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n=t.slice(0,1).toUpperCase()+t.slice(1),o={[`colorPalette${n}Background1`]:P[t].tint60,[`colorPalette${n}Background2`]:P[t].tint40,[`colorPalette${n}Background3`]:P[t].primary,[`colorPalette${n}Foreground1`]:P[t].shade10,[`colorPalette${n}Foreground2`]:P[t].shade30,[`colorPalette${n}Foreground3`]:P[t].primary,[`colorPalette${n}BorderActive`]:P[t].primary,[`colorPalette${n}Border1`]:P[t].tint40,[`colorPalette${n}Border2`]:P[t].primary};return Object.assign(e,o)},{});$e.colorPaletteYellowForeground1=P.yellow.shade30;$e.colorPaletteRedForegroundInverted=P.red.tint20;$e.colorPaletteGreenForegroundInverted=P.green.tint20;$e.colorPaletteYellowForegroundInverted=P.yellow.tint40;const xi=uo.reduce((e,t)=>{const n=t.slice(0,1).toUpperCase()+t.slice(1),o={[`colorPalette${n}Background2`]:pe[t].tint40,[`colorPalette${n}Foreground2`]:pe[t].shade30,[`colorPalette${n}BorderActive`]:pe[t].primary};return Object.assign(e,o)},{}),wi={...$e,...xi},_e=Object.entries(W).reduce((e,[t,n])=>{const o=t.slice(0,1).toUpperCase()+t.slice(1),a={[`colorStatus${o}Background1`]:C[n].tint60,[`colorStatus${o}Background2`]:C[n].tint40,[`colorStatus${o}Background3`]:C[n].primary,[`colorStatus${o}Foreground1`]:C[n].shade10,[`colorStatus${o}Foreground2`]:C[n].shade30,[`colorStatus${o}Foreground3`]:C[n].primary,[`colorStatus${o}ForegroundInverted`]:C[n].tint30,[`colorStatus${o}BorderActive`]:C[n].primary,[`colorStatus${o}Border1`]:C[n].tint40,[`colorStatus${o}Border2`]:C[n].primary};return Object.assign(e,a)},{});_e.colorStatusDangerBackground3Hover=C[W.danger].shade10;_e.colorStatusDangerBackground3Pressed=C[W.danger].shade20;_e.colorStatusWarningForeground1=C[W.warning].shade20;_e.colorStatusWarningForeground3=C[W.warning].shade20;_e.colorStatusWarningBorder2=C[W.warning].shade20;const ki=e=>({colorNeutralForeground1:g[14],colorNeutralForeground1Hover:g[14],colorNeutralForeground1Pressed:g[14],colorNeutralForeground1Selected:g[14],colorNeutralForeground2:g[26],colorNeutralForeground2Hover:g[14],colorNeutralForeground2Pressed:g[14],colorNeutralForeground2Selected:g[14],colorNeutralForeground2BrandHover:e[80],colorNeutralForeground2BrandPressed:e[70],colorNeutralForeground2BrandSelected:e[80],colorNeutralForeground3:g[38],colorNeutralForeground3Hover:g[26],colorNeutralForeground3Pressed:g[26],colorNeutralForeground3Selected:g[26],colorNeutralForeground3BrandHover:e[80],colorNeutralForeground3BrandPressed:e[70],colorNeutralForeground3BrandSelected:e[80],colorNeutralForeground4:g[44],colorNeutralForeground5:g[38],colorNeutralForeground5Hover:g[14],colorNeutralForeground5Pressed:g[14],colorNeutralForeground5Selected:g[14],colorNeutralForegroundDisabled:g[74],colorNeutralForegroundInvertedDisabled:H[40],colorBrandForegroundLink:e[70],colorBrandForegroundLinkHover:e[60],colorBrandForegroundLinkPressed:e[40],colorBrandForegroundLinkSelected:e[70],colorNeutralForeground2Link:g[26],colorNeutralForeground2LinkHover:g[14],colorNeutralForeground2LinkPressed:g[14],colorNeutralForeground2LinkSelected:g[14],colorCompoundBrandForeground1:e[80],colorCompoundBrandForeground1Hover:e[70],colorCompoundBrandForeground1Pressed:e[60],colorBrandForeground1:e[80],colorBrandForeground2:e[70],colorBrandForeground2Hover:e[60],colorBrandForeground2Pressed:e[30],colorNeutralForeground1Static:g[14],colorNeutralForegroundStaticInverted:S,colorNeutralForegroundInverted:S,colorNeutralForegroundInvertedHover:S,colorNeutralForegroundInvertedPressed:S,colorNeutralForegroundInvertedSelected:S,colorNeutralForegroundInverted2:S,colorNeutralForegroundOnBrand:S,colorNeutralForegroundInvertedLink:S,colorNeutralForegroundInvertedLinkHover:S,colorNeutralForegroundInvertedLinkPressed:S,colorNeutralForegroundInvertedLinkSelected:S,colorBrandForegroundInverted:e[100],colorBrandForegroundInvertedHover:e[110],colorBrandForegroundInvertedPressed:e[100],colorBrandForegroundOnLight:e[8

80],colorBrandForegroundOnLightHover:e[70],colorBrandForegroundOnLightPressed:e[50],colorBrandForegroundOnLightSelected:e[60],colorNeutralBackground1:S,colorNeutralBackground1Hover:g[96],colorNeutralBackground1Pressed:g[88],colorNeutralBackground1Selected:g[92],colorNeutralBackground2:g[98],colorNeutralBackground2Hover:g[94],colorNeutralBackground2Pressed:g[86],colorNeutralBackground2Selected:g[90],colorNeutralBackground3:g[96],colorNeutralBackground3Hover:g[92],colorNeutralBackground3Pressed:g[84],colorNeutralBackground3Selected:g[88],colorNeutralBackground4:g[94],colorNeutralBackground4Hover:g[98],colorNeutralBackground4Pressed:g[96],colorNeutralBackground4Selected:S,colorNeutralBackground5:g[92],colorNeutralBackground5Hover:g[96],colorNeutralBackground5Pressed:g[94],colorNeutralBackground5Selected:g[98],colorNeutralBackground6:g[90],colorNeutralBackground7:"#00000000",colorNeutralBackground7Hover:g[92],colorNeutralBackground7Pressed:g[84],colorNeutralBackground7Selected:"#00000000",colorNeutralBackground8:g[99],colorNeutralBackgroundInverted:g[16],colorNeutralBackgroundInvertedHover:g[24],colorNeutralBackgroundInvertedPressed:g[12],colorNeutralBackgroundInvertedSelected:g[22],colorNeutralBackgroundStatic:g[20],colorNeutralBackgroundAlpha:H[50],colorNeutralBackgroundAlpha2:H[80],colorSubtleBackgroun

8d:"transparent",colorSubtleBackgroundHover:g[96],colorSubtleBackgroundPressed:g[88],colorSubtleBackgroundSelected:g[92],colorSubtleBackgroundLightAlphaHover:H[70],colorSubtleBackgroundLightAlphaPressed:H[50],colorSubtleBackgroundLightAlphaSelected:"transparent",colorSubtleBackgroundInverted:"transparent",colorSubtleBackgroundInvertedHover:Q[10],colorSubtleBackgroundInvertedPressed:Q[30],colorSubtleBackgroundInvertedSelected:Q[20],colorTransparentBackground:"transparent",colorTransparentBackgroundHover:"transparent",colorTransparentBackgroundPressed:"transparent",colorTransparentBackgroundSelected:"transparent",colorNeutralBackgroundDisabled:g[94],colorNeutralBackgroundDisabled2:S,colorNeutralBackgroundInvertedDisabled:H[10],colorNeutralStencil1:g[90],colorNeutralStencil2:g[98],colorNeutralStencil1Alpha:Q[10],colorNeutralStencil2Alpha:Q[5],colorBackgroundOverlay:Q[40],colorScrollbarOverlay:Q[50],colorBrandBackground:e[80],colorBrandBackgroundHover:e[70],colorBrandBackgroundPressed:e[40],colorBrandBackgroundSelected:e[60],colorCompoundBrandBackground:e[80],colorCompoundBrandBackgroundHover:e[70],colorCompoundBrandBackgroundPressed:e[60],