjectionDeltas(){this.prevProjectionDelta=si(),this.projectionDelta=si(),this.projectionDeltaWithTransform=si()}setAnimationOrigin(u,h=!1){const f=this.snapshot,p=f?f.latestValues:{},g={...this.latestValues},y=si();(!this.relativeParent||!this.relativeParent.options.layoutRoot)&&(this.relativeTarget=this.relativeTargetOrigin=void 0),this.attemptToResolveRelativeTarget=!h;const v=Ke(),w=f?f.source:void 0,b=this.layout?this.layout.source:void 0,S=w!==b,k=this.getStack(),T=!k||k.members.length<=1,A=!!(S&&!T&&this.options.crossfade===!0&&!this.path.some(vP));this.animationProgress=0;let R;this.mixTargetDelta=L=>{const F=L/1e3;bg(y.x,u.x,F),bg(y.y,u.y,F),this.setTargetDelta(y),this.relativeTarget&&this.relativeTargetOrigin&&this.layout&&this.relativeParent&&this.relativeParent.layout&&(Oa(v,this.layout.layoutBox,this.relativeParent.layout.layoutBox,this.options.layoutAnchor||void 0),yP(this.relativeTarget,this.relativeTargetOrigin,v,F),R&&qE(this.relativeTarget,R)&&(this.isProjectionDirty=!1),R||(R=Ke()),qt(R,this.relativeTarget)),S&&(this.animationValues=g,QE(g,p,this.latestValues,F,A,T)),this.root.scheduleUpdateProjection(),this.scheduleRender(),this.animationProgress=F},this.mixTargetDelta(this.options.layoutRoot?1e3:0)}startAnimation(u){this.notifyListeners("animationStart"),this.currentAnimation?.stop(),this.resumingFrom?.currentAnimation?.stop(),this.pendingAnimation&&(Jn(this.pendingAnimation),this.pendingAnimation=void 0),this.pendingAnimation=Ce.update(()=>{wa.hasAnimatedSinceResize=!0,this.motionValue||(this.motionValue=di(0)),this.motionValue.jump(0,!1),this.currentAnimation=JE(this.motionValue,[0,1e3],{...u,velocity:0,isSync:!0,onUpdate:h=>{this.mixTargetDelta(h),u.onUpdate&&u.onUpdate(h)},onStop:()=>{},onComplete:()=>{u.onComplete&&u.onComplete(),this.completeAnimation()}}),this.resumingFrom&&(this.resumingFrom.currentAnimation=this.currentAnimation),this.pendingAnimation=void 0})}completeAnimation(){this.resumingFrom&&(this.resumingFrom.currentAnimation=void 0,this.resumingFrom.preserveOpacity=void 0);const u=this.getStack();u&&u.exitAnimationComplete(),this.resumingFrom=this.currentAnimation=this.animationValues=void 0,this.notifyListeners("animationComplete")}finishAnimation(){this.currentAnimation&&(this.mixTargetDelta&&this.mixTargetDelta(rP),this.currentAnimation.stop()),this.completeAnimation()}applyTransformsToTarget(){const u=this.getLead();let{targetWithTransforms:h,target:f,layout:p,latestValues:g}=u;if(!(!h||!f||!p)){if(this!==u&&this.layout&&p&&dw(this.options.animationType,this.layout.layoutBox,p.layoutBox)){f=this.target||Ke();const y=ft(this.layout.layoutBox.x);f.x.min=u.target.x.min,f.x.max=f.x.min+y;const v=ft(this.layout.layoutBox.y);f.y.min=u.target.y.min,f.y.max=f.y.min+v}qt(h,f),ya(h,g),bo(this.projectionDeltaWithTransform,this.layoutCorrected,h,g)}}registerSharedNode(u,h){this.sharedNodes.has(u)||this.sharedNodes.set(u,new nP),this.sharedNodes.get(u).add(h);const p=h.options.initialPromotionConfig;h.promote({transition:p?p.transition:void 0,preserveFollowOpacity:p&&p.shouldPreserveFollowOpacity?p.shouldPreserveFollowOpacity(h):void 0})}isLead(){const u=this.getStack();return u?u.lead===this:!0}getLead(){const{layoutId:u}=this.options;return u?this.getStack()?.lead||this:this}getPrevLead(){const{layoutId:u}=this.options;return u?this.getStack()?.prevLead:void 0}getStack(){const{layoutId:u}=this.options;if(u)return this.root.sharedNodes.get(u)}promote({needsReset:u,transition:h,preserveFollowOpacity:f}={}){const p=this.getStack();p&&p.promote(this,f),u&&(this.projectionDelta=void 0,this.needsReset=!0),h&&this.setOptions({transition:h})}relegate(){const u=this.getStack();return u?u.relegate(this):!1}resetSkewAndRotation(){const{visualElement:u}=this.options;if(!u)return;let h=!1;const{latestValues:f}=u;if((f.z||f.rotate||f.rotateX||f.rotateY||f.rotateZ||f.skewX||f.skewY)&&(h=!0),!h)return;const p={};f.z&&uu("z",u,p,this.animationValues);for(let g=0;g<cu.length;g++)uu(`rotate${cu[g]}`,u,p,this.animationValues),uu(`skew${cu[g]}`,u,p,this.animationValues);u.render();for(const g in p)u.setStaticValue(g,p[g]),this.animationValues&&(this.animationValues[g]=p[g]);u.scheduleRender()}applyProjectionStyles(u,h){if(!this.instance||this.isSVG)return;if(!this.isVisible){u.visibility="hidden";return}const f=this.getTransformTemplate();if(this.needsReset){this.needsReset=!1,u.visibility="",u.opacity="",u.pointerEvents=va(h?.pointerEvents)||"",u.transform=f?f(this.latestValues,""):"none";return}const p=this.getLead();if(!this.projectionDelta||!this.layout||!p.target){this.options.layoutId&&(u.opacity=this.latestValues.opacity!==void 0?this.latestValues.opacity:1,u.pointerEvents=va(h?.pointerEvents)||""),this.hasProjected&&!wr(this.latestValues)&&(u.transform=f?f({},""):"none",this.hasProjected=!1);return}u.visibility="";const g=p.animationValues||p.latestValues;this.applyTransformsToTarget();let y=KE(this.projectionDeltaWithTransform,this.treeScale,g);f&&(y=f(g,y)),u.transform=y;const{x:v,y:w}=this.projectionDelta;u.transformOrigin=`${v.origin*100}% ${w.origin*100}% 0`,p.animationValues?u.opacity=p===this?g.opacity??this.latestValues.opacity??1:this.preserveOpacity?this.latestValues.opacity:g.opacityExit:u.opacity=p===this?g.opacity!==void 0?g.opacity:"":g.opacityExit!==void 0?g.opacityExit:0;for(const b in qu){if(g[b]===void 0)continue;const{correct:S,applyTo:k,isCSSVariable:T}=qu[b],A=y==="none"?g[b]:S(g[b],p);if(k){const R=k.length;for(let L=0;L<R;L++)u[k[L]]=A}else T?this.options.visualElement.renderState.vars[b]=A:u[b]=A}this.options.layoutId&&(u.pointerEvents=p===this?va(h?.pointerEvents)||"":"none")}clearSnapshot(){this.resumeFrom=this.snapshot=void 0}resetTree(){this.root.nodes.forEach(u=>u.currentAnimation?.stop()),this.root.nodes.forEach(vg),this.root.sharedNodes.clear()}}}function oP(e){e.updateLayout()}function sP(e){const n=e.resumeFrom?.snapshot||e.snapshot;if(e.isLead()&&e.layout&&n&&e.hasListeners("didUpdate")){const{layoutBox:i,measuredBox:o}=e.layout,{animationType:a}=e.options,c=n.source!==e.layout.source;if(a==="size")rn(g=>{const y=c?n.measuredBox[g]:n.layoutBox[g],v=ft(y);y.min=i[g].min,y.max=y.min+v});else if(a==="x"||a==="y"){const g=a==="x"?"y":"x";Ku(c?n.measuredBox[g]:n.layoutBox[g],i[g])}else dw(a,n.layoutBox,i)&&rn(g=>{const y=c?n.measuredBox[g]:n.layoutBox[g],v=ft(i[g]);y.max=y.min+v,e.relativeTarget&&!e.currentAnimation&&(e.isProjectionDirty=!0,e.relativeTarget[g].max=e.relativeTarget[g].min+v)});const u=si();bo(u,i,n.layoutBox);const h=si();c?bo(h,e.applyTransform(o,!0),n.measuredBox):bo(h,i,n.layoutBox);const f=!sw(u);let p=!1;if(!e.resumeFrom){const g=e.getClosestProjectingParent();if(g&&!g.resumeFrom){const{snapshot:y,layout:v}=g;if(y&&v){const w=e.options.layoutAnchor||void 0,b=Ke();Oa(b,n.layoutBox,y.layoutBox,w);const S=Ke();Oa(S,i,v.layoutBox,w),aw(b,S)||(p=!0),g.options.layoutRoot&&(e.relativeTarget=S,e.relativeTargetOrigin=b,e.relativeParent=g)}}}e.notifyListeners("didUpdate",{layout:i,snapshot:n,delta:h,layoutDelta:u,hasLayoutChanged:f,hasRelativeLayoutChanged:p})}else if(e.isLead()){const{onExitComplete:i}=e.options;i&&i()}e.options.transition=void 0}function 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f=zo(n),p=ia(f,this.transformPagePoint),{point:g}=p,{timestamp:y}=rt;this.history=[{...g,timestamp:y}];const{onSessionStart:v}=i;v&&v(n,fu(p,this.history)),this.removeListeners=Bo(So(this.contextWindow,"pointermove",this.handlePointerMove),So(this.contextWindow,"pointerup",this.handlePointerUp),So(this.contextWindow,"pointercancel",this.handlePointerUp)),h&&this.startScrollTracking(h)}startScrollTracking(n){let i=n.parentElement;for(;i;){const o=getComputedStyle(i);(Mg.has(o.overflowX)||Mg.has(o.overflowY))&&this.scrollPositions.set(i,{x:i.scrollLeft,y:i.scrollTop}),i=i.parentElement}this.scrollPositions.set(window,{x:window.scrollX,y:window.scrollY}),window.addEventListener("scroll",this.onElementScroll,{capture:!0}),window.addEventListener("scroll",this.onWindowScroll),this.removeScrollListeners=()=>{window.removeEventListener("scroll",this.onElementScroll,{capture:!0}),window.removeEventListener("scroll",this.onWindowScroll)}}handleScroll(n){const 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c=y=>{i&&this.snapToCursor(zo(y).point),this.stopAnimation()},u=(y,v)=>{const{drag:w,dragPropagation:b,onDragStart:S}=this.getProps();if(w&&!b&&(this.openDragLock&&this.openDragLock(),this.openDragLock=HT(w),!this.openDragLock))return;this.latestPointerEvent=y,this.latestPanInfo=v,this.isDragging=!0,this.currentDirection=null,this.resolveConstraints(),this.visualElement.projection&&(this.visualElement.projection.isAnimationBlocked=!0,this.visualElement.projection.target=void 0),rn(T=>{let A=this.getAxisMotionValue(T).get()||0;if(ln.test(A)){const{projection:R}=this.visualElement;if(R&&R.layout){const 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Tw(n,{onSessionStart:c,onStart:u,onMove:h,onSessionEnd:f,resumeAnimation:p},{transformPagePoint:this.visualElement.getTransformPagePoint(),dragSnapToOrigin:g,distanceThreshold:o,contextWindow:kw(this.visualElement),element:this.visualElement.current})}stop(n,i){const o=n||this.latestPointerEvent,a=i||this.latestPanInfo,c=this.isDragging;if(this.cancel(),!c||!a||!o)return;const{velocity:u}=a;this.startAnimation(u);const{onDragEnd:h}=this.getProps();h&&Ce.postRender(()=>h(o,a))}cancel(){this.isDragging=!1;const{projection:n,animationState:i}=this.visualElement;n&&(n.isAnimationBlocked=!1),this.endPanSession();const{dragPropagation:o}=this.getProps();!o&&this.openDragLock&&(this.openDragLock(),this.openDragLock=null),i&&i.setActive("whileDrag",!1)}endPanSession(){this.panSession&&this.panSession.end(),this.panSession=void 0}updateAxis(n,i,o){const{drag:a}=this.getProps();if(!o||!oa(n,a,this.currentDirection))return;const c=this.getAxisMotionValue(n);let u=this.originPoint[n]+o[n];this.constraints&&this.constraints[n]&&(u=cC(u,this.constraints[n],this.elastic[n])),c.set(u)}resolveConstraints(){const{dragConstraints:n,dragElastic:i}=this.getProps(),o=this.visualElement.projection&&!this.visualElement.projection.layout?this.visualElement.projection.measure(!1):this.visualElement.projection?.layout,a=this.constraints;n&&ri(n)?this.constraints||(this.constraints=this.resolveRefConstraints()):n&&o?this.constraints=uC(o.layoutBox,n):this.constraints=!1,this.elastic=pC(i),a!==this.constraints&&!ri(n)&&o&&this.constraints&&!this.hasMutatedConstraints&&rn(c=>{this.constraints!==!1&&this.getAxisMotionValue(c)&&(this.constraints[c]=fC(o.layoutBox[c],this.constraints[c]))})}resolveRefConstraints(){const{dragConstraints:n,onMeasureDragConstraints:i}=this.getProps();if(!n||!ri(n))return!1;const o=n.current,{projection:a}=this.visualElement;if(!a||!a.layout)return!1;const c=vE(o,a.root,this.visualElement.getTransformPagePoint());let u=hC(a.layout.layoutBox,c);if(i){const h=i(mE(u));this.hasMutatedConstraints=!!h,h&&(u=qv(h))}return u}startAnimation(n){const{drag:i,dragMomentum:o,dragElastic:a,dragTransition:c,dragSnapToOrigin:u,onDragTransitionEnd:h}=this.getProps(),f=this.constraints||{},p=rn(g=>{if(!oa(g,i,this.currentDirection))return;let y=f&&f[g]||{};(u===!0||u===g)&&(y={min:0,max:0});const v=a?200:1e6,w=a?40:1e7,b={type:"inertia",velocity:o?n[g]:0,bounceStiffness:v,bounceDamping:w,timeConstant:750,restDelta:1,restSpeed:10,...c,...y};return this.startAxisValueAnimation(g,b)});return Promise.all(p).then(h)}startAxisValueAnimation(n,i){const o=this.getAxisMotionValue(n);return Nu(this.visualElement,n),o.start(kh(n,o,0,i,this.visualElement,!1))}stopAnimation(){rn(n=>this.getAxisMotionValue(n).stop())}getAxisMotionValue(n){const i=`_drag${n.toUpperCase()}`,o=this.visualElement.getProps(),a=o[i];return a||this.visualElement.getValue(n,(o.initial?o.initial[n]:void 0)||0)}snapToCursor(n){rn(i=>{const{drag:o}=this.getProps();if(!oa(i,o,this.currentDirection))return;const{projection:a}=this.visualElement,c=this.getAxisMotionValue(i);if(a&&a.layout){const{min:u,max:h}=a.layout.layoutBox[i],f=c.get()||0;c.set(n[i]-Me(u,h,.5)+f)}})}scalePositionWithinConstraints(){if(!this.visualElement.current)return;const{drag:n,dragConstraints:i}=this.getProps(),{projection:o}=this.visualElement;if(!ri(i)||!o||!this.constraints)return;this.stopAnimation();const a={x:0,y:0};rn(u=>{const h=this.getAxisMotionValue(u);if(h&&this.constraints!==!1){const f=h.get();a[u]=dC({min:f,max:f},this.constraints[u])}});const{transformTemplate:c}=this.visualElement.getProps();this.visualElement.current.style.transform=c?c({},""):"none",o.root&&o.root.updateScroll(),o.updateLayout(),this.constraints=!1,this.resolveConstraints(),rn(u=>{if(!oa(u,n,null))return;const h=this.getAxisMotionValue(u),{min:f,max:p}=this.constraints[u];h.set(Me(f,p,a[u]))}),this.visualElement.render()}addListeners(){if(!this.visualElement.current)return;mC.set(this.visualElement,this);const n=this.visualElement.current,i=So(n,"pointerdown",p=>{const{drag:g,dragListener:y=!0}=this.getProps(),v=p.target,w=v!==n&&YT(v);g&&y&&!w&&this.start(p)});let o;const a=()=>{const{dragConstraints:p}=this.getProps();ri(p)&&p.current&&(this.constraints=this.resolveRefConstraints(),o||(o=yC(n,p.current,()=>this.scalePositionWithinConstraints())))},{projection:c}=this.visualElement,u=c.addEventListener("measure",a);c&&!c.layout&&(c.root&&c.root.updateScroll(),c.updateLayout()),Ce.read(a);const h=Lo(window,"resize",()=>this.scalePositionWithinConstraints()),f=c.addEventListener("didUpdate",(({delta:p,hasLayoutChanged:g})=>{this.isDragging&&g&&(rn(y=>{const v=this.getAxisMotionValue(y);v&&(this.originPoint[y]+=p[y].translate,v.set(v.get()+p[y].translate))}),this.visualElement.render())}));return()=>{h(),i(),u(),f&&f(),o&&o()}}getProps(){const n=this.visualElement.getProps(),{drag:i=!1,dragDirectionLock:o=!1,dragPropagation:a=!1,dragConstraints:c=!1,dragElastic:u=Gu,dragMomentum:h=!0}=n;return{...n,drag:i,dragDirectionLock:o,dragPropagation:a,dragConstraints:c,dragElastic:u,dragMomentum:h}}}function Bg(e){let n=!0;return()=>{if(n){n=!1;return}e()}}function yC(e,n,i){const o=$m(e,Bg(i)),a=$m(n,Bg(i));return()=>{o(),a()}}function oa(e,n,i){return(n===!0||n===e)&&(i===null||i===e)}function vC(e,n=10){let i=null;return Math.abs(e.y)>n?i="y":Math.abs(e.x)>n&&(i="x"),i}class wC extends tr{constructor(n){super(n),this.removeGroupControls=jt,this.removeListeners=jt,this.controls=new gC(n)}mount(){const{dragControls:n}=this.node.getProps();n&&(this.removeGroupControls=n.subscribe(this.controls)),this.removeListeners=this.controls.addListeners()||jt}update(){const{dragControls:n}=this.node.getProps(),{dragControls:i}=this.node.prevProps||{};n!==i&&(this.removeGroupControls(),n&&(this.removeGroupControls=n.subscribe(this.controls)))}unmount(){this.removeGroupControls(),this.removeListeners(),this.controls.isDragging||this.controls.endPanSession()}}const pu=e=>(n,i)=>{e&&Ce.update(()=>e(n,i),!1,!0)};class xC extends tr{constructor(){super(...arguments),this.removePointerDownListener=jt}onPointerDown(n){this.session=new Tw(n,this.createPanHandlers(),{transformPagePoint:this.node.getTransformPagePoint(),contextWindow:kw(this.node)})}createPanHandlers(){const{onPanSessionStart:n,onPanStart:i,onPan:o,onPanEnd:a}=this.node.getProps();return{onSessionStart:pu(n),onStart:pu(i),onMove:pu(o),onEnd:(c,u)=>{delete this.session,a&&Ce.postRender(()=>a(c,u))}}}mount(){this.removePointerDownListener=So(this.node.current,"pointerdown",n=>this.onPointerDown(n))}update(){this.session&&this.session.updateHandlers(this.createPanHandlers())}unmount(){this.removePointerDownListener(),this.session&&this.session.end()}}let mu=!1;class bC extends _.Component{componentDidMount(){const{visualElement:n,layoutGroup:i,switchLayoutGroup:o,layoutId:a}=this.props,{projection:c}=n;c&&(i.group&&i.group.add(c),o&&o.register&&a&&o.register(c),mu&&c.root.didUpdate(),c.addEventListener("animationComplete",()=>{this.safeToRemove()}),c.setOptions({...c.options,layoutDependency:this.props.layoutDependency,onExitComplete:()=>this.safeToRemove()})),wa.hasEverUpdated=!0}getSnapshotBeforeUpdate(n){const{layoutDependency:i,visualElement:o,drag:a,isPresent:c}=this.props,{projection:u}=o;return u&&(u.isPresent=c,n.layoutDependency!==i&&u.setOptions({...u.options,layoutDependency:i}),mu=!0,a||n.layoutDependency!==i||i===void 0||n.isPresent!==c?u.willUpdate():this.safeToRemove(),n.isPresent!==c&&(c?u.promote():u.relegate()||Ce.postRender(()=>{const h=u.getStack();(!h||!h.members.length)&&this.safeToRemove()}))),null}componentDidUpdate(){const{visualElement:n,layoutAnchor:i}=this.props,{projection:o}=n;o&&(o.options.layoutAnchor=i,o.root.didUpdate(),Ch.postRender(()=>{!o.currentAnimation&&o.isLead()&&this.safeToRemove()}))}componentWillUnmount(){const{visualElement:n,layoutGroup:i,switchLayoutGroup:o}=this.props,{projection:a}=n;mu=!0,a&&(a.scheduleCheckAfterUnmount(),i&&i.group&&i.group.remove(a),o&&o.deregister&&o.deregister(a))}safeToRemove(){const{safeToRemove:n}=this.props;n&&n()}render(){return null}}function Pw(e){const[n,i]=pw(),o=_.useContext(ah);return C.jsx(bC,{...e,layoutGroup:o,switchLayoutGroup:_.useContext(bw),isPresent:n,safeToRemove:i})}const SC={pan:{Feature:xC},drag:{Feature:wC,ProjectionNode:fw,MeasureLayout:Pw}};function 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Continuous behavioral intelligence moves understanding earlier, before an incident takes shape.","content":[{"type":"heading","text":"How continuous behavioral understanding helps security AI recognize risk as it unfolds"},{"type":"paragraph","text":"The first wave of generative AI in security has been easy to recognize. Large language models are being given access to alerts and logs so analysts can ask questions in natural language, summarize incidents, explain detections, and determine what to investigate next. These capabilities are useful because they can help analysts work faster and make complex security systems easier to navigate. They also reflect a familiar pattern in how new technologies enter security, where the first step is often to improve the workflows teams already have."},{"type":"paragraph","text":"The larger opportunity is to rethink where intelligence enters the security process. Today, much of security AI becomes useful only after an alert has fired or an analyst has started an investigation. By that point, the system is already reacting to something it has identified as noteworthy."},{"type":"paragraph","text":[{"text":"The next phase of security AI will move intelligence earlier in the process, toward systems that "},{"href":"https://ent.ai/blog/the-future-of-security-lives-where-work-happens/","text":"continuously understand enterprise behavior"},{"text":", preserve context over time, and recognize meaningful changes as they unfold. The goal is not simply to help analysts understand incidents faster. It is to help security systems understand behavior well enough to recognize risk before an incident fully takes shape."}]},{"type":"heading","text":"Security telemetry is not language"},{"type":"paragraph","text":"Most generative AI architectures were designed around language, which makes it tempting to apply the same approach to security telemetry by retrieving relevant logs, placing them into a model’s context, and asking an LLM to reason about the activity. Enterprise behavior does not exist as a collection of documents, and a single event is rarely meaningful on its own. A user opening an application, authenticating to a service, executing a command, or accessing a file may all be completely legitimate."},{"type":"paragraph","text":"The meaning comes from the context around those actions, including whether the behavior is normal for that user, whether the device has behaved this way before, what happened immediately beforehand, which applications, identities, and policies are involved, and how the activity compares with historical patterns."},{"type":"paragraph","text":"Security is inherently longitudinal, which means understanding it requires models that can preserve relationships across users, devices, applications, identities, policies, and time. That is fundamentally different from asking a language model to summarize text."},{"type":"heading","text":"From alert intelligence to behavioral intelligence"},{"type":"paragraph","text":"Much of today’s security AI begins once something has already been identified as interesting. An alert fires, an analyst investigates it, and AI helps summarize the relevant information and determine what to do next."},{"type":"paragraph","text":"The more significant opportunity is to move intelligence earlier in that process by continuously building an understanding of enterprise behavior. Instead of asking AI only to interpret alerts, security systems can learn how users normally behave, how systems typically interact, which patterns are expected, and which changes may be meaningful."},{"type":"paragraph","text":"Rather than waiting for isolated events to become alerts, security intelligence can evaluate a continuous stream of actions in context as work unfolds. This shifts the role of AI from helping analysts investigate known events to helping identify unusual behavior before an analyst knows which question to ask."},{"type":"heading","text":"Context matters more than model size"},{"type":"paragraph","text":[{"text":"Raw model intelligence is not enough in security. A model also needs to understand the environment in which activity is taking place. A highly capable general-purpose model without that c