colorBrandBackgroundStatic:e[80],colorBrandBackground2:e[160],colorBrandBackground2Hover:e[150],colorBrandBackground2Pressed:e[130],colorBrandBackground3Static:e[60],colorBrandBackground4Static:e[40],colorBrandBackgroundInverted:S,colorBrandBackgroundInvertedHover:e[160],colorBrandBackgroundInvertedPressed:e[140],colorBrandBackgroundInvertedSelected:e[150],colorNeutralCardBackground:g[98],colorNeutralCardBackgroundHover:S,colorNeutralCardBackgroundPressed:g[96],colorNeutralCardBackgroundSelected:g[92],colorNeutralCardBackgroundDisabled:g[94],colorNeutralStrokeAccessible:g[38],colorNeutralStrokeAccessibleHover:g[34],colorNeutralStrokeAccessiblePressed:g[30],colorNeutralStrokeAccessibleSelected:e[80],colorNeutralStroke1:g[82],colorNeutralStroke1Hover:g[78],colorNeutralStroke1Pressed:g[70],colorNeutralStroke1Selected:g[74],colorNeutralStroke2:g[88],colorNeutralStroke3:g[94],colorNeutralStroke4:g[92],colorNeutralStroke4Hover:g[88],colorNeutralStroke4Pressed:g[84],colorNeutralStroke4Selected:g[92],colorNeutralStrokeSubtle:g[88],colorNeutralStrokeOnBrand:S,colorNeutralStrokeOnBrand2:S,colorNeutralStrokeOnBrand2Hover:S,colorNeutralStrokeOnBrand2Pressed:S,colorNeutralStrokeOnBrand2Selected:S,colorBrandStroke1:e[80],colorBrandStroke2:e[140],colorBrandStroke2Hover:e[120],colorBrandStroke2Pressed:e[80],colorBrandStroke2Contrast:e[140],colorCompoundBrandStroke:e[80],colorCompoundBrandStrokeHover:e[70],colorCompoundBrandStrokePressed:e[60],colorNeutralStrokeDisabled:g[88],colorNeutralStrokeDisabled2:g[92],colorNeutralStrokeInvertedDisabled:H[40],colorTransparentStroke:"transparent",colorTransparentStrokeInteractive:"transparent",colorTransparentStrokeDisabled:"transparent",colorNeutralStrokeAlpha:Q[5],colorNeutralStrokeAlpha2:H[20],colorStrokeFocus1:S,colorStrokeFocus2:Ye,colorNeutralShadowAmbient:"rgba(0,0,0,0.12)",colorNeutralShadowKey:"rgba(0,0,0,0.14)",colorNeutralShadowAmbientLighter:"rgba(0,0,0,0.06)",colorNeutralShadowKeyLighter:"rgba(0,0,0,0.07)",colorNeutralShadowAmbientDarker:"rgba(0,0,0,0.20)",colorNeutralShadowKeyDarker:"rgba(0,0,0,0.24)",colorBrandShadowAmbient:"rgba(0,0,0,0.30)",colorBrandShadowKey:"rgba(0,0,0,0.25)"}),mo={borderRadiusNone:"0",borderRadiusSmall:"2px",borderRadiusMedium:"4px",borderRadiusLarge:"6px",borderRadiusXLarge:"8px",borderRadius2XLarge:"12px",borderRadius3XLarge:"16px",borderRadius4XLarge:"24px",borderRadius5XLarge:"32px",borderRadius6XLarge:"40px",borderRadiusCircular:"10000px"},go={curveAccelerateMax:"cubic-bezier(0.9,0.1,1,0.2)",curveAccelerateMid:"cubic-bezier(1,0,1,1)",curveAccelerateMin:"cubic-bezier(0.8,0,0.78,1)",curveDecelerateMax:"cubic-bezier(0.1,0.9,0.2,1)",curveDecelerateMid:"cubic-bezier(0,0,0,1)",curveDecelerateMin:"cubic-bezier(0.33,0,0.1,1)",curveEasyEaseMax:"cubic-bezier(0.8,0,0.2,1)",curveEasyEase:"cubic-bezier(0.33,0,0.67,1)",curveLinear:"cubic-bezier(0,0,1,1)"},po={durationUltraFast:"50ms",durationFaster:"100ms",durationFast:"150ms",durationNormal:"200ms",durationGentle:"250ms",durationSlow:"300ms",durationSlower:"400ms",durationUltraSlow:"500ms"},ho={fontSizeBase100:"10px",fontSizeBase200:"12px",fontSizeBase300:"14px",fontSizeBase400:"16px",fontSizeBase500:"20px",fontSizeBase600:"24px",fontSizeHero700:"28px",fontSizeHero800:"32px",fontSizeHero900:"40px",fontSizeHero1000:"68px"},fo={lineHeightBase100:"14px",lineHeightBase200:"16px",lineHeightBase300:"20px",lineHeightBase400:"22px",lineHeightBase500:"28px",lineHeightBase600:"32px",lineHeightHero700:"36px",lineHeightHero800:"40px",lineHeightHero900:"52px",lineHeightHero1000:"92px"},yo={fontWeightRegular:400,fontWeightMedium:500,fontWeightSemibold:600,fontWeightBold:700},vo={fontFamilyBase:"'Segoe UI', 'Segoe UI Web (West European)', -apple-system, BlinkMacSystemFont, Roboto, 'Helvetica Neue', sans-serif",fontFamilyMonospace:"Consolas, 'Courier New', C

8ourier, monospace",fontFamilyNumeric:"Bahnschrift, 'Segoe UI', 'Segoe UI Web (West European)', -apple-system, BlinkMacSystemFont, Roboto, 'Helvetica Neue', sans-serif"},F={none:"0",xxs:"2px",xs:"4px",sNudge:"6px",s:"8px",mNudge:"10px",m:"12px",l:"16px",xl:"20px",xxl:"24px",xxxl:"32px"},bo={spacingHorizontalNone:F.none,spacingHorizontalXXS:F.xxs,spacingHorizontalXS:F.xs,spacingHorizontalSNudge:F.sNudge,spacingHorizontalS:F.s,spacingHorizontalMNudge:F.mNudge,spacingHorizontalM:F.m,spacingHorizontalL:F.l,spacingHorizontalXL:F.xl,spacingHorizontalXXL:F.xxl,spacingHorizontalXXXL:F.xxxl},xo={spacingVerticalNone:F.none,spacingVerticalXXS:F.xxs,spacingVerticalXS:F.xs,spacingVerticalSNudge:F.sNudge,spacingVerticalS:F.s,spacingVerticalMNudge:F.mNudge,spacingVerticalM:F.m,spacingVerticalL:F.l,spacingVerticalXL:F.xl,spacingVerticalXXL:F.xxl,spacingVerticalXXXL:F.xxxl},wo={strokeWidthThin:"1px",strokeWidthThick:"2px",strokeWidthThicker:"3px",strokeWidthThickest:"4px"};function Ze(e,t,n=""){return{[`shadow2${n}`]:`0 0 2px ${e}, 0 1px 2px ${t}`,[`shadow4${n}`]:`0 0 2px ${e}, 0 2px 4px ${t}`,[`shadow8${n}`]:`0 0 2px ${e}, 0 4px 8px ${t}`,[`shadow16${n}`]:`0 0 2px ${e}, 0 8px 16px ${t}`,[`shadow28${n}`]:`0 0 8px ${e}, 0 14px 28px ${t}`,[`shadow64${n}`]:`0 0 8px ${e}, 0 32px 64px ${t}`}}const Si=e=>{const t=ki(e);return{...mo,...ho,...fo,...vo,...yo,...wo,...bo,...xo,...po,...go,...t,...wi,..._e,...Ze(t.colorNeutralShadowAmbient,t.colorNeutralShadowKey),...Ze(t.colorBrandShadowAmbient,t.colorBrandShadowKey,"Brand")}},ko={10:"#061724",20:"#082338",30:"#0a2e4a",40:"#0c3b5e",50:"#0e4775",60:"#0f548c",70:"#115ea3",80:"#0f6cbd",90:"#2886de",100:"#479ef5",110:"#62abf5",120:"#77b7f7",130:"#96c6fa",140:"#b4d6fa",150:"#cfe4fa",160:"#ebf3fc"},ee=lo.reduce((e,t)=>{const n=t.slice(0,1).toUpperCase()+t.slice(1),o={[`colorPalette${n}Background1`]:P[t].shade40,[`colorPalette${n}Background2`]:P[t].shade30,[`colorPalette${n}Background3`]:P[t].primary,[`colorPalette${n}Foreground1`]:P[t].tint30,[`colorPalette${n}Foreground2`]:P[t].tint40,[`colorPalette${n}Foreground3`]:P[t].tint20,[`colorPalette${n}BorderActive`]:P[t].tint30,[`colorPalette${n}Border1`]:P[t].primary,[`colorPalette${n}Border2`]:P[t].tint20};return Object.assign(e,o)},{});ee.colorPaletteRedForeground3=P.red.tint30;ee.colorPaletteRedBorder2=P.red.tint30;ee.colorPaletteGreenForeground3=P.green.tint40;ee.colorPaletteGreenBorder2=P.green.tint40;ee.colorPaletteDarkOrangeForeground3=P.darkOrange.tint30;ee.colorPaletteDarkOrangeBorder2=P.darkOrange.tint30;ee.colorPaletteRedForegroundInverted=P.red.primary;ee.colorPaletteGreenForegroundInverted=P.green.primary;ee.colorPaletteYellowForegroundInverted=P.yellow.shade30;const Ft=uo.reduce((e,t)=>{const n=t.slice(0,1).toUpperCase()+t.slice(1),o={[`colorPalette${n}Background2`]:pe[t].shade30,[`colorPalette${n}Foreground2`]:pe[t].tint40,[`colorPalette${n}BorderActive`]:pe[t].tint30};return Object.assign(e,o)},{});Ft.colorPaletteDarkRedBackground2=pe.darkRed.shade20;