56ontext may be less useful than a smaller system that understands "},{"href":"https://ent.ai/blog/when-helpful-becomes-harmful","text":"what normal behavior looks like inside"},{"text":" that organization."}]},{"type":"paragraph","text":"That understanding starts at the endpoint, where user activity is continuously unfolding. Individual actions may look harmless on their own. Their meaning becomes clearer when they are understood alongside behavioral history, organizational context, and policy. Security intelligence emerges when telemetry is connected to that broader understanding of how people, applications, and systems normally behave."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/Blog%20images/Telemetry.png?width=1600","alt":"Telemetry","caption":"From Telemetry to Organizational Context"},{"type":"paragraph","text":[{"text":"At "},{"href":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/Marketing/Ent%20Solutions%20Brief%202026.pdf","text":"Ent"},{"text":", we are building AI models that turn endpoint telemetry and user activity into behavioral representations informed by organizational context and policy. This gives security systems a continuously updated understanding of what normal looks like, providing richer context for both real-time decisions at the endpoint and deeper reasoning when additional analysis is needed."}]},{"type":"heading","text":"Security intelligence has to be continuous"},{"type":"paragraph","text":"Security decisions often need to happen in real time, especially when important activity is unfolding continuously on the endpoint. In those moments, milliseconds matter. Continuous security requires intelligence that can keep pace with the stream of actions as they occur, interpreting those actions in context rather than waiting for individual events to become alerts."},{"type":"paragraph","text":"Continuous endpoint intelligence operates differently from slower agent workflows that investigate activity after something has already surfaced. Those agents remain valuable for deeper reasoning, investigation, and orchestration, but prevention operates on a different timescale."},{"type":"paragraph","text":"That points toward a hierarchical architecture in which smaller models perform continuous behavioral inference with low latency at the endpoint, while larger reasoning systems provide deeper analysis, correlate activity across the environment, and orchestrate more complex response workflows. The two layers serve different purposes. Endpoint intelligence supports immediate understanding and prevention, while larger agents provide deeper investigation when additional analysis is required."},{"type":"paragraph","text":[{"text":"At the endpoint, the UI becomes part of that response layer, enabling direct interaction with end users and supporting interventions as "},{"href":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/Marketing/ENT-DATASHEET-V3b.pdf","text":"risky activity occurs."}]},{"type":"paragraph","text":"Figure 2 shows how the system combines activity happening now with context learned over time. At the endpoint, inference evaluates the live stream of actions alongside context embeddings that represent previously learned normal behavior."},{"type":"paragraph","text":"Separately, context capture supplies new endpoint context to the broader learning system, which builds and updates behavioral baselines across users, departments, and the enterprise."},{"type":"paragraph","text":"Those updated baselines are periodically returned to endpoints, helping inference support an immediate UI intervention or trigger an investigation agent when deeper analysis is required."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/Blog%20images/AI%20Inference%20Architecture.png?width=1600","alt":"AI Inference Architecture","caption":"AI Inference Architecture for Continuous Behavioral Understanding"},{"type":"paragraph","text":"The goal is not to replace large language models, which remain valuable for reasoning, investigation, and orchestration, but to use them as one layer within a broader system. In this architecture, inference at the endpoint supports continuous, time-sensitive decisions, while larger models and agents handle more complex analysis and response. Together, these layers move security AI beyond explaining what has already happened and toward recognizing and preventing risk as it unfolds."},{"type":"heading","text":"Building for continuous understanding"},{"type":"paragraph","text":"The opportunity for security AI is to move from helping teams make sense of alerts to recognizing meaningful behavior as it happens. Getting there requires systems that can maintain an understanding of what is normal for an organization and use that understanding to identify risk earlier. It also requires security intelligence that can operate at the speed of the activity it is protecting, rather than waiting for a slower investigative workflow to determine what happened."},{"type":"paragraph","text":"That is the direction we are building toward at Ent, creating security that continuously understands behavior and helps teams act before risky activity becomes an incident."}]},{"slug":"black-hat-2026-confirmed-it-security-has-to-move-closer-to-where-work-happens","title":"Black Hat 2026 Confirmed It: Security Has to Move Closer to Where Work Happens","authors":[{"name":"Janani Nagarajan","title":"VP of Product Marketing at Ent"}

56],"image":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/Blog%20images/u2872878144_A_black_and_white_image_of_a_shape_merging_with_an__d8cdc1df-9170-45da-992c-31b5fa52fee5.png?width=1600","date":"2026-08-13","updated":"2026-09-02","readMinutes":8,"excerpt":"Janani Nagarajan|VP of Product Marketing at Ent","seoTitle":"Black Hat 2026 Confirmed It: Security Has to Move Closer to Where Work Happens","metaDescription":"At Black Hat 2026, one theme kept surfacing: security has to move closer to where work happens. Why intent—not just activity—is the future of prevention.","content":[{"type":"paragraph","text":"Black Hat USA 2026 was one of Ent’s biggest weeks, and one message came through clearly: security architecture needs to be rethought for the AI era, with prevention back at the center."},{"type":"paragraph","text":"Across meetings with customers, prospects, and industry experts, live demos, and our hands-on Discovery workshops, we heard that the current security stack can no longer keep pace with how work happens."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/img_8554_720.jpg?width=1600","alt":"img_8554_720","caption":"Ent signage at Black Hat 2026"},{"type":"paragraph","text":"Work now spans browsers, SaaS applications, AI tools, local files, and automated workflows. Attackers operate through many of the same tools. Their activity can appear legitimate because the user is authenticated, the application is approved, and each action looks normal on its own."},{"type":"paragraph","text":"The strongest conversations at Black Hat focused on how security teams can recognize and stop that activity before it causes damage."},{"type":"heading","text":"AI is making familiar security problems move faster"},{"type":"paragraph","text":"AI and agentic messaging dominated the conference, but most security leaders were not looking for another product category called “AI security.” They were trying to solve problems they already own: ineffective DLP, insider risk, unsanctioned AI use, application control, social engineering and click-fix attacks, and investigations that take too long or lack the right evidence."},{"type":"paragraph","text":"Employees are putting company data into AI tools. Agents are taking actions across applications and files. On the flip side, attackers are using AI to find vulnerabilities, generate exploits, and coordinate campaigns faster. The activity still involves data, applications, identities, and endpoints. The speed and volume have changed."},{"type":"paragraph","text":"A Microsoft keynote described how AI is lowering the cost of vulnerability discovery and exploit development. Work that once required specialized skills and significant time can increasingly be automated. That puts more pressure on defenders to prevent attacks earlier instead of relying on alerts and investigations after execution."},{"type":"paragraph","text":"Several conversations at Black Hat raised the same architectural concern. Cloud-dependent security introduces delay when a decision needs to be made immediately. It can also require organizations to send sensitive workplace context outside their environment for analysis."},{"type":"paragraph","text":"Security controls need to make more of these decisions locally, while the action is still underway."},{"type":"heading","text":"Existing tools see pieces of the activity"},{"type":"paragraph","text":"Traditional security tools are very good at answering specific questions."},{"type":"paragraph","text":"EDR can tell you what process was executed. DLP can tell you when governed data moved through a monitored channel. Identity tools can tell you who authenticated and are authorized to perform certain actions. SIEM can bring those signals together and SOC platforms can assemble them for investigation."},{"type":"paragraph","text":"Those tools remain necessary. The gap appears when an approved user, application, or AI agent performs an action that looks legitimate on its own. The question that matters now is why an action is happening right now and whether it should be allowed to continue."},{"type":"paragraph","text":"An engineer may use SSH every day as part of the job. The same action could become risky when it follows an unusual file download or connects to a system the engineer has never accessed. An employee may upload a document to an approved AI tool, but the action requires a different response if the document contains customer data and the tool is not sanctioned for that use."},{"type":"paragraph","text":"The action alone doesn’t always tell you enough."},{"type":"paragraph","text":"And more telemetry isn’t necessarily the answer. What matters is being able to interpret the action in context and understand what it means. The same action can be routine for one user and risky for another. Security team

56s need the sequence around it: who performed it, what data was involved, which applications and systems were touched, whether it fits the person’s role, and what happened immediately before it."},{"type":"paragraph","text":"As Andrew Cal, CISO at WestCap, explains,"},{"type":"paragraph","text":"“Modern work creates signals that can look identical on the surface, even when the intent is completely different. Ent reads the chain of events and helps security teams understand the difference between normal work and risky actions.”"},{"type":"paragraph","text":"That’s where intent matters."},{"type":"paragraph","text":[{"text":"This is the foundation of "},{"href":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/Marketing/Ent%20Solutions%20Brief%202026.pdf","text":"Intent-Aware Workspace Security"},{"text":", an approach that brings together endpoint telemetry, behavioral context, organizational policy, and AI reasoning to understand why activity is happening as work happens and enable intervention before risky actions become incidents."}]},{"type":"heading","text":"From watching an attack to stopping It"},{"type":"paragraph","text":"At Black Hat, we wanted attendees to experience that difference for themselves."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/Blog%20images/4d21e832-68dd-4d5e-841a-4546872faed4.png?width=1600","alt":"4d21e832-68dd-4d5e-841a-4546872faed4","caption":"Ent Discovery Workshop at Black Hat 2026"},{"type":"paragraph","text":"In our Discovery workshops: Threat Investigation Files, participants didn’t sit through another presentation. They sat down at an operator console and worked through the investigation themselves."},{"type":"paragraph","text":"They watched an attack unfold across a user, an endpoint, applications, and other systems and saw what happened after access was gained. They investigated the activity using behavioral timelines and contextual evidence. Then they saw how user intervention could change the outcome and why it needed to happen at the endpoint, before the damage occurs."},{"type":"paragraph","text":"The workshops brought the concept of intent-aware security to life. When activity looks legitimate on the surface, understanding the sequence of behavior and the context surrounding it can make the difference between another alert post-incident and meaningful intervention in real-time."},{"type":"paragraph","text":"One workshop participant summed it up this way."},{"type":"paragraph","text":"“I didn’t know what to expect, but it wasn’t this. I have nothing that does this today, you’re solving the hardest part of our investigation and no one is doing this. I can’t wait to show my team.”"},{"type":"paragraph","text":"That reaction reflected something we heard throughout the week. Security teams don’t need another pile of telemetry. They need help inferring the context and intent behind an action, pinpoint deviations from regular work, and what to do next."},{"type":"heading","text":"Prevention needs more than a block button"},{"type":"paragraph","text":"Real-time prevention does not mean blocking every unusual action."},{"type":"paragraph","text":"One of the clearest themes at Black Hat was a shift from reactive detection and response toward proactive prevention. It showed up in conversations across the conference, not just at our booth."},{"type":"paragraph","text":"Visibility is only valuable if it can change the outcome."},{"type":"paragraph","text":"A good control should apply the right response for the situation. It may warn the user, ask for a reason, redirect the user to an approved application, require another approval, or block the action when the risk is clear."},{"type":"paragraph","text":"Context determines which response makes sense."},{"type":"paragraph","text":"Security teams don’t just want to know that something risky happened. They want enough context to make a decision while the action is still unfolding."},{"type":"paragraph","text":"That means moving from detecting and reconstructing incidents after the fact toward intervening at the moment risk occurs. Controls that understand the user, role, data, application, and sequence of activity can be more operationally effective than blunt controls."},{"type":"paragraph","text":"Ent Founder Elias (Lou) Manousos with Richard Sherman at Decibel GameDay."},{"type":"paragraph","text":"The same approach can govern people and AI agents. If an agent tries to move sensitive data, install an unsanctioned application, or execute an action outside its approved role, the policy should apply regardless of whether it was a human or an agent-driven workflow."},{"type":"heading","text":"AI Agents are redefining endpoint security"},{"type":"paragraph","text":"AI is changing how employees work and how attackers operate."},{"type":"paragraph","text":"Employees can move sensitive information into AI tools in seconds. Attackers can automate social engineering and parts of the attack lifecycle. AI agents can act across applications and systems faster than security team

56s can review each step."},{"type":"paragraph","text":"But the underlying problems are often familiar."},{"type":"paragraph","text":"Sensitive data still leaves the organization. Attackers still abuse trusted applications. Insiders still work outside expected workflows. Social engineering still convinces users to take actions they shouldn’t. AI increases the speed, scale, and volume of that activity."},{"type":"paragraph","text":"As Jon Sakoda, Founding Partner at Decibel, puts it,"},{"type":"paragraph","text":"“AI has been a killer app for hackers and offensive researchers, but the industry is waiting for a novel defensive solution that can keep up with the modern era of LLMs. Ent has reimagined what is possible to protect the endpoint by using specialized AI models and adaptive policy enforcement to detect and prevent malicious activity in real time. It’s a game changer for cybersecurity teams who need a paradigm shift to defend their workforce against LLM-based attacks.”"},{"type":"paragraph","text":[{"text":"That shift was evident throughout Black Hat. Security leaders aren’t simply looking for more AI security products. Many are trying to solve problems they already own, including data protection, "},{"href":"https://preview.d2oftr9oq6im4e.amplifyapp.com/blog/when-trust-becomes-the-attack-vector/","text":"insider risk,"},{"text":" application and AI usage control, investigations, and rapid response."}]},{"type":"heading","text":"Protecting work requires trust"},{"type":"paragraph","text":"As security moves closer to where work happens, trust becomes essential."},{"type":"paragraph","text":"Understanding behavior at the endpoint naturally raises questions about privacy, what telemetry is collected, and how that information is used."},{"type":"paragraph","text":"Organizations need control over what is collected, where security data resides, and how behavioral information is used. The goal is to capture the context needed to understand risk without turning security into employee surveillance. This requires clear policies, controlled access to behavioral data, and an architecture that lets customers keep sensitive context inside their environment."},{"type":"paragraph","text":"Protecting work as it happens requires an approach that balances security with privacy and gives organizations control over how they protect their human and AI workforce."},{"type":"heading","text":"What comes next"},{"type":"paragraph","text":"The response we experienced at Black Hat reinforced that the market is ready for a different approach. We saw a growing interest in endpoint security that can understand human and AI activity and intervene while risk is still unfolding."},{"type":"paragraph","text":"The energy around Gen3 endpoint security, prevention, securing human and AI agent workflows, and real-time intervention was impossible to miss. Investors, customers, partners, and practitioners were all wrestling with versions of the same question. How does security keep up when risky activity increasingly looks like legitimate work?"},{"type":"paragraph","text":"For Ent, the answer starts with intent."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/DSCF2610.jpg?width=1600","alt":"DSCF2610","caption":"Ent booth at Black Hat 2026"},{"type":"paragraph","text":"It means working towards a vision where organizations understand why an action is happening, apply the right response, and give investigators evidence they can follow. It also means working with the EDR, DLP, SIEM, and SOC systems customers already use."},{"type":"paragraph","text":"We left Black Hat 2026 energized by the conversations, the engagement in our workshops, and the momentum around what we’re building."},{"type":"heading","text":"See Ent in Action"},{"type":"paragraph","text":"Learn how Ent helps security teams understand intent, intervene before risky actions become incidents, and protect human and AI-driven work as it happens."},{"type":"paragraph","text":[{"text":"See the platform in action and schedule a demo at "},{"href":"http://ent.ai/contact","text":"ent.ai/contact."}]},{"type":"paragraph","text":[{"text":"Follow us on "},{"href":"https://x.com/Ent_Security","text":"X"},{"text":" and "},{"href":"https://www.linkedin.com/company/ent-security/posts/?feedView=all","text":"LinkedIn"},{"text":"."}]}]},{"slug":"when-helpful-becomes-harmful","title":"When Helpful Becomes Harmful","authors":[{"name":"Janani Nagarajan","title":"VP of Product Marketing at Ent"}

56],"image":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/When%20Helpful%20Becomes%20Harmful.png?width=1600","date":"2026-06-26","updated":"2026-06-26","readMinutes":7,"excerpt":"Janani Nagarajan | VP of Product Marketing at Ent","seoTitle":"When Helpful Becomes Harmful","metaDescription":"AI adoption is accelerating, but so are the risks. Learn how organizations can prevent sensitive data exposure at the point of use.","content":[{"type":"heading","text":"The hidden security risk in your AI adoption strategy"},{"type":"paragraph","text":"AI tools are not going away. The question is not whether to allow AI adoption, but whether you can see and control what happens at the point of use."},{"type":"paragraph","text":"Generative AI has moved from experiment to the default form of work in many enterprises. Engineers debug with it. HR teams draft with it. Finance analysts summarize spreadsheets with it. Legal reviews contracts with it. The productivity gains are real, and employees who have adopted these tools are unlikely to give them up."},{"type":"paragraph","text":"Generative AI tools are integrated into modern workflows"},{"type":"paragraph","text":"The problem is that AI adoption has outpaced the governance structures meant to contain it. Every time an employee pastes content into a chatbot, that data leaves the organization's control. The model receives it, the service provider processes it, and what happens next depends entirely on the provider's data-handling policies, not yours."},{"type":"paragraph","text":[{"text":"The scale of this exposure is significant. According to the LayerX Enterprise AI and SaaS Data Security Report, "},{"href":"https://go.layerxsecurity.com/hubfs/LayerX_Enterprise_AI_and_SaaS_Data_Security_Report.pdf?","text":"77% of enterprise employees "},{"text":"paste data into generative AI prompts. 1 in 5 of those past events includes personally identifiable information or payment data. The inputs span the full spectrum of what organizations work hardest to protect: source code, customer records, internal meeting notes, product roadmaps, financial data, and protected health information."}]},{"type":"paragraph","text":[{"text":"The consequences of this unregulated data flow are not inconsequential. Regulatory violations under "},{"href":"https://en.wikipedia.org/wiki/General_Data_Protection_Regulation","text":"GDPR"},{"text":", "},{"href":"https://www.ncbi.nlm.nih.gov/books/NBK500019/","text":"HIPAA"},{"text":", and sector-specific frameworks can follow a single incident. Proprietary code submitted for debugging may enter a training pipeline accessible to anyone. Competitive intelligence embedded in a meeting transcript summary can be exposed without ever triggering a conventional alert."}]},{"type":"paragraph","text":"Most organizations respond to this threat with one of two strategies: blanket restrictions that impede legitimate work and drive shadow IT, or passive acceptance due to a lack of visibility into what is actually happening at the point of use. Neither is a sustainable answer."},{"type":"paragraph","text":"Closing the gap requires understanding actual user behaviors at scale, detecting when patterns shift toward unusual data access or external submissions, and distinguishing genuine risk from routine productivity in real time. It also requires overlaying user intent and organizational context onto individual actions, so that security teams can see what is happening, understand why, and act before data leaves the building. Let's look at a couple of examples to understand why this is such a pervasive problem, and how Ent changes the equation."},{"type":"heading","text":"What Unrestricted AI Access Actually Looks Like"},{"type":"paragraph","text":"In 2023, Samsung Semiconductor lifted an internal ban on generative AI tools and permitted employees to use them for work-related tasks. Within three weeks, three separate incidents had already occurred."},{"type":"paragraph","text":"In the first, an engineer pasted the semiconductor measurement source code into an external AI service to debug a defect-detection program. In the second, another employee submitted chip-defect detection code to the same service for optimization assistance. In the third, an employee entered the full transcript of an internal meeting to generate a summary."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.

56net/hubfs/243241691/u2872878144_A_black_and_white_image_of_multiple_app_icons_on__818ead72-9000-409d-8919-59c4acc58cf1_0.png?width=1600","alt":"u2872878144_A_black_and_white_image_of_multiple_app_icons_on__818ead72-9000-409d-8919-59c4acc58cf1_0","caption":"Copying and pasting sensitive information into external AI tools"},{"type":"paragraph","text":"None of these employees had malicious intent. All three were trying to do their jobs faster. The problem was that sensitive information was being submitted to a third-party AI platform outside Samsung's control. Once the data left the organization, Samsung could no longer directly govern how it was processed, retained, or protected. Samsung immediately issued a company-wide restriction on the use of generative AI and began developing an internal alternative. The incidents made global headlines and prompted organizations across multiple industries to re-evaluate how employees interact with external AI services."},{"type":"heading","text":"The Visibility Gap: When AI Moves Beyond Enterprise Oversight"},{"type":"paragraph","text":"The intuitive response is to block AI tools. The problem is that blanket restrictions do not hold when the productivity incentive is strong enough."},{"type":"paragraph","text":"Employees who use generative AI complete tasks faster, produce more polished outputs, and encounter fewer workflow bottlenecks. The efficiency gains are structural, not incidental. When organizations restrict access, employees find workarounds, and those workarounds are less visible, not less risky."},{"type":"paragraph","text":[{"text":"That dynamic is reflected in the data. According to ITdaily, "},{"href":"https://itdaily.com/news/security/generatieve-ai-data-breaches/","text":"82% of generative AI prompt submissions "},{"text":"occur through unmanaged personal accounts. These interactions often occur outside traditional enterprise oversight."}]},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/u2872878144_A_black_and_white_image_of_bar_chart_on_a_laptop__f63a66b2-4111-4079-ba4d-6717fc3e640b_0.png?width=1600","alt":"u2872878144_A_black_and_white_image_of_bar_chart_on_a_laptop__f63a66b2-4111-4079-ba4d-6717fc3e640b_0","caption":"The growing challenge of maintaining visibility across enterprise AI usage"},{"type":"paragraph","text":"The problem is further compounded by the proliferation of tools. Generative AI isn’t confined to a handful of dedicated platforms. It’s embedded in communication tools, productivity suites, customer engagement platforms, and operating system interfaces. Each of those integrations has different data-handling terms, retention policies, and enterprise visibility. Managing the risk means knowing about all of them, in real time, across every user in the organization. Most security stacks are not designed for that."},{"type":"heading","text":"AI Runs Beyond Traditional Endpoint Visibility"},{"type":"paragraph","text":"The paste-into-a-chatbot problem is the visible half of AI risk. The harder half is where AI actually runs."},{"type":"paragraph","text":"Developers and AI agents do not just type into web tools. They execute code in containers, spin up virtual machines, call hosted services, and run AI workloads inside sandboxed environments built for speed and isolation. Those runtimes are exactly where modern work is moving, and they are precisely where traditional endpoint tooling goes dark. Traditional endpoint tooling was designed primarily to provide visibility into processes, files, and network activity on the host operating system."},{"type":"paragraph","text":"Additionally, AI workloads increasingly run in containers, virtual machines, and third-party runtime environments, making it significantly more challenging to maintain the same level of visibility."},{"type":"paragraph","text":"That can create a compounding problem. The very environments that make AI development faster and, in some respects, safer, by isolating workloads from the host, also remove them from the line of sight of the tools meant to secure them. An AI agent running in a container can read a secret, call an external API, or move data, and the host-based EDR sees a process it cannot inspect. The isolation that protects the host is the same isolation that blinds the defender. Organizations gain a sandbox and lose their visibility in the same step."},{"type":"paragraph","text":"This is why the AI data-exposure problem is not just about employees pasting text into browsers. It extends into the runtimes where agents and developers operate, where the action is real, consequential, and almost entirely unobserved by the existing stack. Closing the chatbot blind spot without closing the runtime blind spot leaves the larger half of the problem untouched."},{"type":"heading","text":"How Ent Closes the Gap"},{"type":"paragraph","text":"Ent is purpose-built for this problem. Traditional DLP relies on deterministic rules: block this file type, flag this keyword, alert on this destination. That approach breaks down in the AI context because the risk is not defined by what is being moved, but by what is being revealed and to whom. An employee pasting a paragraph of text into a browser tab looks identical to any other copy-paste event. Without behavioral context and user intent, no rule-based system can reliably distinguish between them."},{"type":"paragraph","text":"Ent observes AI tool usage in real time, including what data is being formed, combined, and submitted. When an employee is about to paste patient records into a browser-based AI assistant, Ent identifies the content, assesses the risk, and intervenes at the moment of decision. The intervention is proportional: Ent can explain the risk in plain language, guide the user to a compliant alternative, or automatically obfuscate sensitive fields before the submission is processed."},{"type":"paragraph","text":"Because Ent operates as a lightweight endpoint agent rather than a 

56network proxy or application plugin, it observes all activity regardless of whether the employee is using a corporate-licensed platform or a personal account. Ent also adapts to each user's workflow. A security engineer submitting code for review is profiled differently from an HR manager who does the thing. Behavioral context shapes the response, so security teams are never choosing between blocking everything and knowing nothing."},{"type":"heading","text":"Stopping Sensitive Data Before It Leaves the Organization"},{"type":"paragraph","text":"Consider a recent example from a global organization in which WhatsApp could not be blocked due to regional communication requirements. An HR employee, working through a personnel complaint file, used WhatsApp's built-in Meta AI feature (an unsanctioned AI tool) to generate a summary of the file."},{"type":"paragraph","text":"The file contained medical diagnoses and personnel records protected under HIPAA. No network-layer control could see the interaction because it occurred inside a messaging application that the organization could not restrict. No traditional DLP tool flagged the behavior because it occurred within an application that the security stack could not inspect"},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/u2872878144_A_black_and_white_image_of_a_lock_on_a_laptop_scr_527c61cf-302b-4c4e-aad5-565620cb3ac6_0.png?width=1600","alt":"u2872878144_A_black_and_white_image_of_a_lock_on_a_laptop_scr_527c61cf-302b-4c4e-aad5-565620cb3ac6_0","caption":"Protection of sensitive organizational data from unauthorized exposure"},{"type":"paragraph","text":"Ent saw it. The endpoint agent identified the document contents, recognized the sensitive data categories involved, and guided the user through obfuscating the critical fields before the content was processed by Meta AI. The submission was modified before it reached the model. The submission was modified before it reached the AI model, reducing the risk of a potential HIPAA compliance incident."},{"type":"heading","text":"The Control Point Is the Endpoint"},{"type":"paragraph","text":"AI tools are not going away. Employees will continue to use them, with or without organizational approval, because the productivity value is too significant to ignore. The question is not whether to allow AI adoption, but whether you can see and control what happens at the point of use."},{"type":"paragraph","text":"Workforce security gives security teams that visibility. By operating at the endpoint, understanding intent, and acting in real time, Ent converts a persistent and growing blind spot into a manageable risk, without blocking the productivity that employees and the business depend on."},{"type":"paragraph","text":[{"text":"To learn more about securing enterprise AI adoption and preventing sensitive data exposure at the point of use, visit "},{"href":"https://ent.ai/","text":"ent.ai."}]},{"type":"paragraph","text":[{"text":"Follow us on "},{"href":"https://x.com/Ent_Security","text":"X"},{"text":" and "},{"href":"https://www.linkedin.com/company/ent-security/posts/?feedView=all","text":"LinkedIn"},{"text":". To talk to us and see our product in action, schedule a demo."}]}]},{"slug":"when-trust-becomes-the-attack-vector","title":"When trust becomes the attack vector","authors":[{"name":"Janani Nagarajan","title":"VP of Product Marketing at Ent"}],"image":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/u2872878144_Imagine_an_ultra_high_resolution_black_and_white__c0fc226f-fa21-44d1-8a01-7cd47603ff4b_0-1.png?width=1600","date":"2026-06-18","updated":"2026-06-26","readMinutes":11,"excerpt":"Janani Nagarajan | VP of Product Marketing at Ent Rethinking modern insider risk, and telling malicious from a mistake","seoTitle":"When trust becomes the attack vector","metaDescription":"Most insider risk comes from trusted users, not bad actors. Learn why context and intent matter more than alerts alone.","content":[{"type":"heading","text":"Rethinking modern insider risk, and telling malicious from a mistake"},{"type":"paragraph","text":"Insider threats occupy a uniquely difficult position in security. Unlike external attacks that originate outside the perimeter, insider risk begins with access deliberately granted. The user is already inside, already implicitly trusted, and their daily activity is presumed to be legitimate work."},{"type":"paragraph","text":"But insider risk is broader than the word \\"threat\\" suggests. It is easy to picture the malicious actor: the operative, the fraudster, the person who joined to harm. They are real, and we will look at them closely. Yet most insider risk does not come from bad people. It comes from good people moving fast."},{"type":"paragraph","text":"A new employee who does not yet know the right way to do something. An engineer who takes the convenient path because the secure one is not obvious. Someone who pastes the wrong data into the wrong tool because they are trying to finish a task, not cause an incident. The same access that lets people do their jobs lets them make mistakes, and at scale, those mistakes carry as much risk as deliberate abuse."},{"type":"paragraph","text":"The challenge is not that behavioral signals are absent. It is that connecting those signals into something meaningful requires understanding context that most security tools are not equipped to process."}