8Ft.colorPalettePlumBackground2=pe.plum.shade20;const Ai={...ee,...Ft},ye=Object.entries(W).reduce((e,[t,n])=>{const o=t.slice(0,1).toUpperCase()+t.slice(1),a={[`colorStatus${o}Background1`]:C[n].shade40,[`colorStatus${o}Background2`]:C[n].shade30,[`colorStatus${o}Background3`]:C[n].primary,[`colorStatus${o}Foreground1`]:C[n].tint30,[`colorStatus${o}Foreground2`]:C[n].tint40,[`colorStatus${o}Foreground3`]:C[n].tint20,[`colorStatus${o}BorderActive`]:C[n].tint30,[`colorStatus${o}ForegroundInverted`]:C[n].shade10,[`colorStatus${o}Border1`]:C[n].primary,[`colorStatus${o}Border2`]:C[n].tint20};return Object.assign(e,a)},{});ye.colorStatusDangerBackground3Hover=C[W.danger].shade10;ye.colorStatusDangerBackground3Pressed=C[W.danger].shade20;ye.colorStatusDangerForeground3=C[W.danger].tint40;ye.colorStatusDangerBorder2=C[W.danger].tint30;ye.colorStatusSuccessForeground3=C[W.success].tint40;ye.colorStatusSuccessBorder2=C[W.success].tint40;ye.colorStatusWarningForegroundInverted=C[W.warning].shade20;const So=Si(ko),_i=e=>({colorNeutralForeground1:S,colorNeutralForeground1Hover:S,colorNeutralForeground1Pressed:S,colorNeutralForeground1Selected:S,colorNeutralForeground2:g[84],colorNeutralForeground2Hover:S,colorNeutralForeground2Pressed:S,colorNeutralForeground2Selected:S,colorNeutralForeground2BrandHover:e[100],colorNeutralForeground2BrandPressed:e[90],colorNeutralForeground2BrandSelected:e[100],colorNeutralForeground3:g[68],colorNeutralForeground3Hover:g[84],colorNeutralForeground3Pressed:g[84],colorNeutralForeground3Selected:g[84],colorNeutralForeground3BrandHover:e[100],colorNeutralForeground3BrandPressed:e[90],colorNeutralForeground3BrandSelected:e[100],colorNeutralForeground4:g[60],colorNeutralForeground5:g[68],colorNeutralForeground5Hover:S,colorNeutralForeground5Pressed:S,colorNeutralForeground5Selected:S,colorNeutralForegroundDisabled:g[36],colorNeutralForegroundInvertedDisabled:H[40],colorBrandForegroundLink:e[100],colorBrandForegroundLinkHover:e[110],colorBrandForegroundLinkPressed:e[90],colorBrandForegroundLinkSelected:e[100],colorNeutralForeground2Link:g[84],colorNeutralForeground2LinkHover:S,colorNeutralForeground2LinkPressed:S,colorNeutralForeground2LinkSelected:S,colorCompoundBrandForeground1:e[100],colorCompoundBrandForeground1Hover:e[110],colorCompoundBrandForeground1Pressed:e[90],colorBrandForeground1:e[100],colorBrandForeground2:e[110],colorBrandForeground2Hover:e[130],colorBrandForeground2Pressed:e[160],colorNeutralForeground1Static:g[14],colorNeutralForegroundStaticInverted:S,colorNeutralForegroundInverted:g[14],colorNeutralForegroundInvertedHover:g[14],colorNeutralForegroundInvertedPressed:g[14],colorNeutralForegroundInvertedSelected:g[14],colorNeutralForegroundInverted2:g[14],colorNeutralForegroundOnBrand:S,colorNeutralForegroundInvertedLink:S,colorNeutralForegroundInvertedLinkHover:S,colorNeutralForegroundInvertedLinkPressed:S,colorNeutralForegroundInvertedLinkSelected:S,colorBrandForegroundInverted:e[80],colorBrandForegroundInvertedHover:e[70],colorBrandForegroundInvertedPressed:e[60],colorBrandForegroundOnLight:e[80],colorBrandForegroundOnLightHover:e[70],colorBrandForegroundOnLightPressed:e[50],colorBrandForegroundOnLightSelected:e[60],colorNeutralBackground1:g[16],colorNeutralBackground1Hover:g[24],colorNeutralBackground1Pressed:g[12],colorNeutralBackground1Selected:g[22],colorNeutralBackground2:g[12],colorNeutralBackground2Hover:g[20],colorNeutralBackground2Pressed:g[8],colorNeutralBackground2Selected:g[18],colorNeutralBackground3:g[8],colorNeutralBackground3Hover:g[16],colorNeutralBackground3Pressed:g[4],colorNeutralBackground3Selected:g[14],colorNeutralBackground4:g[4],colorNeutralBackground4Hover:g[12],colorNeutralBackground4Pressed:Ye,colorNeutralBackground4Selected:g[10],colorNeutralBackground5:Ye,colorNeutralBackground5Hover:g[8],colorNeutralBackground5Pressed:g[2],colorNeutralBackground5Selected:g[6],colorNeutralBackground6:g[20],colorNeutralBackground7:"#00000000",colorNeutralBackground7Hover:g[10],colorNeutralBackground7Pressed:g[4],colorNeutralBackground7Selected:"#00000000",colorNeutralBackgroun

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8,{step:"Analyst investigates",detail:"Evidence, timeline and Copilot summaries in one workspace."},{step:"Response executes",detail:"Playbooks and the Response Center drive action and record it."}],ai:["Copilot summaries and plain-language explanations of alerts and investigations.","AI-assisted triage suggestions with every recommendation logged to the tenant."],integrations:["Splunk","Microsoft Sentinel","ServiceNow","Jira","PagerDuty","Slack","Microsoft Teams","AWS Security Hub","Microsoft Defender for Cloud","Google Security Command Center"],businessOutcome:"Fewer consoles, faster investigations and one defensible record of AI activity.",relatedUseCases:["secops-modernization","executive-risk-visibility","account-takeover"],coreConnection:"CORE is the platform itself. Every add-on writes findings into it and reads risk, identity and asset context from it.",inOneSentence:"CORE is the platform itself: the registry of AI assets and agents, their telemetry, the detection engine, and the shared alert, investigation, response and automation workflow that every module writes into.",owns:["The inventory of AI assets and agents and what each can reach","Event telemetry from monitored agents, gateways and integrations","Detection rules, alerts and the unified findings model","Investigations, the Response Center, playbooks, Copilot and the audit log"],leavesTo:[{module:"identity",text:"Scoring and enforcing what an agent identity may do is AI Identity & Trust."},{module:"phishing",text:"Analysing email and social engineering is AI Phishing Protection."},{module:"dataguard",text:"Classifying data and following data flows is AI DataGuard."},{module:"offensive",text:"Attacking your own estate to prove exposure is AI Offensive."},{module:"governance",text:"Mapping controls and producing compliance evidence is AI Governance."