56,{"type":"paragraph","text":"Take a few common scenarios: data exfiltration looks like a file transfer. A careless paste looks like a productive one. Access abuse looks like authorized use. Privilege escalation blends into normal administrative activity. The patterns that matter only become visible when individual actions are evaluated against a deeper understanding of who the user is, what their role demands, and whether a given sequence of events actually makes sense."},{"type":"paragraph","text":"Traditional security tools were built around a different model. They look for known bad artifacts, rule violations, and policy exceptions. That approach works well against deterministic threats. It struggles when the risk is adaptive, human-shaped, and operating inside the bounds of legitimate access, whether the person behind it means harm or not. A few categories of insider risk illustrate this gap clearly."},{"type":"heading","text":"The Trojan employee: When getting hired is the attack"},{"type":"paragraph","text":"One of the most organized insider threat operations in recent memory did not begin with a zero-day exploit or a phishing link. It began with a job application."},{"type":"paragraph","text":[{"text":"According to "},{"href":"https://www.justice.gov/opa/pr/justice-department-announces-coordinated-nationwide-actions-combat-north-korean-remote?","text":"U.S. government investigations"},{"text":", North Korean state-sponsored IT worker schemes have built a sophisticated infrastructure for placing fraudulent workers inside American and European companies, including Fortune 500 firms. The operation functions like an industrial hiring machine, with specialists dedicated to creating false identities, crafting resumes, preparing candidates for interviews, and managing the employment lifecycle once a position is secured."}]},{"type":"paragraph","text":"To get past the hiring process, operatives have stolen the identities of American citizens, forged government documents, and used AI-generated imagery and voice conversion tools to pass live video interviews convincingly. In some cases, cooperative participants physically appear at offices or provide cover by lending their identities to operators working remotely."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/u2872878144_Imagine_a_black_and_white_image_composed_of_an_em_40b7319c-b114-4c2c-bb52-b7f5b8bd041e_0.png?width=1600","alt":"u2872878144_Imagine_a_black_and_white_image_composed_of_an_em_40b7319c-b114-4c2c-bb52-b7f5b8bd041e_0","caption":"Figure 1. Insider Access as an Attack Vector"},{"type":"paragraph","text":[{"text":"Once a position is secured, the actual work is handed off. A separate workforce, operating through VPNs configured to appear as US-based connections, performs the job while the hired employee collects a paycheck. In documented cases, a single facilitator maintained a laptop farm containing more than "},{"href":"https://www.justice.gov/opa/pr/arizona-woman-sentenced-17m-information-technology-worker-fraud-scheme-generated-revenue?","text":"90 company-issued laptops"},{"text":", enabling North Korean IT workers to access employer-issued devices remotely across hundreds of organizations."}]},{"type":"paragraph","text":[{"text":"The financial scope is significant. In 2024, a United Nations Panel of Experts report estimated that the technology sector remains a key moneymaker for North Korea, with an estimated 3,000 North Korean IT workers abroad and another 1,000 operating inside North Korea, "},{"href":"https://www.justice.gov/usao-dc/pr/arizona-woman-sentenced-17m-it-worker-fraud-scheme-illegally-generated-revenue-north?","text":"generating $250 million to $600 million annually"},{"text":". Beyond the financial impact, successful placements have, in some cases, led to intellectual property theft and the deployment of malware within corporate environments."}]},{"type":"paragraph","text":"What makes this so difficult to detect is that the activity, on its surface, looks like work. Files are accessed. Systems are used. The authenticated user is credentialed and behaving within the scope of their assigned role. Traditional security tools were not built to ask whether the person behind the keyboard is actually the person who was hired for the job."},{"type":"heading","text":"Targeting the trusted: Social engineering through a fake job offer"},{"type":"paragraph","text":"A related category of insider risk targets employees from the outside, using professional trust as the delivery mechanism."},{"type":"paragraph","text":"North Korean-linked threat groups have run sustained campaigns against software developers, particularly software developers and technical professionals active on public professional platforms. The approach is methodical: fabricated professional profiles and company pages establish credibility, while developer-focused platforms, repositories, and job opportunities are used to build trust and attract prospective targets."},{"type":"paragraph","text":[{"text":"Once a target engages, they are directed through what appears to be a standard onboarding process. Somewhere in that workflow, they are instructed to install packages from repositories seeded with malware, either through "},{"href":"https://en.wikipedia.org/wiki/Typosquatting","text":"typosquatting"},{"text":" of legitimate packages or through compromised repositories specifically designated for use as part of the work."}]},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.

56net/hubfs/243241691/u2872878144_Imagine_a_black_and_white_image_composed_of_a_clo_cafede23-9dd7-4f8b-a217-f8e034fdfd0f_2.png?width=1600","alt":"u2872878144_Imagine_a_black_and_white_image_composed_of_a_clo_cafede23-9dd7-4f8b-a217-f8e034fdfd0f_2","caption":"Figure 2. Typosquatting (or URL hijacking) is a cyberattack where criminals register misspelled or lookalike domains of popular websites"},{"type":"paragraph","text":[{"text":"Developers are a high-value target for several reasons. They hold significant permissions. They download, compile, and execute code as a routine part of their job. Their workflows move quickly, with little tolerance for friction that would slow delivery. And critically, the line between normal developer behavior and a threat is genuinely ambiguous without a clear picture of what that specific developer typically does. Documented incidents have linked these campaigns to "},{"href":"https://attack.mitre.org/groups/G1052/","text":"cryptocurrency theft"},{"text":", supply chain compromises, and the theft of sensitive corporate information."}]},{"type":"paragraph","text":"It is worth pausing on that last point, because it applies far beyond this campaign. The very thing that makes a developer a target, broad permissions and fast-moving work, is also what makes an honest developer mistake so easy. The malicious package install and the careless one look almost identical. That overlap is the heart of the insider risk problem."},{"type":"heading","text":"The everyday majority: When good people move fast"}

56,{"type":"paragraph","text":"The headlines go to nation-state operatives, but the volume of insider risk lives somewhere far more ordinary: in the new hire on day three, the employee racing to meet a deadline, the employee still learning how to navigate a new workplace."},{"type":"paragraph","text":"Consider how routine the risky moments are. A new employee, eager to be productive, moves a customer list to a personal drive so they can work over the weekend. An engineer under a deadline pastes a config file with live credentials into a public AI tool to debug it faster. A salesperson forwards a deck to a personal email because the VPN is slow. None of these people intends harm. Each person is trying to get work done and naturally chooses the most convenient path rather than the most secure one, often because the secure path was never clearly communicated."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/u2872878144_Imagine_a_black_and_white_image_composed_of_a_clo_8a1d5db9-e0df-4867-b9f7-34d73f4dcf1f_3.png?width=1600","alt":"u2872878144_Imagine_a_black_and_white_image_composed_of_a_clo_8a1d5db9-e0df-4867-b9f7-34d73f4dcf1f_3","caption":"Figure 3. Well-Intentioned Actions, Unintended Risk"},{"type":"paragraph","text":"These moments rarely trigger anything in a traditional stack because each action is authorized individually. And when they do surface, the typical response is a policy violation after the fact: a flag, a ticket, sometimes a conversation with a manager weeks later, long after the lesson would have mattered. The employee learns that they did something wrong, but not in the moment they were doing it, and not in a way that makes the right path easier next time."},{"type":"paragraph","text":"This is the larger truth about insider risk. The malicious insider and the well-meaning one generate the same ambiguous signals, and a program that only looks for bad actors will miss the much larger population of good people who need guidance, not suspicion. Treating every anomaly as a potential threat can erode trust and bury genuine risks in the noise. The goal is not to catch people. It is to understand what they are trying to do and help them do it safely."},{"type":"heading","text":"Why existing security tools were not built for this problem"},{"type":"paragraph","text":"These scenarios share a common structural failure. When viewed in isolation, none of the individual actions appears inherently risky. The file access is authorized. Installing the package is routine developer behavior. The remote session is opened through an approved tool. The paste into an AI tool is no different from thousands of others performed every day. The risk only becomes visible when these actions are evaluated in context."},{"type":"paragraph","text":"Traditional security tools are built around deterministic logic. They match events against known signatures and rule sets. They can tell you what happened. What they cannot tell you is whether it matters, whether this specific user in this specific context should be taking that action, or whether the behavior represents a genuine threat or simply someone trying to get their job done."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/u2872878144_Imagine_a_black_and_white_image_composed_of_a_pat_c900f151-aa46-42eb-9d62-fcd4dbcfb06f_3.png?width=1600","alt":"u2872878144_Imagine_a_black_and_white_image_composed_of_a_pat_c900f151-aa46-42eb-9d62-fcd4dbcfb06f_3","caption":"Figure 4: Approved tool usage without the right context rarely flags alerts"},{"type":"paragraph","text":"This helps explain why both endpoint detection and earlier-generation user behavior analytics have often struggled with insider risk. Behavioral anomalies generated by those systems are technically accurate but operationally ambiguous. Someone accessing files on a weekend is anomalous. Someone logging in from an unfamiliar location is anomalous. Neither of those signals, standing alone, tells an analyst anything actionable, and neither distinguishes the new hire who needs guidance from the operative who needs to be removed. When analysts are handed a queue of individually valid but contextually hollow alerts, the genuine threats get buried in the noise, and the teachable moments go unaddressed."},{"type":"paragraph","text":"Human-driven investigation is the fallback, but the timeline is the problem. Insider risk cases can take days to weeks to build. In that window, access has been transferred, sensitive data has moved, and the material damage is already done. Most security practitioners know this is a gap in their program. Most have not had a realistic path to closing it."},{"type":"heading","text":"Closing the Gap: Understanding Intent at Scale"},{"type":"paragraph","text":"Addressing insider risk effectively requires a shift in the underlying model. Rather than asking what happened, the question is whether what happened makes sense for this specific user, at this time, in this organizational context, and what the right response is when it does not."},{"type":"paragraph","text":"That question requires three capabilities working together. First, telemetry is collected at the endpoint, where work actually happens: not just file events and process executions, but the full behavioral context surrounding each action, including which applications were active, which accounts were in use, and the sequence of events that preceded and followed."},{"type":"paragraph","text":"Second, a behavioral baseline built around the individual, not just statistical peer averages, grounded in a real understanding of role, routine, and intent. Third, the ability to reason across that information continuously, correlate signals in real time, and produce not just alerts but coherent accounts of what is actually occurring."},{"type":"paragraph","text":[{"href":"https://preview.d2oftr9oq6im4e.amplifyapp.com/blog/why-we-built-ent-rethinking-the-architecture-that-makes-prevention-possible","text":"Ent was built around this model"},{"text":". By understanding user intent at the endpoint, Ent can tell whether behavior, including agentic behavior, stays within the bounds of what a user is legitimately doing. Crucially, understanding intent also means Ent can tell the difference between someone acting maliciously and someone simply making a mistake, and respond proportionally to each."}]},{"type":"paragraph","text":"That distinction changes what a response can be. When the risk is genuine and hostile, Ent alerts the security team and preserves the visual and audit evidence needed for investigation. But when the risk is an honest mistake, the better response is not a t

56icket weeks later. It is guidance at the moment. Ent can step in at the point of action and show the user the right path rather than the convenient one: explaining why pasting that file into an unsanctioned tool is risky, offering the approved alternative, and turning a potential incident into a thirty-second lesson. The new employee learns the correct way to do something the first time they reach for the wrong one. The engineer under a deadline is redirected before the credentials leave the building. Over time, the behavior of the whole workforce shifts toward the secure path because it is finally the one being taught, exactly when it matters."},{"type":"paragraph","text":[{"text":"This is the part of insider risk that detection alone has never addressed. According to industry research, the human element is the root cause in up to"},{"href":"https://www.cisecurity.org/insights/blog/why-employee-cybersecurity-awareness-training-is-important","text":" 74% of data breaches"},{"text":", often stemming from compromised credentials, misuse, or falling for social engineering tactics. Catching a bad actor protects you once. Educating a good employee in the moment protects you every time after."}]},{"type":"heading","text":"What This Looks Like in Practice"},{"type":"paragraph","text":"The following examples are drawn from two anonymized customer investigations conducted by Ent at a Fortune 500 hospitality company."},{"type":"paragraph","text":"In the first case, a new employee connected a KVM switch on day one. The device itself raised no alarms, as they often have a legitimate business purpose. What followed did. Microsoft Teams audio was routed away from local speakers and through the KVM device. Team messages contained credential transfers. File access patterns shifted in ways inconsistent with the employee's assigned role. Taken together, those signals revealed that system control was being handed to an external party. The investigation concluded in five days, resulting in termination. No other tool in the organization's security stack, including its EDR and UEBA platforms, had surfaced anything."},{"type":"paragraph","text":"In the second case, Ent detected employees granting extended remote access sessions using legitimate tools such as Zoom and AnyDesk. Sessions ran for up to eight hours at a stretch. Subsequent activity traced external parties accessing sensitive Google Drive files. The pattern was consistent with over-employment: employees using outside contractors to perform their work while holding down multiple positions simultaneously. Ent identified the moment of handoff, traced the downstream access, and surfaced the full scope of what had occurred."},{"type":"paragraph","text":"In both cases, every individual signal was defensible in isolation. The combination told a different story. And in both cases, the same behavioral understanding that surfaced genuine abuse is what lets Ent leave the far larger population of honest employees alone, or better, guide them, rather than burying everyone in suspicion. That is the core capability that behavioral security at the endpoint enables: a complete, contextual account of what a user is actually doing, why it matters, and the right response."},{"type":"heading","text":"The Stakes Are Getting Higher"},{"type":"paragraph","text":"The challenge of insider risk is only growing. The same AI tools that make legitimate work more efficient also give threat actors better cover, more convincing personas, and faster operational tempo. They also give well-meaning employees more powerful ways to move data and take action quickly, which means more opportunities for an honest mistake to become a serious one. The attack surface defined by human behavior at the endpoint is expanding, and the ability to distinguish malicious activity from a mistake, and both from legitimate work, is becoming more important, not less."},{"type":"paragraph","text":"The organizations best positioned to manage this are not the ones generating the most alerts. They are the ones that understand their users, recognize when behavior changes, and know whether the right response is to intervene, investigate, or educate."},{"type":"paragraph","text":[{"text":"That is the problem Ent is built to solve. To learn more about how Ent approaches insider risk and workforce security, visit "},{"href":"https://ent.ai/","text":"ent.ai."}]},{"type":"paragraph","text":[{"text":"Follow us on "},{"href":"https://x.com/Ent_Security","text":"X"},{"text":" and "},{"href":"https://www.linkedin.com/company/ent-security/posts/?feedView=all","text":"LinkedIn"},{"text":". To talk to us and see our product in action, schedule a demo."}]}]},{"slug":"designing-security-for-the-age-of-orchestration","title":"Security Design for Generated Experiences","authors":[{"name":"Sunder Srinivasan","title":"Head of Experience at Ent"}

56],"image":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/u2872878144_Imagine_an_ultra_high_resolution_black_and_white__ffca45f1-3458-49c4-945b-532cf5b3cc59_3.png?width=1600","date":"2026-06-16","updated":"2026-06-26","readMinutes":5,"excerpt":"Sunder Srinivasan | Head of Experience at Ent","seoTitle":"Security Design for Generated Experiences","metaDescription":"Security must evolve for AI-driven experiences. Learn why orchestration, operational scope, and governance are reshaping enterprise security.","content":[{"type":"heading","text":"Why security must move beyond access control to govern execution itself"},{"type":"paragraph","text":"When our founders broke down the structural problems inside enterprise security, they arrived at one conclusion: the interaction model enterprise security relied on had shifted."},{"type":"paragraph","text":"Enterprise security systems were built around deterministic workflows, explicit navigation, and direct human execution. But generated experiences behave differently. Interfaces are becoming orchestration layers. The gap between intent and execution is compressing. Systems act on users' behalf rather than simply respond to them. Security largely is not participating in that shift."},{"type":"paragraph","text":"Most of the industry approaches security as infrastructure layered onto experience after the interaction patterns have already been designed. We believe that approach will fail inside generated experiences, where operational scope expands faster than traditional interaction patterns can expose it."},{"type":"paragraph","text":"That conclusion shaped how we built the company. It pushed us to invest deeply in design, interaction thinking, and behavioral systems rather than treating security primarily as policy and control infrastructure. This is the first of three posts exploring the foundational thinking behind that approach."},{"type":"paragraph","text":"A generated experience is software assembled in the moment from what a person asks for. The user expresses intent, and the experience is composed in response. Beneath it runs the underlying agentic system: the orchestration and execution that fulfills that intent, retrieving data, reasoning across tools, and acting in ways the user never sees step by step. The experience is the shift people feel. The system underneath is where the work, and the operational risk, lives."},{"type":"paragraph","text":"Two terms carry the argument from here. Operational scope is the context and access a system is given to act on a request: the data it can read, the tools it can call, the systems it can reach. Operational consequence is what results when it acts across that scope. In hand-operated software, a person sets scope as they go, each file opened, each step traversed, and consequence stays roughly in view because they built up to it. In a generated experience, the system underneath sets scope on the user's behalf, and the consequence can land before the user senses how far the system reached."},{"type":"paragraph","text":"Enterprise security assumes users understand operational consequences because they perform each step by hand."},{"type":"paragraph","text":"Permissions constrain movement through known paths. Authentication appears before access. Governance attaches itself to stable control points because the systems underneath them behave predictably. Enterprise workflows expose boundaries gradually through navigation itself."},{"type":"paragraph","text":"Generated experiences weaken that visibility. The shift is not primarily about chat interfaces or automation. It is a deeper change in how interaction behaves once interfaces become orchestration layers."},{"type":"paragraph","text":"For example, a customer recently shared this prompt:"},{"type":"quote","text":"\\"I want to negotiate my salary with my boss. What should I expect for my level? How should I approach this?\\""},{"type":"paragraph","text":"The interaction felt small. The operational consequence was not. The system responded by retrieving compensation data from a copied organizational file with broader access than intended, exposing salary information well beyond the user's expected scope."},{"type":"paragraph","text":"Generated experiences can expand scope before users fully perceive it."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.

56net/hubfs/243241691/image%20(3).png?width=1600","alt":"image (3)","caption":"Figure 1: Scope Builds Through Navigation, Expands Through Orchestration"},{"type":"paragraph","text":"This is what we mean when we say productivity itself is becoming the attack surface."},{"type":"paragraph","text":"In navigation-based systems, the attack surface is the artifacts. Files, endpoints, accounts, network paths. Security wraps itself around those artifacts because users have to traverse them to do anything."},{"type":"paragraph","text":"In generated experiences, a new surface opens in the act of working itself. A single prompt can trigger retrieval across multiple systems, reasoning over data the user has never seen, and action taken in their name. That gap, between what a user asks for and what the system does to deliver it, compresses to almost nothing. Operational scope expands faster than interfaces can expose it."},{"type":"paragraph","text":"Interruption alone no longer communicates consequence effectively. Excessive friction breaks orchestration flow, but invisible governance creates a different risk: users lose the ability to understand what systems are doing for them as execution becomes increasingly abstracted."},{"type":"heading","text":"Generated experiences force security to govern execution"},{"type":"paragraph","text":"Most conversations around AI governance remain incomplete. They focus on capability, safety, or policy while treating interaction design as secondary infrastructure. The challenge is not simply preventing misuse. It is designing environments where the actions taken on a user's behalf stay visible as the systems underneath become more autonomous."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/image%20(4).png?width=1600","alt":"image (4)","caption":"Figure 2. Compression of Intent and Execution"},{"type":"paragraph","text":"Security has struggled to live naturally inside the enterprise experience."},{"type":"paragraph","text":"Most security systems exist as overlays attached to workflows rather than properties embedded within them. Perimeter security surrounds networks. Endpoint security surrounds devices. Identity systems are gateways users pass through before work begins."},{"type":"paragraph","text":"Security's design philosophy has long been to stay out of the way. Even the most successful security experiences largely succeed by reducing disruption. SSO reduced  repeated authentication. Biometric login removed procedural friction. Adaptive MFA applied interruption more selectively. Even with simplification, the pattern remains the same. Governance appears as something users have to get through."},{"type":"paragraph","text":"Generated experiences create a rare opportunity to rethink the relationship between security and the people moving through it, before new interaction patterns harden. Right now, people are actively learning how to work with systems that retrieve context, reason across tools, and act for them. The interaction patterns forming around those systems will settle quickly."},{"type":"paragraph","text":"The same risk exists now. If orchestration becomes the dominant interaction model while governance remains detached infrastructure, organizations will recreate the same adversarial patterns around systems that are far more dynamic and far less visible."},{"type":"paragraph","text":"The opportunity is not to make security hidden or invisible. It is to design systems where operational consequence remains tangible even as execution becomes increasingly abstracted. Governance needs to understand intent in order to be effective. That requires governance to behave less like interruption and more like what we will come to call environmental signaling. Systems will need ways to signal when their reach is changing, adjust what they do on a user's behalf to fit the situation, and help users understand the actions they no longer perform by hand."},{"type":"paragraph","text":"These interaction patterns are being defined right now. The organizations shaping them are also shaping how people work alongside systems acting for them."},{"type":"paragraph","text":[{"text":"To learn more about Ent, our vision for security in generated experiences, and the ideas 

56shaping our work, visit "},{"href":"https://ent.ai/","text":"ent.ai"},{"text":" and follow us on "},{"href":"https://x.com/Ent_Security","text":"X"},{"text":" and "},{"href":"https://www.linkedin.com/company/ent-security/posts/?feedView=all","text":"LinkedIn"},{"text":"."}]}]},{"slug":"why-security-needs-to-stop-reading-logs-and-start-watching-the-world","title":"Why Security Needs to Stop Reading Logs and Start Watching the World","authors":[{"name":"Brandon Dixon","title":"co-founder and CTO at Ent"}],"image":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/u2872878144_Imagine_a_black_and_white_image_composed_of_the_mos_1272a0f3-f114-4df8-8089-d76a326f4006.png?width=1600","date":"2026-06-16","updated":"2026-06-26","readMinutes":9,"excerpt":"Brandon Dixon | co-founder and CTO at Ent","seoTitle":"Why Security Needs to Stop Reading Logs and Start Watching the World","metaDescription":"What autonomous driving can teach cybersecurity: why security must move beyond logs and alerts to understand context, intent, and risk today.","content":[{"type":"paragraph","text":[{"text":"Before autonomous vehicles could drive, they had to learn to see and to understand. A stop sign in the US is just a red octagon with a white outline, but it’s also a social contract where we all agree to behave a certain way. A car drifting toward your lane is not just a position change; it’s also a signal of intent to keep coming. The breakthroughs that made self-driving cars possible were not about faster processors or better cameras. They were about building a world model: a representation of the environment that could answer not just "},{"italic":true,"text":"what’s happening?"},{"text":" but "},{"italic":true,"text":"what’s about to happen next? "},{"text":"and "},{"italic":true,"text":"what’s my best course of action?"}]},{"type":"paragraph","text":"Security is at the same inflection point today."},{"type":"heading","text":"A Short History of Seeing"},{"type":"paragraph","text":"The first autonomous vehicles operated on a relatively simple set of rules. If you see a red light, stop. If you see an obstacle, brake. These systems worked well in controlled conditions and failed everywhere else because the real world is full of surprises and corner cases that don’t fit neatly into finite rules based on fixed inputs. Operating in the real world means dealing with a lot more context."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/undefined-Jun-16-2026-03-44-30-3755-AM.png?width=1600","alt":"","caption":"Figure 1: How autonomous vehicles see the world"},{"type":"paragraph","text":[{"text":"The "},{"href":"https://en.wikipedia.org/wiki/DARPA_Grand_Challenge_(2004)","text":"2004 DARPA Grand Challenge"},{"text":" was a humbling moment for autonomous driving. This generation of vehicles relied heavily on hand-tuned rules to decide what was drivable. The result was vehicles that either crawled because every shadow looked like an axel-breaking crevice, or barreled into actual obstacles because the thresholds were too loose. Of 15 vehicles that participated in the final race, none completed more than 5% of the 150-mile course before crashing out due to errors and mechanical failures."}]},{"type":"paragraph","text":[{"text":"One year later, "},{"href":"https://en.wikipedia.org/wiki/DARPA_Grand_Challenge_(2005)","text":"5 out of 23 completed the course."},{"text":" The difference was not horsepower or hardware; It was perception and understanding. Teams fused telemetry from different types of sensors together to build a more complete picture of the world around them. They also applied machine learning based on observing real human driving behaviors, resulting in systems that could reason about the environment rather than just follow a static flow chart."}]},{"type":"paragraph","text":"By the 2010s, deep learning changed the game entirely. Cameras, radar, and lidar merged into a single coherent picture of the world, which was overlaid with high-definition maps. With that high-res model came the ability to predict and plan. The system no longer asked \\"

56is there an obstacle in front of me?\\" It asked \\"is that pedestrian about to step into my path?\\" and “what course corrections do I need to make so I don’t hit him or anything else around me?”"},{"type":"paragraph","text":"This shift from detection to prediction is what separated early autonomy experiments from something you can actually trust with your life. Cybersecurity is on a parallel journey, it’s just running about twenty years behind."},{"type":"heading","text":"The Security Equivalent of Rules-Based Driving"},{"type":"paragraph","text":"The first generation of security was perimeter-based. We built a wall to keep bad stuff out and assume anything inside is safe. That assumption broke down the moment organizations started poking holes in the wall for business traffic to pass through, and allowed users to make their own decisions about bringing executable files and untrusted content across that moat."},{"type":"paragraph","text":"So we built more rules, this time in the form of signature-based detection. Matching known bad patterns and blocking them worked reasonably well until attackers learned to morph their payloads on the fly."},{"type":"paragraph","text":"Next came SIEM and log correlation, which centralized security data, runs yet more rules against it after the fact to generate alerts, and lets analysts piece together what happened. It was a powerful step in the right direction, but in practice it created analyst overload and still answered questions about the past, not the present."},{"type":"paragraph","text":"EDR improved things by making the endpoint the primary source of truth and collecting broader and deeper telemetry. XDR went a step further uniting the EDR data with additional telemetry from network, cloud, and identity sources. We got better telemetry and faster detection, but still fundamentally reactive and rules-intensive. Analysts are still triaging and investigating alerts triggered by rules and reconstructing incidents from logs, almost always a step behind their adversaries."},{"type":"paragraph","text":"Attackers are well-versed in side-stepping this modern detection and response infrastructure. The modern attacker isn’t typically using novel malware. They’re using legitimate tools that blend in with day-to-day activity: PowerShell, remote desktop, browsers, SaaS applications, and collaboration platforms. The malicious activity looks just like work. The signals they generate closely resemble what any normal employee produces on a normal day. Like an axel-breaking boulder that looks just like a shadow, you can’t catch this by reading the same logs faster. You need better telemetry and intelligence to understand it in order to act in time to avoid critical damage"},{"type":"heading","text":"The Problem Is Not Volume. It’s Visibility."},{"type":"paragraph","text":"Here is what a traditional investigation looks like:"},{"type":"list","ordered":false,"items":["Your XDR fires off a series of alerts.","Tier 1 analysts triage the alerts and determine something seems amiss and worth investigating further.","Tier 2 analysts query SIEM logs and see a suspicious download occurred, but don’t have enough information to declare an incident or act, so they pull in additional help.","The forensics team finds suspiciously obfuscated scripts in a downloads folder, traces it to a URL accessed three days ago via cross-referenced proxy logs, and finally figures out what’s happened.","They remediate the immediate threat, and then begin the laborious process of hunting for similar signs of intrusion elsewhere before closing the incident.","Finally, updated threat intelligence is shared with the detection engineering team so they can update detection rules to do better next time. Hopefully.","The whole process takes days, and at the end of it you still don’t know exactly what the user saw, why they did what they did, or how to coach them to prevent similar incidents in the future."]},{"type":"paragraph","text":"Now here is what modern security can look like."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.

56net/hubfs/243241691/undefined-Jun-16-2026-03-44-29-1778-AM.png?width=1600","alt":"","caption":"Figure 2: The Organizational Work Model"},{"type":"paragraph","text":"For example, imagine you have a screenshot of the user in Discord. They’re chatting with a new contact who convinces them to download and execute a file. You’re looking at a visual record of the conversation, the download, the execution, with behavioral context layered on top. You can see the source of the scam so you can put in place better countermeasures. You can see the additional URLs for more effective threat hunting. You can understand exactly what happened without unreliable user interviews. Most importantly, you can create an intervention so that if this pattern appears again, the system responds before the file is ever opened."},{"type":"paragraph","text":"This isn’t just an incremental improvement in tactics for security teams; it’s an entire new model for defenders, and it’s what we’re building at Ent."},{"type":"heading","text":"What the User Sees Is the Signal"},{"type":"paragraph","text":"The core insight that drives everything we’re building at Ent is simple: the user sees things that security tools don’t, and that context is key to making better, faster decisions."},{"type":"paragraph","text":"When a user copies a file from one application and opens it into another, traditional security sees a process launch event, and maybe a file write. What it doesn’t see is that the user has three applications open. One of them is a project they are actively working on, they are about to send a document containing PII to an external contact, and based on their history and role, this is either completely normal or a potential compliance violation."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/undefined-Jun-16-2026-03-44-29-6808-AM.png?width=1600","alt":"","caption":"Figure 3: Context Reveals Intent"},{"type":"paragraph","text":"Those details needed to unravel the user’s intent are all there, just not visible to a typical security stack. They require a different kind of seeing."},{"type":"paragraph","text":"Ent combines real-time endpoint telemetry that reflects exactly what the user sees and does with multimodal AI to build an Organizational Work Model, a real-time understanding of how people actually operate within the scope of their job. Ent’s model reveals not just what actions they take, but what those actions mean given who they are, what team they are on, what they normally do, and what they are looking at right now."},{"type":"paragraph","text":"This is the security equivalent of the world model developed for autonomous vehicles. Instead of asking \\"what happened?\\", we ask \\"what is happening, why, and what should we do about it?\\""},{"type":"heading","text":"Seeing Is Not Enough. You Have to Act."},{"type":"paragraph","text":"Returning to our autonomous vehicle analogy, today’s autonomous vehicles are not safer just because they have better sensors. They are safer because they’ve got better brains that build perception loops that lead to action. The system sees everything around it, understands it in context, anticipates what comes next, and responds proportionally. It performs a soft course correction for a pothole a half block away, but performs emergency braking for an imminent collision. The response fits the risk."},{"type":"paragraph","text":"Ent is creating this real-time feedback loop for cybersecurity."},{"type":"paragraph","text":"When Ent identifies a risky action, it fires an alert, but also intervenes at the moment of user decision. That can be a plain-language nudge for the user that explains the risk and offers a safer path. It can involve automatically masking sensitive fields before a spreadsheet is submitted to an AI tool for analysis. It could be a hard block and immediate deletion of a malicious file. Or it can be a silent, context-rich alert to the security team so investigators have everything they need without starting from scratch."},{"type":"paragraph","text":"The intervention happens at the right moment, enriched with all the right context, with the right level of force. A security awareness training session six months after an incident changes almost nothing. An explanation that appears at the exact moment someone is about to make a mistake changes behavior when it matters."},{"type":"heading","text":"Fleet Learning and the Compounding Advantage"},{"type":"paragraph","text":"One more thing autonomous vehicles figured out that security largely has not: fleet learning. When one self-driving car encounters a new edge case, that data propagates across the entire system. Every vehicle has the opportunity to benefit from a new corner case that one vehicle learned. The safety of the fleet compounds over time at a speed no individual human driver can match."},{"type":"paragraph","text":"Ent's Organizational Work Model works the same way. The system continuously learns what is normal for each user, each role, each w

56orkflow. When behavior shifts, it understands the context: is this a mistake, a gray area, or something genuinely malicious? And as the model learns, every detection gets sharper, every intervention gets more precise, and every investigation gets faster. This is the structural advantage that reactive tools can’t close by throwing more data and people at the problem."},{"type":"heading","text":"The Next Generation Is Already Here"},{"type":"paragraph","text":"We built Ent because we believe cybersecurity has to be redesigned around a work model, not just a threat model. The threat model tells you what bad looks like. The work model tells you when something is happening that’s outside of what’s normal, and gives you the opportunity to do something about it at decision time. The self-driving era of security is here. The question is whether your stack is built to drive in it."},{"type":"paragraph","text":[{"text":"To learn more about Ent and our vision for securing human and AI-driven work, visit "},{"href":"https://ent.ai/","text":"ent.ai."}]},{"type":"paragraph","text":[{"italic":true,"text":"Brandon Dixon is CTO and co-founder of Ent. Before Ent, Brandon led threat intelligence and security product strategy at Microsoft Security."}]},{"type":"paragraph","text":[{"text":"Follow us on "},{"href":"https://x.com/Ent_Security","text":"X"},{"text":" and "},{"href":"https://www.linkedin.com/company/ent-security/posts/?feedView=all","text":"LinkedIn"},{"text":"."}]},{"type":"paragraph","text":"To see our product in action, schedule a demo."}]},{"slug":"why-we-built-ent-rethinking-the-architecture-that-makes-prevention-possible","title":"Why We Built Ent: Rethinking the Architecture that Makes Prevention Possible","authors":[{"name":"Elias (Lou) Manousos","title":"CEO & Co-founder at Ent"},{"name":"Brandon Dixon","title":"co-founder & CTO at Ent"}],"image":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/Blog%20post%20logo.png?width=1600","date":"2026-06-16","updated":"2026-06-26","readMinutes":6,"excerpt":"Elias (Lou) Manousos|CEO & Co-founder at Ent , Brandon Dixon|co-founder & CTO at Ent","seoTitle":"Why We Built Ent: Rethinking the Architecture that Makes Prevention Possible","metaDescription":"Ent emerges from stealth with $100M to bring AI-powered prevention back to cybersecurity through intent-aware workspace security.","content":[{"type":"paragraph","text":"$100 million seed round backs the industry’s first intent-aware Workspace Security platform."},{"type":"paragraph","text":"For most of the last decade, security vendors gave up on prevention. The industry concluded that breaches were inevitable and poured its energy into detection and response. Logs were collected across every kind of telemetry, shipped to the cloud, and analyzed to understand what happened after the fact. EDR and SIEM became the center of gravity, and they became very good at triaging incidents and rather slow at stopping them, they just had to be somewhat faster than the human advisory at the other end."},{"type":"paragraph","text":"AI has changed the equation, and that tradeoff no longer holds at the speed work now moves. Organizations are moving faster than ever. Employees work across more applications, while AI assistants and agents are becoming part of everyday workflows. As work changes, so does the risk."},{"type":"paragraph","text":"AI has collapsed the time between compromise and impact. An attack that once unfolded over days now completes in minutes, faster than a human can respond. It starts with a single action: a copy, a paste, a prompt, a click, or a handoff of remote control to someone outside the business. By the time EDR fires anything, the damage is already underway. Every CISO we talk to feels this today. The time-to-damage window is closing faster than the time-to-respond window their existing tooling can deliver."},{"type":"paragraph","text":"The question is no longer how quickly you can investigate. It is whether you can prevent the incident from happening in the first place."},{"type":"paragraph","text":"We are building a new security platform that returns prevention to its rightful place, as security tools originally intended to, designed for where work actually happens."},{"type":"heading","text":"The news"},{"type":"paragraph","text":[{"text":"Today, we are excited to share a milestone. "},{"href":"https://ent.ai/","text":"Ent"},{"text":" is emerging from stealth with $100 million in funding led by "},{"href":"https://www.decibel.vc/","text":"Decibel"},{"text":", with participation from "},{"href":"https://sequoiacap.com/","text":"Sequoia"},{"text":","},{"href":"https://crosspointcapital.com/","text":" Crosspoint Capital Partners"},{"text":","},{"href":"https://www.craftventures.com/","text":" Craft Ventures"},{"text":", "},{"href":"https://shieldcap.com/","text":"Shield Capital"},{"text":","},{"href":"https://www.felicis.com/","text":" Felicis"},{"text":", and"},{"href":"https://www.iqt.org/","text":" In-Q-Tel"},{"text":" (IQT)l. We are grateful for it, and it reflects the scale of the opportunity ahead of us."}]},{"type":"quote","text":[{"text":"“"},{"italic":true,"text":"We have entered a new era defined by AI-powered attacks, one that demands a return to prevention and resilience. The level of inference required to stop threats before they materialize must now live directly on the endpoint. Ent is leading this fundamental shift in endpoint protection."},{"text":"” - "},{"italic":true,"text":"said Greg Clark, Co-Founder and Managing Partner, Crosspoint Capital Partners."}]},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.