}]},{slug:"identity",name:"AI Identity & Trust",kicker:"Identity security for AI agents",color:"#7C3AED",colorText:"#5B21B6",isCore:!1,valueProp:"Know which agent identities can be trusted before access becomes compromise.",summary:"Treats every AI agent and non-human identity as a first-class principal: what it is, who owns it, which credentials it holds, what it can reach and whether its behaviour still matches its baseline. High-risk actions route to a human approvals queue, and the enforcement plane can suspend, quarantine or kill an agent immediately.",problems:["AI agents hold credentials and entitlements nobody inventories.","An agent that starts behaving differently is indistinguishable from one that is compromised.","There is no place to approve, deny or revoke an agent's high-risk action."],outcomes:["Every agent identity registered with owner, role and deployment context.","An access graph of which agent can reach which tool, resource or model.","Trust scores and anomaly findings when behaviour drifts from baseline.","Human approval for high-risk actions and one-click emergency enforcement."],capabilities:[{name:"Agent identity registry",desc:"Catalogue every AI agent with owner, role, deployment context and lifecycle state."}

8,{name:"Access graph",desc:"Map agent → tool → resource → model relationships to see effective reach."},{name:"Credential inventory",desc:"Track the keys, tokens and service credentials each agent holds and when they rotate."},{name:"Trust scoring & anomaly detection",desc:"Per-agent risk scores recomputed as behaviour, reach and credentials change."},{name:"Approvals queue",desc:"Route high-risk agent actions to a reviewer to approve, reject or escalate."},{name:"Enforcement plane",desc:"Suspend, quarantine or kill an agent identity; every action is audited."}],workflow:[{step:"Register",detail:"Agents are discovered by CORE or registered with an owner."},{step:"Map reach",detail:"The access graph shows tools, data and models each agent can touch."},{step:"Score & watch",detail:"Trust scores drop when behaviour or reach drifts."},{step:"Approve or enforce",detail:"Reviewers approve risky actions; responders suspend or kill."}],ai:["Behavioural baselines per agent with anomaly findings that carry the evidence.","Copilot explanations of why an identity's trust score changed."],integrations:["SCIM 2.0 provisioning","Slack","Microsoft Teams","ServiceNow","Jira"],businessOutcome:"Agent identities become governable: owned, scoped, scored and revocable.",relatedUseCases:["identity-risk","account-takeover","attack-path-discovery"],coreConnection:"Identity findings enrich CORE investigations with who — or what — was acting, and CORE playbooks can call the enforcement plane.",inOneSentence:"AI Identity & Trust answers one question about every AI agent and non-human identity: can it be trusted right now — what it is, who owns it, what it holds, what it can reach and whether its behaviour still matches its baseline — and it enforces the answer.",owns:["The registry of agents and non-human identities, each with an owner and a purpose","The credentials and permissions each identity holds, and where they reach","Behavioural baselines, drift detection and a trust score per identity","Approvals for high-risk actions, and the enforcement plane: suspend, quarantine, kill"],leavesTo:[{module:"core",text:"The inventory of AI assets in general, and the shared alert and investigation workflow, live in CORE."},{module:"dataguard",text:"What data an agent actually moved is AI DataGuard’s question; Identity knows what it was allowed to reach."},{module:"phishing",text:"A phished human credential is caught by AI Phishing Protection; Identity takes over when an agent uses it."},{module:"offensive",text:"Whether an over-privileged identity is truly exploitable is proven by AI Offensive."}]},{slug:"phishing",name:"AI Phishing Protection",kicker:"Email and social-engineering defense",color:"#0891B2",colorText:"#0E7490",isCore:!1,valueProp:"Catch credential harvesting and executive impersonation before the click becomes an incident.",summary:"AI-assisted verdicts on suspicious messages, lookalike-domain and executive-impersonation detection, and risk intelligence that shows which people, departments and executives attackers are most likely to succeed against. Awareness simulations use AI-generated content so no two employees see the same lure.",problems:["Reported messages pile up with no consistent verdict or evidence trail.","Executive impersonation and lookalike domains slip past static filters.","Awareness programmes reuse the same templates and stop teaching anything."],outcomes:["A verdict, indicators and recommended action for each analysed message.","Named executives and lookalike domains watched continuously.","Risk intelligence by employee, department and executive.","Simulations with unique, AI-generated content and adaptive difficulty."],capabilities:[{name:"Phishing verdicts",desc:"Analyse a submitted message for credential-harvesting, BEC and impersonation indicators and record the verdict as a finding."},{name:"Lookalike-domain detection",desc:"Flag domains that imitate your brand or executives."},{name:"Executive impersonation watch",desc:"Maintain a watchlist of executives and detect messages that impersonate them."},{name:"Risk intelligence",desc:"Susceptibility and exposure views by employee, department and executive."},{name:"Awareness simulations",desc:"AI-generated, per-user campaign content with adaptive difficulty."}