56net/hubfs/243241691/undefined-Jun-16-2026-02-46-26-0560-AM.png?width=1600","alt":"","caption":"Figure 1: ENT Team Photo"},{"type":"heading","text":"Why prevention is possible again"},{"type":"paragraph","text":"Prevention failed for a practical reason. To stop something before it happens, you have to see and understand it in real time, at the moment of decision. With traditional cloud-based tools that was not possible. The processing power lived in the cloud, and a round trip was needed from the endpoint to instrument the action."},{"type":"paragraph","text":"With AI, this has changed. We run small AI models locally on the endpoint, moving reasoning and action to the edge without the round-trip latency. A decision can be made in sub-seconds, before the incident occurs. For the first time, a system can observe what is happening, understand with full context whether it should continue, and intervene before the moment passes."},{"type":"paragraph","text":"This is the shift left that security has wanted for years: prevention close to where work happens, with an architecture you can actually deploy."},{"type":"heading","text":"Workspace security is the new control plane"},{"type":"paragraph","text":"Modern work does not happen at the layers where EDR and SIEM are watching. It is spread across the apps, browsers, collaboration tools, and AI assistants a person moves through in a day, alongside the AI agents acting on their behalf."},{"type":"paragraph","text":"That is where risk now lives, looking like legitimate work, and that is where the traditional stack is blind. EDR can tell you a process is running. SIEM can collect information around it. Neither can tell you that a user just handed control of their machine via RMM (Remote monitoring and management) to someone outside the organization, or pasted sensitive data into an unsanctioned AI tool, or the intent behind either action. The instrumentation sits at the wrong layer, arrives too late, and lacks the context of the human and the agent activities."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/undefined-Jun-16-2026-02-46-25-1138-AM.png?width=1600","alt":"","caption":"Figure 2: On-Device Telemetry and Reasoning"},{"type":"paragraph","text":"It requires a new layer: a control plane at the endpoint, where behavioral telemetry is collected, intent is inferred to tell normal work from risky action, and interventions happen at the moment of decision."},{"type":"paragraph","text":"That's why we're excited to introduce Ent and share our vision for the future of workspace security. Organizations need a better way to secure human and AI-driven work."},{"type":"paragraph","text":"Our mission is simple: protect work as it happens."},{"type":"heading","text":"Foundation starts with a complete record of work"},{"type":"paragraph","text":"Here is the part we strongly believe in."},{"type":"paragraph","text":"Securing modern work starts with a complete, faithful record of it: application use, browser, chat, AI use, workflows, runtime execution, and data movement. Today that record lives in fragmented tools, never in one place, which is why security teams spend their days reconstructing events from pieces scattered across a dozen systems."},{"type":"paragraph","text":"Ent creates that record at every endpoint, a comprehensive log of what is actually happening across the business. Intent is derived from the same telemetry, adding the why behind a human or agent action to the what. With behavioral baselining, Ent learns what is normal for each role and each workflow. Because the record is complete and lives at the right layer, it becomes the foundation for action. We intervene in the moment to prevent threats, misuse, and mistakes."},{"type":"paragraph","text":"With this new layer in place, security teams operate at a different speed. What used to take hours or days takes minutes. And many incidents simply never happen, because the platform steps in to take action before they can."},{"type":"heading","text":"Built Alongside Our Customers"},{"type":"paragraph","text":"The challenges we are describing are not future problems. They are what security team

56s are managing right now: embracing AI while keeping control of sensitive data, navigating insider risk, responding to social engineering that looks exactly like legitimate work, and investigating incidents that span applications and workflows. All this while being asked to enable innovation and move faster than ever before."},{"type":"paragraph","text":"We built Ent alongside customers living these realities every day. Their feedback and insights have shaped both the platform and our vision. Organizations use Ent to detect insider risk, govern AI usage, prevent data loss, stop last-mile threats, and accelerate investigations with complete behavioral context. More than any single feature, what they get is clarity in environments where the old approach left too many questions open."},{"type":"paragraph","text":"As one customer told us:"},{"type":"quote","text":[{"italic":true,"text":"\\"Ent is the first tool where I felt like an expert on day one. Reading exactly what happened took the guesswork out of my job and let me scale my team.\\""},{"text":" "},{"italic":true,"text":"— Insider Threat Lead, Public Financial Institution"}]},{"type":"paragraph","text":"We are proud to support Global 2000 organizations across hospitality, financial services, and defense as they navigate human and AI-driven work. Their partnership continues to shape how we build and innovate."},{"type":"heading","text":"What comes next"},{"type":"paragraph","text":"The way work happens will continue to evolve. So will the challenges facing security teams."},{"type":"paragraph","text":"We believe the future of workspace security will be defined by the return to prevention, because for the first time the architecture exists to make it real: AI-powered intelligence at the edge, a complete record of work, and the context to understand intent and act before risk becomes an incident. While detection and response will continue to exist, modern workplace security needs a new approach to bring back prevention."},{"type":"paragraph","text":[{"text":"We built Ent for what comes next.To learn more about Ent and our vision for securing human and AI-driven work, visit "},{"href":"https://ent.ai/","text":"ent.ai."}]},{"type":"paragraph","text":[{"text":"Follow us on "},{"href":"https://x.com/Ent_Security","text":"X"},{"text":" and "},{"href":"https://www.linkedin.com/company/ent-security/posts/?feedView=all","text":"LinkedIn"},{"text":". To talk to us and see our product in action, schedule a "},{"href":"http://ent.ai/demo","text":"demo"},{"text":"."}]}]},{"slug":"the-future-of-security-lives-where-work-happens","title":"The Future of Security Lives Where Work Happens","authors":[{"name":"Janani Nagarajan","title":"VP of Product Marketing at Ent"}],"image":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/u2872878144_httpss.mj.runTRGHchD_qpI_You_are_an_illustrator_w_bf6a5096-1173-4f6b-b7f3-5ce48f522dd2_3.png?width=1600","date":"2026-06-16","updated":"2026-06-26","readMinutes":6,"excerpt":"Janani Nagarajan | VP of Product Marketing at Ent","seoTitle":"The Future of Security Lives Where Work Happens","metaDescription":"Ent CTO Brandon Dixon shares why the future of cybersecurity is built around people, AI, and intent-aware protection.","content":[{"type":"paragraph","text":"Why the next era of cybersecurity will be built for people, not just experts."},{"type":"paragraph","text":"A conversation with Brandon Dixon, CTO and co-founder of Ent"},{"type":"paragraph","text":[{"italic":true,"text":"For decades, cybersecurity has been built around experts who investigate alerts and respond after risk has already emerged. "},{"href":"https://www.linkedin.com/in/brandonsdixon/details/experience/","italic":true,"text":"Brandon Dixon"},{"italic":true,"text":", co-founder and CTO of Ent, has spent his career helping organizations make sense of increasingly complex security signals. He co-founded PassiveTotal, which was later acquired by RiskIQ, and served as a Security AI Strategist at Microsoft, where he launched Microsoft Security Copilot. Today Brandon believes AI creates an opportunity to fundamentally rethink who cybersecurity is built for, by bringing expertise to the people doing the work, reading intent in the moment, and protecting work before risk becomes an incident."}]},{"type":"paragraph","text":"For most of cybersecurity's history, security has been built around experts."},{"type":"paragraph","text":"Organizations invested in security team

56s, specialized tools, and increasingly sophisticated systems designed to help trained professionals investigate threats and respond to incidents. As attacks became more complex, the industry responded by creating more visibility, more telemetry, and more data for experts to analyze."},{"type":"paragraph","text":"That approach shaped much of Brandon's career."},{"type":"paragraph","text":[{"italic":true,"text":"\\"So much of my career has been about building security systems and tools for the expert with the idea that if we can give them the advantage, then we can stop the adversary from being successful and better protect organizations.\\""}]},{"type":"paragraph","text":"For years, Brandon focused on helping security professionals better defend their organizations through improved visibility, intelligence, and security systems."},{"type":"paragraph","text":"But as new technologies emerged, Brandon began to see an opportunity to rethink who security was built for."},{"type":"heading","text":"Why now: the technology finally makes it possible"},{"type":"paragraph","text":"At Microsoft, Brandon had an early view into how fast generative AI was evolving and what these new models were capable of unlocking. As he watched the technology evolve, he became increasingly convinced that it would fundamentally change security. Not just by giving experts another tool, but by reaching everyone else."},{"type":"paragraph","text":[{"italic":true,"text":"\\"What excited me most was the fact that we could democratize knowledge and the capability of security by putting it in the hands of not an expert user, but users who are just trying to do the right thing in their job.\\""}]},{"type":"paragraph","text":"For years, the idea of bringing security reasoning directly to where people worked was difficult to achieve. While the vision was compelling, the technology was not yet ready to operate where decisions were being made."},{"type":"paragraph","text":"That began to change as AI models matured."},{"type":"paragraph","text":"AI could understand intent, bringing context, reasoning, and expertise closer to the moment decisions were being made. For the first time, people could understand not just what they were doing, but whether those actions aligned with the goals of the organization."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/undefined-Jun-16-2026-12-33-26-8836-AM.png?width=1600","alt":"undefined-Jun-16-2026-12-33-26-8836-AM","caption":"Figure 1: Ent Founders Brandon Dixon and Elias Manousos"},{"type":"paragraph","text":"Brandon and Lou shared a conviction about what would follow."},{"type":"paragraph","text":[{"italic":true,"text":"\\"The reason why we started the company was that eventually I knew that these models would become cheaper, faster, more efficient, and that they would be made available to operate at the edge where people actually worked.\\""}]},{"type":"paragraph","text":"Once reasoning could run locally, security expertise no longer had to stay confined to the SOC. It could move into the flow of work itself. Prevention at the moment risk occurs becomes a possibility."},{"type":"heading","text":"How it works: reading intent, not just activity"},{"type":"paragraph","text":"The hard part was not about detecting that something happened. It was understanding why. The same action can be routine or dangerous depending on who takes it, what is normal for them, and what they are trying to do."},{"type":"paragraph","text":"Brandon's team took a lesson from self-driving cars. Early systems tried to hard-code a rule for every situation and broke the moment the road changed. The breakthrough came from building a world model that understood the environment and could predict what would happen next. Ent does the same for the enterprise. It builds an organizational work model, a living understanding of how people and agents actually operate, so it can tell normal work from real risk instead of relying on brittle rules. The platform reads behavior across every application on the endpoint, infers intent with that context, and acts in the moment."},{"type":"paragraph","text":"The everyday case makes it concrete. In a Fortune 500 deployment, an HR employee activated an unsanctioned AI assistant inside a sanctioned communication tool and nearly pasted patient records into it. No static rule could have caught that. A behavioral layer that understands intent did, and stepped in before the data left."},{"type":"heading","text":"Security that works alongside you"},{"type":"paragraph","text":"For Brandon, the promise of AI was not just a more efficient SOC. It is about enabling non-expert

56s to become better security investigators and responders and educating users about security in real-time."},{"type":"paragraph","text":[{"italic":true,"text":"\\"I didn't want to build just another expert tool. I wanted to be in a position where I was helping the average person be better at security, ideally without them ever having to know about it. But in the event that they did have to know about it, educating them at the same time. And that's why we founded Ent.\\""}]},{"type":"paragraph","text":"His vision is a workplace where people focus on their jobs and security runs quietly underneath, present when it is needed and invisible when it is not. Whether someone is collaborating with colleagues, using applications, or working with AI tools, protection should be available in the moment and unobtrusive the rest of the time."},{"type":"paragraph","text":[{"italic":true,"text":"\\"What excites me most is the ability to have security operate behind the scenes while people do their jobs, where they never have to become an expert at all. It's as if an expert is running locally on their system.\\""}]},{"type":"paragraph","text":"That is the shift Brandon is working on: not asking people to become security specialists, but putting an expert in the flow of their work."},{"type":"heading","text":"The road ahead"},{"type":"paragraph","text":"The opportunity AI creates goes well beyond improving today's tools. For Brandon, it is a chance to change how people experience security entirely."},{"type":"paragraph","text":"As AI keeps evolving, security can become more deeply woven into the work itself, operating in the background while people focus on their jobs and reading intent in real time across both users and agents."},{"type":"paragraph","text":[{"italic":true,"text":"\\"The overarching vision that I have is that one day, regardless of experience, without even thinking about it, you're capable of doing your job or doing things that you enjoy, being productive on your computer and your system, and you don't have to worry about security because something like Ent is running on that system and protecting you, bringing that reasoning directly to where you work.\\""}]},{"type":"paragraph","text":"Throughout his career, Brandon built technologies designed to help experts defend organizations against adversaries. What excites him most now is the opportunity to bring that same knowledge and reasoning directly to the people doing the work."},{"type":"paragraph","text":"The future of cybersecurity is not about creating more expert tools. It is about making expertise available wherever work happens. It is about bringing security reasoning closer to users and AI systems, understanding intent in real time, and helping organizations protect work before risk becomes an incident."},{"type":"paragraph","text":[{"text":"Watch the "},{"href":"https://vimeo.com/1201604322/2cbb87ae0b?share=copy&fl=sv&fe=ci","text":"full interview with Brandon Dixon"},{"text":" to hear more about the future of cybersecurity, why security expertise should live where work happens, and the vision behind Ent."}]},{"type":"paragraph","text":[{"text":"To learn more about Ent and our vision for securing human and AI-driven work, visit "},{"href":"https://ent.ai/","text":"ent.ai."}]},{"type":"paragraph","text":[{"text":"Follow us on "},{"href":"https://x.com/Ent_Security","text":"X"},{"text":" and "},{"href":"https://www.linkedin.com/company/ent-security/posts/?feedView=all","text":"LinkedIn"},{"text":". To talk to us and see our product in action, schedule a demo."}]}]},{"slug":"the-brand-had-to-mean-something","title":"The Brand Had to Mean Something","authors":[{"name":"Matt Weitkamp","title":"Creative Director at Ent"}],"image":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/u2872878144_Imagine_a_black_and_white_image_composed_of_the_mos_ad56274c-cbac-47ef-9494-7c6e00051736.png?width=1600","date":"2026-06-16","updated":"2026-06-26","readMinutes":7,"excerpt":"Matt Weitkamp|Creative Director at Ent","seoTitle":"The Brand Had to Mean Something","metaDescription":"See how Ent’s identity was built from first principles to represent protection and intent-aware security.","content":[{"type":"paragraph","text":"Most cybersecurity branding does one of two things: it signals that a company exists and is professional, or it attempts to stand out without saying anything at all. In either case, the goal is usually the same: to help people understand what a company does."},{"type":"paragraph","text":"We wanted our brand to express why we built Ent in the first place."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.

56net/hubfs/243241691/Blog%20post%20logo.png?width=1600","alt":"Blog post logo"},{"type":"paragraph","text":"At Ent, we apply a first-principles approach to everything we create: the product, the way we use AI, and the way we think about security itself. For us, the brand could not be separate from the product. It needed to be an expression of the same ideas. That belief shaped the process itself. We developed the brand alongside the product, not before it, and held the design process to the same standard as the engineering process: nothing ships unless we can defend why it exists."},{"type":"paragraph","text":"What follows is not a recap of how we got here. It's an account of the ideas behind the brand and the thinking that shaped them."},{"type":"heading","text":"A Symbol of Protection and Prosperity"},{"type":"paragraph","text":"The symbol began with a question: what meaning could we defend? Early concepts leaned into nature and were often interpreted as tribal. Later concepts were visually interesting but felt either too AI-generic or too abstract. None of them failed on craft. They failed in meaning. A symbol we could not explain was a symbol we did not want."},{"type":"paragraph","text":"What we needed was a symbol grounded in the product and the principles behind it."},{"type":"paragraph","text":[{"text":"The breakthrough came from "},{"href":"https://en.wikipedia.org/wiki/Runes","text":"runes"},{"text":". Unlike modern letters, runes were not simply characters used to spell words. Each carried its own meaning and represented an idea. That distinction resonated with us. We were not looking for a symbol that identified Ent. We were looking for a symbol that represented what Ent stands for."}]},{"type":"paragraph","text":[{"text":"Our symbol draws from two runes: "},{"href":"https://en.wikipedia.org/wiki/Algiz","text":"Algiz"},{"text":" for protection and "},{"href":"https://en.wikipedia.org/wiki/Fehu","text":"Fehu"},{"text":" for prosperity."}]},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/undefined-Jun-16-2026-12-46-24-6329-AM.png?width=1600","alt":"","caption":"Figure 1: The Ent Symbol"},{"type":"paragraph","text":"Protection was the easier half to define because it is at the core of what the product does. Most security tools react to actions after they occur. Ent is intent-aware. Understanding the context behind an action as it happens allows us to help organizations prevent risk before it becomes an incident."},{"type":"paragraph","text":"Prosperity took longer to land, but ultimately became the more important half of the story. For decades, security has often treated safety and restriction as inseparable. Lock it down. Gate it. Deny it. Prosperity represents a different approach. Security should protect people without preventing them from doing their best work."},{"type":"paragraph","text":"When security is working well, it becomes an enabler rather than an obstacle. It provides guidance when needed, surfaces risk when it matters, and allows people to work with confidence. That balance between protection and prosperity is the commitment our symbol represents."},{"type":"paragraph","text":"We arrived at the final symbol during the last week of our agency engagement, though the inspiration came earlier. A member of the founding team came across a photograph of a small rune carved into the frame of an office door. The image had sparked curiosity online, with people asking what it meant and why it had been placed there."},{"type":"paragraph","text":"What stayed with us was not just the symbol itself, but the question it inspired. \\"What does this mean?\\" is ultimately the same question our product is designed to answer. That moment led us to explore runes more deeply and ultimately helped shape the symbol we use today."},{"type":"heading","text":"Signal to Sigil: A Visual Language for What the Product Does"},{"type":"paragraph","text":"Once the symbol was established, we turned to the rest of the identity and applied the same test: what would each element need to mean to be defensible? That question produced the brand's visual language, which we call signal to sigil."},{"type":"paragraph","text":"Signal to sigil describes the transformation at the heart of the system: raw activity becomes something meaningful and legible."},{"type":"paragraph","text":"A modern organization generates millions of user actions, file accesses, and application calls. In most security tools, this arrives as a flat blur of logs and alerts, noise that another human is expected to sort through. The industry has come to accept this as visibility. It is not. It is the absence of visibility disguised as completeness."},{"type":"paragraph","text":"The visual language draws from two sources. The first is sigils, which began as pictorial signatures in ancient texts, personal symbols that carried meaning. To look at a sigil was to see intent made visible."},{"type":"paragraph","text":"The second is cymatics, which expresses the same idea through physics. Place sand on a thin metal plate, run a frequency through it, and the particles settle into quiet regions while leaving active areas empty. What first appears as scattered grains resolves into a geometric pattern. Change the frequency and the pattern reorganizes. Chaos is not chaos. It is a signal waiting for the right resonance."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.

56net/hubfs/243241691/cymatic.png?width=1600","alt":"cymatic","caption":"Figure 2: Frequency Based Cymatic Patterns"},{"type":"paragraph","text":"The synthesis came from another designer on our team. I had been collecting sigil references. They brought the cymatics. Once we put the two together, the language became obvious."},{"type":"paragraph","text":"A sigil holds meaning in a fixed symbol. Cymatics shows meaning taking shape in real time. Together, they describe what Ent is designed to do: reveal the pattern beneath what appears to be noise. What emerges is not another queue, but a behavioral signature of what is actually happening, legible at a glance."},{"type":"paragraph","text":"Treating the visual language as a system rather than a collection of assets is the only approach consistent with the product it represents."},{"type":"heading","text":"Adaptive Color"},{"type":"paragraph","text":"The standard approach to a product color system is familiar: pick a palette, check it for accessibility, verify it in light and dark mode, and ship. The palette remains the same in both modes. One mode is the original, and the other is its desaturated translation. One mode always loses."},{"type":"paragraph","text":"The alternative was biomimicry. The palette would shift between day and night the way a forest does. The idea emerged early, but it took the rest of the brand catching up before we could fully realize it."},{"type":"paragraph","text":"Our primary color is green, so the reference point became the forest. A forest does not desaturate at night. It transforms. Different organisms take over. The greens that are restrained at noon, dark foliage and moss on stone, give way after sundown to the bioluminescent greens of foxfire fungus, fireflies, and organisms that emit their own light when the sun is gone."},{"type":"paragraph","text":"In light mode, Ent is the forest at midday. A warm off-white background, the color of sunlight filtering through the canopy. Greens held in reserve. Calm. Visibility without anxiety."},{"type":"paragraph","text":"In dark mode, Ent is the same forest after sundown. The background drops to near black, and the greens that were once restrained begin to glow. The forest remains the same. Different organisms are doing the work."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/undefined-Jun-16-2026-03-13-48-7946-AM.png?width=1600","alt":"","caption":"Figure 3: The Ent Color System"},{"type":"paragraph","text":"This is biomimicry applied to a design system. Not borrowing nature's palette, but borrowing the way it transforms as conditions change. The light and dark palettes are not translations of one another. They are two states of the same living system. That is the only honest way to render a brand whose product also adapts in real time to what is in front of it."},{"type":"paragraph","text":"The symbol, the visual language, and the color system are not three separate design decisions. They are three expressions of a single belief: meaning is not decoration laid on top of a thing. Meaning is the thing."},{"type":"paragraph","text":"That belief appears differently in each part of the system."},{"type":"paragraph","text":"A symbol of protection and prosperity. A visual language that shows noise resolving into a signal. A color system that adapts without losing itself. Each element is a claim about what Ent is and what security can become when it stops being a tax on the work."},{"type":"paragraph","text":"The discipline that produced them is the same discipline we apply to the product. The brand carries the same commitment as the product: that what happens in your environment is understood, and that the people inside it are free to do their work."},{"type":"heading","text":"See the Product Behind the Brand"},{"type":"paragraph","text":"Most brands are designed to be recognized. We wanted ours to be understood."},{"type":"paragraph","text":"Everything described here began with the product. A symbol of protection and prosperity. A visual language that turns noise into signal. A design system that adapts without losing itself. These were not branding exercises. They emerged from the same principles that shaped the product and were made visible through design."},{"type":"paragraph","text":"The brand reflects the product it represents."},{"type":"paragraph","text":[{"text":"See the product behind the brand at "},{"href":"http://ent.ai","text":"ent.ai"},{"text":"."}]},{"type":"paragraph","text":[{"text":"Follow us on "},{"href":"https://x.com/Ent_Security","text":"X"},{"text":" and "},{"href":"https://www.linkedin.com/company/ent-security/posts/?feedView=all","text":"LinkedIn"},{"text":". To talk to us and see our product in action, schedule a demo."}]}]},{"slug":"designing-security-for-the-way-work-happens-today","title":"Designing Security for the Way Work Happens Today","authors":[{"name":"Janani Nagarajan","image":"https://app.hubspot.com/settings/avatar/d41d8cd98f00b204e9800998ecf8427e"}

56],"image":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/u2872878144_httpss.mj.runTRGHchD_qpI_You_are_an_illustrator_w_bf6a5096-1173-4f6b-b7f3-5ce48f522dd2_2.png?width=1600","date":"2026-06-16","updated":"2026-06-26","readMinutes":6,"excerpt":"Janani Nagarajan | VP of Product Marketing at Ent Preventing risk begins with understanding human and agent intent A conversation with Elias (Lou) Manousos, CEO and co-founder of Ent Existing…","seoTitle":"Designing Security for the Way Work Happens Today","metaDescription":"AI is changing work. Ent’s CEO explains why intent-aware security is essential for protecting humans and agents.","content":[{"type":"paragraph","text":[{"italic":true,"text":"Existing security tools are good at telling organizations what happened and being reactive. "},{"href":"https://www.linkedin.com/in/eliasmanousos/","italic":true,"text":"Elias Manousos"},{"italic":true,"text":", co-founder and CEO of Ent, believes the harder problem to solve is moving the industry back to prevention. He talks about going back to first principles where the key to preventing the risk before it becomes an incident lies in understanding intent behind the actions, be it human or agent. He shares the experiences that led to the founding of Ent, lessons from decades in cybersecurity, and the future of modern work. "}]},{"type":"paragraph","text":"For most of its history, security has been organized around a single question: what happened? Elias (Lou) Manousos believes the next evolution of security is understanding why it happened."},{"type":"paragraph","text":"For decades, cybersecurity has improved at detecting attacks, investigating incidents, and collecting evidence. Organizations have more telemetry and visibility than ever before. Yet security leaders face the same challenge: by the time risk is identified, the incident has already happened."},{"type":"paragraph","text":"Lou has spent much of his career helping organizations solve difficult security problems. Across threat intelligence, attack surface management, AI copilots, and enterprise security platforms, one theme has remained constant for Lou."},{"type":"paragraph","text":"The goal is not simply to understand what happened."},{"type":"paragraph","text":"The goal is to understand why it happened, and to prevent what happens next."},{"type":"paragraph","text":"That belief ultimately became the foundation for Ent, the intent-aware Workspace Security platform designed to help organizations understand risk and move from reactive detection to preventive security."},{"type":"heading","text":"When the technology finally caught up"},{"type":"paragraph","text":"The idea behind Ent started years before the company itself."},{"type":"paragraph","text":"While helping build Microsoft's first security copilot, Lou found himself returning to a problem cybersecurity has struggled with from the start: prevention."},{"type":"paragraph","text":"Security teams had become increasingly good at detecting attacks and investigating incidents after they occurred. But the question that stayed with him was whether AI could finally help stop threats before they happened."},{"type":"quote","text":[{"italic":true,"text":"\\"It got me thinking the real problem that we've been trying to solve in cybersecurity since the very start is one of prevention.\\""}]},{"type":"paragraph","text":"The vision was clear. The technology was not."},{"type":"paragraph","text":"Five years ago, enterprises were still figuring out how generative AI fit into everyday work. Endpoints couldn't run sophisticated models locally. Response times weren't fast enough. Most users weren't ready to rely on AI as part of their security experience."},{"type":"paragraph","text":"Then the landscape changed."},{"type":"paragraph","text":"Local AI models became practical. Copilot installed hardware emerged. Sub-second inference became possible. More importantly, AI became part of everyday work."},{"type":"quote","text":[{"italic":true,"text":"\\"And that's when we realized this great idea that we had five years ago is actually doable now.\\""}]},{"type":"paragraph","text":"The technology had finally caught up with the vision. It was time to build."},{"type":"heading","text":"The partnership behind the company"},{"type":"paragraph","text":[{"text":"Long before Ent, Lou and "},{"href":"https://docs.google.com/document/d/124gY9ZIa2OJmGv9nDPA_sD-4rTFxLMc48lcK2dsysRY/edit?tab=t.0#:~:text=Link-,https%3A//www.linkedin.com/in/brandonsdixon/details/experience/,-https%3A//www.linkedin","text":"Brandon"},{"text":" had spent years building security products together through some of the industry's b

56iggest shifts, from threat intelligence and attack surface management to AI-powered security."}]},{"type":"paragraph","text":"Their partnership began when Brandon co-founded PassiveTotal, a community-driven platform that helped security teams use DNS intelligence to track adversaries.RiskIQ acquired the company in 2015, bringing Brandon into the organization and beginning a collaboration that would span more than a decade."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/undefined-Jun-16-2026-12-33-26-8836-AM.png?width=1600","alt":"undefined-Jun-16-2026-12-33-26-8836-AM","caption":"Figure 1: Ent Founders Brandon Dixon and Elias Manousos"},{"type":"paragraph","text":"Together, they helped build RiskIQ into a leading threat intelligence company before joining Microsoft through acquisition. There, they worked on Defender Threat Intelligence, attack surface management, and one of the industry's earliest security copilots."},{"type":"paragraph","text":"Those experiences gave them a front-row seat to how security was evolving and where it continued to fall short."},{"type":"paragraph","text":"For years, both had helped organizations detect attacks, investigate incidents, and respond to threats. Ent was the chance to move beyond reactive security to more of preventive security."},{"type":"quote","text":[{"italic":true,"text":"\\"Brandon and I have been at this a long time, and we work really well together. That's what makes a great team.\\""}]},{"type":"paragraph","text":"What unites them isn’t just years of experience. It is the shared belief that security has to move beyond understanding what happened and get better at preventing what happens next."},{"type":"heading","text":"Shift to the new control point"},{"type":"paragraph","text":"As AI agents become part of everyday work, security faces a new challenge."},{"type":"paragraph","text":"Agents move faster than humans. They create more data, access more systems, and take actions on behalf of users at a speed and scale security teams have never had to manage before."},{"type":"paragraph","text":"During early conversations with customers and industry leaders, Lou kept returning to a fundamental question: where should security operate in a world where humans and agents work side by side?"},{"type":"quote","text":[{"italic":true,"text":"\\"We concluded that that control point will be at the endpoint or at the edge. That's the natural place where a human will task an agent.\\""}]},{"type":"paragraph","text":"That insight became one of Ent’s foundational ideas."},{"type":"paragraph","text":"The endpoint isn't just another security layer. It is where work happens, where users take decisions and increasingly where agents receive instructions and act."},{"type":"paragraph","text":"If organizations want to understand risk before it becomes an incident, Lou believes security needs to operate at the same place where intent originates."},{"type":"paragraph","text":"Understanding why, not just what"},{"type":"paragraph","text":"Throughout his career, Lou built systems to detect attacks and respond to incidents. He kept hitting the same limitation."},{"type":"paragraph","text":"Most security tools excel at telling what happened."},{"type":"paragraph","text":"Few can explain why."},{"type":"paragraph","text":"That distinction mattered long before AI entered the picture. Security teams have spent years trying to solve problems like insider risk, data loss, and human mistakes, where context matters more than the action itself."},{"type":"paragraph","text":"As AI systems began acting on behalf of users, it mattered even more."},{"type":"paragraph","text":"Whether the action comes from a person or an agent, intent provides the context that traditional security controls lack."},{"type":"quote","text":[{"italic":true,"text":"\\"Legacy security products are based on deterministic outcomes and look for the wrong things. They look at what happened and not why it happened.\\""}]},{"type":"paragraph","text":"For Lou, understanding intent wasn't simply another security signal. It became the foundation upon which Ent was built, and the opportunity to build the system Lou and Brandon wanted to for years."},{"type":"paragraph","text":[{"italic":true,"text":"\\"The system that we've always dreamed of building is one that can protect the entire end-user attack surface from any threat, whether that's an insider threat, intentional or unintentional data leakage, a phishing attack, unauthorized software, or malware, all classes of attacks in one unified endpoint.\\""}]},{"type":"paragraph","text":"The vision wasn't to solve one security problem. It was to create a platform capable of understanding and preventing risk across the entire end-user attack surface."},{"type":"heading","text":"The future of intent-aware security"},{"type":"paragraph","text":"The security challenges organizations face today are evolving rapidly as AI reshapes work."},{"type":"paragraph","text":"Work happens across more applications, data moves faster and across broader systems, and AI tools increasingly act on behalf of users."},{"type":"paragraph","text":"Lou believes the next major transformation will happen at the operating system level."},{"type":"paragraph","text":"Today, most AI systems function as applications layered on top of operating systems built for humans. As agents become more autonomous, that model will change. Future operating systems will increasingly be designed for both humans and agents working side by side."},{"type":"paragraph","text":"As agents gain access to files, applications, memory, and enterprise data, organizations will need new ways to understand and govern their actions. Deterministic controls will struggle to keep pace with software that can reason, act, and make decisions on behalf of users."}

56,{"type":"paragraph","text":"This shift has profound implications for security."},{"type":"paragraph","text":"This is where intent becomes critical."},{"type":"paragraph","text":"Understanding what happened will matter. Understanding why will become the different between reacting and preventing."},{"type":"paragraph","text":"As the boundaries between users and AI systems continue to blur, Lou believes the endpoint will remain the place where work, decisions, and risk converge."},{"type":"paragraph","text":[{"href":"https://vimeo.com/1201627841/d2a04d229a?share=copy&fl=sv&fe=ci","text":"Watch the full interview"},{"text":" with Lou Manousos for a deeper discussion on the future of workspace security."}]},{"type":"heading","text":"Resources"},{"type":"paragraph","text":[{"text":"To learn more about Ent and our vision for securing human and AI-driven work, visit "},{"href":"https://ent.ai/","text":"ent.ai."}]},{"type":"paragraph","text":[{"text":"Follow us on "},{"href":"https://x.com/Ent_Security","text":"X"},{"text":" and "},{"href":"https://www.linkedin.com/company/ent-security/posts/?feedView=all","text":"LinkedIn"},{"text":"."}]},{"type":"paragraph","text":"To talk to us and see our product in action, schedule a demo."}]},{"slug":"building-security-telemetry-for-intent","title":"Building Security Telemetry for Intent","authors":[{"name":"Brandon Dixon","title":"co-Founder & CTO at Ent"}],"image":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/u2872878144_You_are_an_illustrator_who_works_in_black_and_whi_80229ac3-9926-4145-8a45-442c852cbdc0_1.png?width=1600","date":"2026-06-15","updated":"2026-06-26","readMinutes":6,"excerpt":"Brandon Dixon|co-Founder & CTO at Ent","seoTitle":"Building Security Telemetry for Intent","metaDescription":"Telemetry built to understand intent: collect the right data at the endpoint, in real time, to intervene before risk becomes impact.","content":[{"type":"paragraph","text":"A new approach to telemetry collection designed to understand intent, enable real-time intervention, and secure both human and AI-driven work."},{"type":"paragraph","text":"Security has spent decades generating telemetry. So much of it, in fact, that entire companies now exist solely to optimize how security data is routed, compressed, stored, and queried. We have become exceptionally good at moving logs around. What I find more interesting is that we rarely stop to ask whether the telemetry itself is still the right abstraction for the problems we are trying to solve."},{"type":"paragraph","text":"I want to make the case that it is not, at least not for the problems that matter most now, and to explain how we approached telemetry differently when we built Ent."},{"type":"heading","text":"Telemetry, reconsidered"},{"type":"paragraph","text":"Historically, structured logs made perfect sense. They were cheap to store, easy to search, and flexible enough to work across many different systems. A process starts. A user authenticates. A file gets written. A network connection occurs. We capture the event and send it elsewhere for analysis."},{"type":"paragraph","text":"That approach worked well for a long time because most security problems were infrastru