8,{name:"Mailbox connectors (Microsoft 365, Google Workspace)",desc:"Automatic ingestion of reported and suspicious mail.",status:"planned"}],workflow:[{step:"Message arrives",detail:"Submitted by a user, analyst or integration."},{step:"Verdict",detail:"Indicators extracted, impersonation and lookalike checks run, verdict recorded."},{step:"Correlate",detail:"CORE links the verdict to the recipient's identity and data activity."},{step:"Respond",detail:"Playbooks notify, ticket and coach; risk intelligence updates."}],ai:["AI-assisted message analysis with indicators shown alongside the verdict.","Generative campaign content for simulations, unique per recipient."],integrations:["Slack","Microsoft Teams","ServiceNow","Jira","Email"],businessOutcome:"Faster, consistent phishing decisions and a measurable picture of human risk.",relatedUseCases:["phishing-bec","account-takeover","executive-risk-visibility"],coreConnection:"Every verdict becomes a CORE finding, so a phishing email, an anomalous agent login and a sensitive-data access can be worked as one investigation.",inOneSentence:"AI Phishing Protection is about email and social engineering aimed at people: verdicts on suspicious messages, lookalike domains and executive impersonation, who attackers are most likely to succeed against, and awareness simulations.",owns:["Verdicts on suspicious messages, with the indicators that drove them","Lookalike-domain and executive-impersonation detection","Department, executive and recipient risk intelligence","AI-generated awareness simulations and their results"],leavesTo:[{module:"identity",text:"What happens once a stolen credential is used by an agent belongs to AI Identity & Trust."},{module:"dataguard",text:"Whether sensitive data left through the lure is AI DataGuard’s finding."},{module:"core",text:"Containment — quarantining the message, resetting the account — runs through CORE playbooks."}]},{slug:"dataguard",name:"AI DataGuard",kicker:"Data protection for AI-era workflows",color:"#D97706",colorText:"#B45309",isCore:!1,valueProp:"Know what sensitive data is exposed, which path it leaves by, and stop it before it does.",summary:"Detects sensitive content in AI interactions and data flows, scans traffic through the AI content proxy, maps dataset lineage and model risk, and surfaces exfiltration paths and insider signals — all written into the same findings model your investigators already use.",problems:["Sensitive data reaches AI tools and external models unnoticed.","Nobody can say which datasets trained or fed which model.","Exfiltration is discovered after the fact, without the path it took."],outcomes:["PII, PHI, financial, credential and source-code exposures detected in AI interactions.","Dataset lineage and model risk ratings for the AI supply chain.","Exfiltration paths and insider signals ranked by sensitivity and reach.","Data-retention rules and legal holds applied where required."],capabilities:[{name:"Data loss detection",desc:"Pattern and semantic detection of PII, PHI, financial data, credentials and code in AI interactions."},{name:"AI content proxy scanning",desc:"Inspect prompts and responses flowing to AI services for sensitive content."},{name:"Dataset lineage",desc:"Trace which datasets feed which models and where they came from."},{name:"Model risk ratings & supply-chain checks",desc:"Rate deployed models and flag serialisation, backdoor and provenance risks."},{name:"Exfiltration paths & insider signals",desc:"Detect suspicious movement of sensitive data and the paths available to it."},{name:"Repository & storage connectors",desc:"Direct scanning of code and document repositories.",status:"planned"}],workflow:[{step:"Observe",detail:"AI interactions and data flows are classified as they happen."},{step:"Detect",detail:"Sensitive content and exfiltration paths raise findings."},{step:"Correlate",detail:"CORE ties the finding to the identity and asset involved."},{step:"Contain",detail:"Playbooks block, notify and open a ticket; retention rules apply."}],ai:["Semantic classification that understands meaning, not only patterns.","Copilot summaries of what was exposed and to whom."],integrations:["Splunk","Microsoft Sentinel","ServiceNow","Jira","Slack"],businessOutcome:"Provable control over sensitive data in AI workflows, with the evidence to show an auditor.",relatedUseCases:["sensitive-data-exposure","account-takeover","compliance-readiness"],coreConnection:"DataGuard findings carry data sensitivity into CORE risk scoring, so an exposed dataset raises the priority of every related alert.",inOneSentence:"AI DataGuard follows the data: which sensitive content moves through AI prompts, responses and proxies, where datasets and models come from, and which paths let data leave.",owns:["Sensitive-content detection in AI prompts, responses and data flows","The AI content proxy and its allow / block decisions","Dataset lineage, model provenance and ML supply-chain scans","Exfiltration paths and insider signals"],leavesTo:[{module:"identity",text:"Who the agent is, and whether it should have had access at all, is AI Identity & Trust."},{module:"offensive",text:"Whether an exposed bucket is reachable from outside is validated by AI Offensive."},{module:"governance",text:"Whether that exposure breaches a control is recorded by AI Governance."}]}

8,{slug:"offensive",name:"AI Offensive",kicker:"Exposure validation and attack-path discovery",color:"#DC2626",colorText:"#B91C1C",isCore:!1,valueProp:"Find the attack path before an adversary does — and prove which controls would stop it.",summary:"Plans and runs red-team engagements against your AI agents and assets, maps attack paths from entry point to crown jewels, rates exploit readiness, and records purple-team runs that show which detections actually fired. Execution against live targets is disabled by default and enabled per tenant with network guardrails.",problems:["Vulnerability lists have no notion of what is actually reachable.","AI agents and their tool access are rarely in scope for testing.","Nobody knows whether existing detections would catch the path that matters."],outcomes:["Attack paths ranked by feasibility, not CVSS alone.","Red-team scenarios targeting prompt injection, jailbreaks and tool abuse.","Purple-team evidence of which detections fired and which did not.","Exposure drift tracked over time as the environment changes."],capabilities:[{name:"Red-team engagements & scenarios",desc:"Plan campaigns against AI agents and assets mapped to MITRE ATT&CK and OWASP."},{name:"Attack-path analysis",desc:"Chain entry points, identities, tools and data into paths ranked by feasibility."},{name:"Exploit readiness & simulations",desc:"Score how exploitable a weakness is and simulate the outcome."},{name:"Purple-team runs",desc:"Record which detections fired for each technique and where coverage is missing."},{name:"Vulnerability management",desc:"Findings for the AI/ML stack, including model scanning."},{name:"Guarded execution",desc:"Live execution is off by default, role-restricted, network-guarded and audited when enabled."}],workflow:[{step:"Scope",detail:"Choose targets from the CORE registry and the identities that can reach them."