56cture-centric. We were largely trying to understand machines, networks, and software. But as security has shifted toward understanding users, intent, and behavior, the limits of traditional telemetry have become much more obvious."},{"type":"paragraph","text":"Logs are summaries. They describe fragments of what happened, but rarely the full story."},{"type":"heading","text":"Security became a correlation problem"},{"type":"paragraph","text":"This is one of the reasons security has been so difficult operationally. Important information is sparse and spread across dozens of systems. Authentication logs live in one place. Endpoint events somewhere else. Browser activity in another product entirely. SaaS audit logs in a different dashboard. To make sense of any of it, an analyst has to understand not only how each system works, but what the logs actually contain and how they relate to one another."},{"type":"paragraph","text":"Even experienced analysts struggle with this. Over time, the industry accepted the complexity as normal and built workflows around it. Correlation engines, SIEM pipelines, and detection logic all emerged to stitch disconnected observations into something useful. Yet even with all of that infrastru

56cture, most security teams still operate reactively, because the telemetry itself arrives after the fact."},{"type":"paragraph","text":"If your product depends entirely on telemetry generated by someone else, you inherently limit your ability to intervene. Your visibility is constrained by whatever the operating system, the browser, or a third-party product chooses to expose. And telemetry has to be generated, forwarded, processed, and analyzed before any decision can happen. By the time a system determines that something risky occurred, the action has often already completed. The file is already uploaded. The credentials are already stolen. The data is already outside the organization."},{"type":"heading","text":"Starting from the operating system"},{"type":"paragraph","text":"At Ent, we approached this differently, because our focus is preventing risky actions, mistakes, and attacks before they happen. To do that, we concluded we needed to deploy where the work itself occurs and model interactions directly at the operating system layer. And to understand intent, we needed to collect our own telemetry."},{"type":"image","src":"https://243241691.fs1.hubspotusercontent-na2.net/hubfs/243241691/image-png.png?width=1600","alt":"","caption":"Figure 1: Operating-System-Level Telemetry and Context"},{"type":"paragraph","text":"Our telemetry is centered on interactions with the operating system: clicks, focus changes, clipboard actions, file access events, and other behavioral signals captured in real time. More importantly, we do not treat those actions as isolated events. We collect the semantic context around each one: who performed it, when, which application was involved, and the content that helps explain what was happening at the time."},{"type":"paragraph","text":"Years ago, a traditional log might have represented this as little more than a mouse event tied to a timestamp. Today, we can understand that a user copied sensitive financial information from an internal system, switched focus to a personal email account, and attempted to upload the contents externally. The interaction itself matters far less than the context surrounding it."},{"type":"paragraph","text":"Staying at the edge also changes what we have to move and what we can keep. Because we collect and reason about telemetry on the endpoint, the data does not have to leave the device to be useful. That is a practical advantage before it is a privacy one: less data in transit means lower bandwidth, lower storage cost, and no saturation from shipping everything to a central store."},{"type":"paragraph","text":"Telemetry collected staying at the endpoint is a privacy advantage. Organizations can preserve sensitive behavioral data without taking on the risk of warehousing all of it outside the boundary. And it is configurable. A customer can choose to send everything back, or only the data involved in a detection, depending on their own risk and compliance posture. When something does happen, none of that visibility is lost. Security teams can still reach back to the endpoint to collect the full context an investigation needs, on demand, rather than paying to stream it continuously just in case."},{"type":"heading","text":"Detection alone is not enough"},{"type":"paragraph","text":"Collecting our own telemetry also puts us in the best position to analyze and act on behavior directly at the edge. Ent continuously evaluates this real-time stream of activity to determine whether an intervention is necessary. When risky behavior is detected or a policy is violated, the platform can respond directly on the endpoint."},{"type":"paragraph","text":"We call these actions interventions."},{"type":"paragraph","text":"Some are silent. Capturing a screenshot, collecting additional forensic detail, or terminating a suspicious process can happen without interrupting the user. Others are intentionally visible. We can flash the screen, play a sound, suspend an action, or overlay directly on top of an application to collect more information from the user before letting them proceed."},{"type":"paragraph","text":"If Ent had been built entirely on traditional logs and delayed event pipelines, much of this would not be possible. We would not be able to evaluate behavior while it is actively occurring, and we would lose the ability to prevent an action before it completes."},{"type":"heading","text":"AI agents extend the same model"},{"type":"paragraph","text":"The same concept extends naturally to AI agents. Traditional telemetry models were never designed for agentic systems, because those systems largely did not exist. For us, agents fit naturally into the telemetry model we already built, because their goals, instructions, and actions are inherently semantic."},{"type":"paragraph","text":"Instead of trying to infer intent from sparse machine events, we can directly observe the relationship between the user and the agent: what the user asked the agent to do, which systems the agent touched, and the sequence of actions it took along the way."},{"type":"paragraph","text":"This matters more as agents gain broader access to enterprise systems and begin operating with greater autonomy. Our behavioral modeling applies across both humans and agents, so we can understand how work is actually happening across the enterprise and identify unusual or risky behavior as it unfolds."},{"type":"heading","text":"Rethinking telemetry for AI-native security"},{"type":"paragraph","text":"As AI continues to reshape how people work, I expect the security industry will need to revisit many of its historical assumptions about telemetry and detection architecture. The older model, collecting sparse machine-generated logs and reconstructing behavior afterward, worked reasonably well for infrastru

56cture monitoring. It is far less effective for understanding intent-driven interactions between users, applications, and autonomous agents operating in real time."},{"type":"paragraph","text":"For us, building telemetry from first principles was never about collecting more data. It was about collecting the right data, in the right place, with enough surrounding context to understand intent and take action before risk becomes impact."},{"type":"paragraph","text":[{"text":"To learn more about Ent and our vision for securing human and AI-driven work, visit "},{"href":"https://ent.ai/","text":"ent.ai."}]},{"type":"paragraph","text":[{"text":"Follow us on "},{"href":"https://x.com/Ent_Security","text":"X"},{"text":" and "},{"href":"https://www.linkedin.com/company/ent-security/posts/?feedView=all","text":"LinkedIn"},{"text":". To talk to us and see our product in action, schedule a demo."}]}]}]`),RI=AI,i2=e=>RI.find(n=>n.slug===e);function Mw(e){const n=e.map(i=>i.name).filter(Boolean);return n.length<=1?n[0]??"":`${n.slice(0,-1).join(", ")} & ${n[n.length-1]}`}function o2(e){return e.length===1&&e[0].title?`${e[0].name}, ${e[0].title}`:Mw(e)}const Nh=[{slug:"ent-extends-intent-aware-prevention",navLabel:"Ent Extends Intent-Aware Prevention",dateline:"July 30, 2026 — SAN FRANCISCO",date:"2026-07-30",headline:"Ent Extends Intent-Aware Prevention Across AI, Data, and Applications",subhead:"New on-device capabilities help organizations protect data, see and control AI usage and high-risk applications to counter AI-scaled threats across the modern workspace",body:[[{text:"Ent",href:"https://ent.ai"},{text:", the intent-aware workspace security company, today announced major platform enhancements that help organizations protect sensitive data and control the applications and AI tools used at the endpoint. The release follows the "},{text:"company’s launch from stealth",href:"/press/ent-raises-100m-seed"},{text:" in June and extends Ent’s prevention-first approach across more of the modern workspace."}],[{text:"A "},{text:"2026 Protiviti AI Pulse Survey",href:"https://www.protiviti.com/us-en/press-release-ai-pulse-half-enterprises-lack-ai-visibility"},{text:" found that 47% of large organizations lack full visibility into the AI tools their employees use, while 65% report challenges with shadow AI. Security teams need to know which tools are active, what data they can access, and whether that activity creates risk. At the same time, the "},{text:"2026 Verizon Data Breach Investigations Report",href:"https://www.verizon.com/business/resources/reports/dbir/"},{text:" found that threat actors are using generative AI for targeting, initial access, vulnerability research, and malware development, shrinking the window for defense from months to mere hours. Security teams face more AI activity to govern and faster-moving attacks to stop."}],"Ent was built ground-up for addressing this exact problem by evaluating and acting on user and agent activity and intent on the endpoint as it happens. It uses context from browsers, applications, AI tools, and files to distinguish routine work from activity that requires intervention. This release extends that intent-aware approach across the data, applications and AI tools attackers abuse, and AI agents through one programmable policy.","“Cybersecurity is shifting from explaining what happened after an incident to stopping incidents, to counter the speed of AI-era threats,” said Elias Manousos, CEO and co-founder of Ent. “The AI-scaled attacks expose the limits of cloud-dependent security. Prevention needs context from browsers, applications, and files so it can distinguish legitimate work from a hijacked user or rogue AI agent. These capabilities bring that control and decision to the endpoint while keeping sensitive context inside the customer’s environment.”","“Modern work creates signals that can look identical on the surface, even when the intent is completely different,” said Andrew Cal, CISO at WestCap. “We use Ent to secure our workspace by understanding the intent behind what users and AI agents are doing, tracking sensitive data movement, and stepping in before the damage occurs, all through one coordinated approach at the endpoint.”",{heading:"New Prevention Capabilities"},[{text:"AI visibility and control.",bold:!0}

56,{text:" Ent gives security teams a live view of the AI tools like OpenAI Codex, Claude Code, Claude Cowork, GitHub Copilot, Cursor, workflows and agents active in the workspace. They see who is using them, what data is going into them, and whether that activity fits the person’s role. Ent applies the same policy to humans and AI agents. It steers users to sanctioned tools, flags sensitive content before it reaches an AI application, and blocks risky agent behavior where needed."}],[{text:"Endpoint data protection.",bold:!0},{text:" Ent uses a custom Small Language Model (SLM) on the endpoint to classify sensitive data at the point of use and track how it is created and moved. The classification is attached to the data, and drives the same policy for both humans and AI agents, so data is protected no matter how it is used, moved, or manipulated. Ent moves past just content patterns and uses behaviors to separate routine work from real risk, reducing alert fatigue. Teams can see what data is sensitive, where it came from, where it resides, and where it is going across applications and AI tools."}],[{text:"Threat-aware application control.",bold:!0},{text:" Ent closes current EDR gaps by identifying applications and AI tools most often abused by attackers and enforcing custom policy-driven interventions to allow, block, deny or restrict usage. Customers can reduce their attack surface by controlling unsanctioned software, shadow AI, weaponized remote management tools, living-off-the-land binaries, and vulnerable drivers."}],"These build on Ent’s core prevention platform: behavioral context-rich visibility across users and AI-driven work, policy enforcement based on intent, just-in-time customized interventions, and natural-language investigation timelines. Ent runs as a single lightweight agent across Windows, macOS, Linux and modern browsers. Customers can deploy it as SaaS or self-hosted in their own cloud with complete data sovereignty.","Ent will showcase its platform innovations at booth #5341 during Black Hat USA 2026, taking place August 1-6 in Las Vegas.",[{text:"To learn more, visit "},{text:"ent.ai",href:"https://ent.ai"},{text:" or request a meeting at "},{text:"ent.ai/contact",href:"/contact"},{text:"."}],[{text:"Connect with us on "},{text:"X",href:"https://x.com/Ent_Security"},{text:" and "},{text:"LinkedIn",href:"https://www.linkedin.com/company/ent-security"},{text:"."}]],mediaContact:{name:"Cole Christy",org:"LaunchTech for Ent",email:"[email protected]",phone:"619-972-9836"},about:["Ent is the industry’s first intent-aware Workspace Security platform powering the AI-native enterprise, extending endpoint protection into a real-time layer of prevention across human and AI-driven work. Ent understands not just what users and agents do but why, and intervenes at the moment of risk before incidents occur. Founded by Elias Manousos and Brandon Dixon, co-founders of RiskIQ (acquired by Microsoft) and the team behind Microsoft Security Copilot, Ent is deployed within Global 2000 customers across hospitality, financial services, and defense. Backed by Decibel, Sequoia, Crosspoint Capital, Craft Ventures, Shield Capital, Felicis, and In-Q-Tel.","Protect work as it happens. Learn more at ent.ai."]},{slug:"ent-raises-100m-seed",navLabel:"Ent Emerges from Stealth",dateline:"June 16, 2026 — SAN FRANCISCO",date:"2026-06-16",headline:"Ent Emerges from Stealth to Bring Prevention Back to Cybersecurity",subhead:"$100 million seed round backs the industry’s first Intent-Aware Workspace Security Platform, built on real-time intervention and designed to stop AI-era threats before they become incidents.",body:["Ent, intent-aware Workspace Security company, today emerged from stealth with $100 million in seed financing. The company is pioneering a new approach to cybersecurity built around the simple belief that AI compresses the time between compromise and impact; prevention must once again become the primary objective of security. Ent’s platform helps organizations understand and intervene in risky actions by humans and AI agents before they become incidents.","Ent is already deployed with Global 2000 customers across hospital

56ity, financial services, and defense. Customers use Ent to detect insider risk, govern AI usage, prevent data loss, stop last-mile threats, and investigate incidents with the full behavioral context of what happened, why it happened, and what should happen next.",'"Security has been stuck in a reactive loop for over a decade, but AI-powered attacks require new thinking," said Elias Manousos, CEO and co-founder of Ent. "AI is changing both how people work and how quickly attackers can act. What once took days now happens in seconds. By the time traditional security systems detect a problem, it is too late. We believe the future of security lies in understanding intent in real time across people and AI agents and stopping risk before it becomes an incident.”',"Prevention requires a new layer at the workspace where work happens, across the browser, apps, AI workflows, and agents. Existing tools are blind because they collect at the wrong layer, tied to process and file events, and respond too late. As enterprises consolidate the platforms that protect endpoints, identities, applications, and data, the layer that reads intent across humans and AI agents in real time becomes the critical one. Ent operates at that layer.","Hosted in the customer's cloud with complete data sovereignty, Ent runs as a lightweight agent that brings AI reasoning to endpoints. The platform observes behavior across applications, browsers, workflows, data movement, and local runtimes; evaluates human and AI agent intent at the moment of use, applies customer-defined policy, and acts through configurable, just-in-time interventions before incidents occur.",[{text:"The funding is led by "},{text:"Decibel",href:"https://www.decibel.vc"},{text:", with participation from "},{text:"Sequoia",href:"https://www.sequoiacap.com"},{text:", "},{text:"Crosspoint Capital Partners",href:"https://www.crosspointcapital.com"},{text:", "},{text:"Craft Ventures",href:"https://www.craftventures.com"},{text:", "},{text:"Shield Capital",href:"https://www.shieldcap.com"},{text:", "},{text:"Felicis",href:"https://www.felicis.com"},{text:", and "},{text:"In-Q-Tel (IQT)",href:"https://www.iqt.org"},{text:"."}],'"AI has been a killer app for hackers and offensive researchers, but the industry is waiting for a novel defensive solution that can keep up with the modern era of LLMs,” said Jon Sakoda, Founding Partner at Decibel. "Ent has reimagined what is possible to protect the endpoint by using specialized AI models and adaptive policy enforcement to detect and prevent malicious activity in real time. It’s a game changer for cybersecurity teams who need a paradigm shift to defend their workforce against LLM-based attacks.”','"For a decade, endpoint security has relied on signals that arrive after the user’s action is complete," said Konstantin Buhler, Partner at Sequoia. "By running AI reasoning directly on the device, Ent moves from detection to prevention at the moment of decision. That shift is where the next era of endpoint defense gets built."',"“We have entered a new era defined by AI-powered attacks, one that demands a return to prevention and resilience,” said Greg Clark, Co-Founder and Managing Partner, Crosspoint Capital Partners. “The level of inference required to stop threats before they materialize must now live directly on the endpoint. Ent is leading this fundamental shift in endpoint protection.”",'"Rapid AI adoption is critical for our government partners, and a cornerstone of that adoption is safety and security," said Grant Whiting, Partner at IQT. "Ent provides the forensic clarity and preventive protection essential for secure AI operations, enabling organizations to monitor AI usage in real-time, govern risky behavior as it occurs, and preserve comprehensive records across every device."',"Ent's team brings together engineers and security operators with deep enterprise experience. The company's advisors include former CISOs of Google, Aetna, and MassMutual, the former Director of the NSA, and the former CVP of Microsoft Azure Cloud Security. The new funding will support continued hiring across engineering and go-to-market, while accelerating Ent’s roadmap across AI governance, threat prevention, security integrations, and multimodal endpoint intelligence.","Ent is generally available today for Windows, macOS, Linux, and browser-extension deployments. Ent will showcase its platform at booth #5341 during Black Hat USA 2026, taking place August 1-6 in Las Vegas.",[{text:"To learn more, visit "},{text:"ent.ai",href:"https://ent.ai"},{text:" or request a demo at "},{text:"ent.ai/demo",href:"/contact"},{text:"."}],[{text:"Connect with us on "},{text:"X",href:"https://x.com/Ent_Security"},{text:" and "},{text:"LinkedIn",href:"https://www.linkedin.com/company/ent-security"},{text:"."}]],mediaContact:{name:"Cole Christy",org:"LaunchTech for Ent",email:"[email protected]",phone:"619-972-9836"},about:["Ent is the intent-aware security platform powering the AI-native enterprise, extending endpoint security into a real-time layer of prevention across human and AI-driven work. Ent understands not just what users and agents do but why, and intervenes at the moment of risk before incidents occur. Founded by Elias Manousos and Brandon Dixon, co-founders of RiskIQ (acquired by Microsoft) and the team behind Microsoft Security Copilot, Ent is deployed within Global 2000 customers across hospital

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