},{step:"Model paths",detail:"Attack paths and feasibility scores are computed."},{step:"Validate",detail:"Scenarios run (guarded) and purple-team results are recorded."},{step:"Fix what matters",detail:"Findings flow to CORE with the controls that would break the path."}],ai:["Scenario generation for AI-specific techniques such as prompt injection and tool abuse.","Copilot narratives that explain an attack path to a non-specialist."],integrations:["Jira","ServiceNow","Splunk","Microsoft Sentinel"],businessOutcome:"Remediation effort spent on the exposures an attacker could actually use.",relatedUseCases:["attack-path-discovery","identity-risk","secops-modernization"],coreConnection:"Attack paths reuse CORE's asset and identity graph, and validated exposures raise the risk score of the assets on the path.",inOneSentence:"AI Offensive attacks your AI estate before an adversary does: posture findings, red-team campaigns against agents and assets, attack paths from entry point to crown jewels, and purple-team runs that show which detections actually fired.",owns:["Attack-surface and posture findings on AI assets","Red-team scenarios — prompt injection, tool abuse, escalation — and their results","Attack paths and exploit readiness","Purple-team runs: which controls held and which detections fired"],leavesTo:[{module:"core",text:"Detecting a real attack as it happens is CORE’s detection engine; Offensive proves what would work."},{module:"identity",text:"Fixing an over-privileged identity is done in AI Identity & Trust."},{module:"governance",text:"Turning a failed test into a control gap and evidence is AI Governance."}]},{slug:"governance",name:"AI Governance",kicker:"Compliance, risk quantification and assurance",color:"#059669",colorText:"#047857",isCore:!1,valueProp:"Turn AI activity into compliance evidence and board-level risk, continuously.",summary:"Maps controls to NIST AI RMF, EU AI Act, ISO 42001 and SOC 2, collects evidence from platform activity, quantifies risk in business terms, manages policies and exceptions, and validates that the controls around your AI estate are configured the way you believe they are.",problems:["Evidence collection is a quarterly scramble across teams.","Risk is reported as colours, not numbers the board can act on.","Security tools drift from their intended configuration without anyone noticing."],outcomes:["Framework coverage with evidence linked to real platform activity.","Quantified risk with propagation across assets, vendors and departments.","Policies and exceptions with owners, expiry and compensating controls.","Continuous assurance that tooling matches intended posture."],capabilities:[{name:"Framework compliance",desc:"Control mapping and status for NIST AI RMF, EU AI Act, ISO 42001 and SOC 2."},{name:"Evidence collection",desc:"Evidence tied to detections, investigations and configuration changes."},{name:"Risk quantification",desc:"FAIR-style quantification with propagation across assets, vendors and departments."},{name:"Policies & exceptions",desc:"Policy library, exception workflow with 

8justification, expiry and approvals."},{name:"Security assurance",desc:"Validate that identity, DLP, logging and AI-API controls are configured as intended."},{name:"Data retention & legal holds",desc:"Retention rules and legal holds across tenant data."}],workflow:[{step:"Map",detail:"Controls are mapped to the frameworks you report against."},{step:"Collect",detail:"Platform activity becomes evidence automatically."},{step:"Quantify",detail:"Risk is expressed in business terms and propagated."},{step:"Report",detail:"Executive and audit views from the same record."}],ai:["Copilot drafting of control narratives from linked evidence.","Risk summaries written for executives, with the underlying findings one click away."],integrations:["ServiceNow","Jira","Email"],businessOutcome:"Audit readiness as a by-product of daily operations, and risk the board can reason about.",relatedUseCases:["compliance-readiness","executive-risk-visibility","sensitive-data-exposure"],coreConnection:"Every CORE investigation and module finding is mapped to affected controls, so governance status reflects what actually happened.",inOneSentence:"AI Governance turns everything the other modules record into compliance evidence, quantified risk and policy: framework control mapping, evidence collection, exceptions with compensating controls, and assurance that your tooling is configured the way you believe.",owns:["Control mapping to NIST AI RMF, EU AI Act, ISO 42001, SOC 2 and OWASP LLM Top 10","Evidence collected from platform activity, with validity and expiry","Risk quantification in business terms, policies and exceptions","Assurance: tooling validation, detection coverage and blind spots"],leavesTo:[{module:"core",text:"It does not detect or respond to incidents; it records their control impact."},{module:"dataguard",text:"It does not find sensitive data; it maps what AI DataGuard found to controls."},{module:"offensive",text:"It does not test controls by attack; it consumes AI Offensive’s results as assurance evidence."}]}],zg=Pe.filter(e=>!e.isCore),Hg=Pe[0],Vg=e=>Pe.find(t=>t.slug===e),qg=[{module:"phishing",signal:"Credential-harvesting email verdict",detail:"A message impersonating the CFO is analysed and recorded as a finding against the recipient."},{module:"identity",signal:"Anomalous credential use",detail:"A finance workflow agent tied to that recipient starts calling tools outside its baseline."},{module:"dataguard",signal:"Sensitive financial data accessed",detail:"Payment-run exports are read and pushed toward an external AI endpoint."},{module:"core",signal:"Signals correlated into one investigation",detail:"CORE links the three findings on one timeline with the identity, asset and data context."},{module:"offensive",signal:"Attack path confirmed",detail:"The path from mailbox → agent credentials → export storage is rated highly feasible."},{module:"governance",signal:"Affected controls identified",detail:"Access-control and data-handling controls are flagged with evidence attached."},{module:"core",signal:"Risk summarised, response recommended",detail:"Copilot summarises the incident; a playbook suspends the agent, opens a ticket and notifies the SOC — pending approval."}],Wg=[{title:"Unified intelligence",desc:"One findings model, one risk score, one investigation timeline — across identity, phishing, data, exposure and governance."},{title:"AI-assisted investigations",desc:"Copilot explains alerts, drafts investigations and summarises risk, with every recommendation logged in your tenant."},{title:"Cross-module correlation",desc:"A phishing verdict, an identity anomaly and a data exposure become one incident, not three tickets."},{title:"Modular architecture",desc:"Start with CORE, add the modules you need, and keep one platform as you grow."},{title:"Unified risk visibility",desc:"Risk scoring that reflects exposure, identity trust and data sensitivity together."},{title:"Automation with control",desc:"Playbooks and if/then rules act through your integrations; high-risk actions wait for a human."},{title:"Enterprise governance",desc:"RBAC, tenant isolation, audit trails, retention and legal holds are platform features, not add-ons."},{title:"Less tool fragmentation",desc:"Fewer consoles to learn, fewer hand-offs to lose context in, one record to defend."}],Qg=[{title:"Security data",desc:"Telemetry from agents, findings from modules, events from integrations."},{title:"ARGUS intelligence",desc:"Everything lands in one findings model with identity, asset and data context."},{title:"AI analysis & correlation",desc:"Rules and analytics link related signals; Copilot summarises what matters."},{title:"Risk prioritisation",desc:"Exposure, trust and sensitivity combine into a score teams can act on."},{title:"Investigation",desc:"One workspace with evidence, timeline and recommended next steps."},{title:"Automated & human response",desc:"Playbooks act through integrations; approvals keep humans in control."}],Vo=[{slug:"account-takeover",title:"Account and credential takeover investigation",persona:"SOC leader",question:"How does this improve my operations?",challenge:"A phishing email, a strange login and a data download are three tickets in three tools. By the time someone joins them, the data has left.",how:[{module:"phishing",text:"The credential-harvesting message is analysed and recorded as a finding against the recipient."},{module:"identity",text:"Credential and behaviour anomalies on the associated agent identity drop its trust score."},{module:"dataguard",text:"Sensitive-data access by that identity raises a data finding with the exfiltration path."},{module:"core",text:"The three findings are correlated into one investigation with a recommended playbook."}],workflow:["Verdict recorded","Identity anomaly correlated","Data access linked","Playbook 

8suspends credentials pending approval"],outcome:"One investigation instead of three tickets, and containment before the export completes."},{slug:"phishing-bec",title:"Phishing and business email compromise",persona:"CISO",question:"Why should I care?",challenge:"Executive impersonation and lookalike domains bypass filters, and reported messages get inconsistent answers.",how:[{module:"phishing",text:"Verdicts with indicators, executive-impersonation watchlist and lookalike-domain detection."},{module:"core",text:"Verdicts become findings; playbooks notify the recipient and open a ticket."},{module:"governance",text:"Human-risk intelligence feeds control status and evidence."}],workflow:["Message submitted","Indicators and verdict","Recipient and department risk updated","Ticket and coaching"],outcome:"Consistent phishing decisions with an evidence trail, and a measurable picture of human risk."},{slug:"sensitive-data-exposure",title:"Sensitive data exposure in AI workflows",persona:"Security engineer",question:"What can this actually do?",challenge:"Employees and agents send PII, source code and financial data to AI tools, and nobody can say what left or where it went.",how:[{module:"dataguard",text:"Content detection in AI interactions and proxy scans; exfiltration paths and insider signals."},{module:"identity",text:"The identity behind the access and what else it can reach."},{module:"core",text:"Findings prioritised by sensitivity; playbooks block and notify."}],workflow:["Interaction classified","Exposure finding raised","Identity and asset context attached","Contain and record"],outcome:"Exposures caught with the path they took, and evidence that controls worked."},{slug:"attack-path-discovery",title:"Attack-path discovery and exposure validation",persona:"Security engineer",question:"What can this actually do?",challenge:"Thousands of vulnerabilities, no idea which are reachable, and AI agents with tool access nobody has tested.",how:[{module:"offensive",text:"Attack paths ranked by feasibility; scenarios against agents; purple-team results."},{module:"identity",text:"Agent reach from the access graph feeds the path model."},{module:"core",text:"Validated exposures raise asset risk and create remediation findings."}],workflow:["Scope targets","Model and rank paths","Validate (guarded)","Remediate what matters"],outcome:"Remediation focused on paths an attacker could actually use."},{slug:"compliance-readiness",title:"Compliance readiness for AI systems",persona:"Procurement / GRC",question:"What am I purchasing?",challenge:"NIST AI RMF, the EU AI Act and ISO 42001 need evidence about AI systems that no existing tool records.",how:[{module:"governance",text:"Framework mapping, evidence collection, policies and exceptions, retention and legal holds."},{module:"core",text:"Investigations and detections become linked evidence automatically."},{module:"dataguard",text:"Dataset lineage and model risk ratings document the AI supply chain."}],workflow:["Map controls","Evidence collected from activity","Gaps and exceptions managed","Audit-ready reporting"],outcome:"Audit readiness as a by-product of operations instead of a quarterly project."},{slug:"identity-risk",title:"AI agent identity risk",persona:"CISO",question:"Why should I care?",challenge:"AI agents hold credentials and entitlements that were never designed, reviewed or revoked.",how:[{module:"identity",text:"Registry, access graph, credential inventory, trust scores, approvals and enforcement."},{module:"offensive",text:"Attack paths that pass through over-privileged agents."},{module:"core",text:"Identity findings correlated with everything else the agent touched."}],workflow:["Register and assign owners","Map reach","Score and watch","Approve or enforce"],outcome:"Agent identities that are owned, scoped, scored and revocable."},{slug:"secops-modernization",title:"Bringing AI activity into security operations",persona:"SOC leader",question:"How does this improve my operations?",challenge:"Analysts swivel between consoles, investigations are rebuilt by hand and automation lives in scripts nobody owns.",how:[{module:"core",text:"Shared findings, investigations, Response Center, playbooks and Copilot."},{module:"phishing",text:"Phishing triage handled as findings, not a separate queue."},{module:"governance",text:"Every incident mapped to controls without extra work."}],workflow:["Signals in one place","Correlation and prioritisation","Investigate with Copilot","Respond through integrations"],outcome:"Fewer hand-offs, faster investigations and automation your team can audit."},{slug:"executive-risk-visibility",title:"Executive cyber-risk visibility",persona:"CEO / Board",question:"How does this reduce organisational risk?",challenge:"Leadership sees red/amber/green summaries disconnected from what the security team is actually working on.",how:[{module:"governance",text:"Quantified risk with propagation across assets, vendors and departments."},{module:"core",text:"Risk scores and open investigations from the same record the SOC uses."},{module:"phishing",text:"Human-risk intelligence by department and executive."}],workflow:["Operational findings","Risk quantified","Trends and top drivers","Executive summary"],outcome:"Board-level risk that traces to the findings behind it."}],Ug=e=>Vo.find(t=>

8t.slug===e),cd=[{name:"Splunk",category:"SIEM",direction:"both",status:"available",note:"HTTP Event Collector out; forwarder ingest in."},{name:"Microsoft Sentinel",category:"SIEM",direction:"both",status:"available",note:"Log Analytics out; forwarder ingest in."},{name:"Generic SIEM ingest",category:"SIEM",direction:"inbound",status:"available",note:"JSON events over an API key."},{name:"Cortex XSOAR",category:"SOAR & automation",direction:"outbound",status:"available",note:"Webhook trigger."},{name:"Tines",category:"SOAR & automation",direction:"outbound",status:"available",note:"Webhook trigger."},{name:"Generic webhook",category:"SOAR & automation",direction:"outbound",status:"available",note:"Signed JSON payloads."},{name:"ServiceNow",category:"Ticketing",direction:"outbound",status:"available"},{name:"Jira",category:"Ticketing",direction:"outbound",status:"available"},{name:"PagerDuty",category:"Ticketing",direction:"outbound",status:"available"},{name:"Slack",category:"Collaboration",direction:"outbound",status:"available"},{name:"Microsoft Teams",category:"Collaboration",direction:"outbound",status:"available"},{name:"Email",category:"Collaboration",direction:"outbound",status:"available"},{name:"AWS Security Hub",category:"Cloud security",direction:"inbound",status:"available"},{name:"Microsoft Defender for Cloud",category:"Cloud security",direction:"inbound",status:"available"},{name:"Google Security Command Center",category:"Cloud security",direction:"inbound",status:"available"},{name:"SCIM 2.0 provisioning",category:"Identity",direction:"inbound",status:"available",note:"User and group provisioning from your identity provider."},{name:"ARGUS Collector",category:"Platform",direction:"inbound",status:"available",note:"Agent telemetry, discoveries and configuration changes."},{name:"REST API & API keys",category:"Platform",direction:"both",status:"available"},{name:"Microsoft 365 mailbox connector",category:"Collaboration",direction:"inbound",status:"planned",note:"Reported-mail ingestion for AI Phishing Protection."},{name:"Google Workspace mailbox connector",category:"Collaboration",direction:"inbound",status:"planned",note:"Reported-mail ingestion for AI Phishing Protection."},{name:"Repository & document-store connectors",category:"Platform",direction:"inbound",status:"planned",note:"Direct scanning for AI DataGuard."},{name:"Passive network discovery",category:"Platform",direction:"inbound",status:"planned",note:"DNS / proxy / packet-based AI discovery."}],Gg=Array.from(new Set(cd.map(e=>e.category))),ld={available:"Available",beta:"Beta",planned:"Planned"},Yg=[{key:"core",title:"ARGUS ONE CORE",who:"Every deployment starts here.",desc:"The platform foundation: registry, telemetry, detection, alerts, investigations, Response Center, automation, Copilot and audit.",includes:["All CORE capabilities","Integrations and API","RBAC, tenant isolation, audit log","Standard support"]},{key:"core-plus",title:"CORE + selected modules",who:"Teams with specific priorities.",desc:"Add any of the five modules individually. Each is licensed separately and switches on inside the same platform.",includes:["Everything in CORE","Any combination of add-on modules",`${z.trialDays}-day in-product module trials`,"Cross-module correlation for the modules you own"]},{key:"complete",title:"ARGUS ONE Complete",who:"Organisations that want the full intelligence layer.",desc:"CORE plus all five modules: identity, phishing, data, exposure validation and governance correlated in one record.",includes:["Everything in CORE","All five add-on modules","Full cross-module correlation and unified risk","Priority onboarding"]},{key:"enterprise",title:"Enterprise",who:"Custom scope, terms and deployment requirements.",desc:"Tailored licensing, deployment and support arrangements for larger or regulated environments.",includes:["Custom licensing dimensions","Deployment and data-residency discussion","Security documentation under NDA","Named support contact"]}],Xg=[{key:"documentation",title:"Documentation",desc:"Product documentation, API reference and integration guides.",items:[],onRequest:"Full product documentation ships in-product with every deployment. Ask us for the customer guides and API reference."},{key:"product-guides",title:"Product guides & datasheets",desc:"Module overviews, architecture and deployment guides.",items:[{title:"Platform overview",desc:"How CORE and the five modules fit together.",href:"/product",kind:"page"}

8,{title:"Integrations",desc:"What connects today, what is in beta and what is planned.",href:"/product#integrations",kind:"page"}],onRequest:"Module datasheets are available on request from your product specialist."},{key:"solution-briefs",title:"Solution briefs & use cases",desc:"How ARGUS ONE is applied to specific AI security problems.",items:[{title:"Use cases",desc:"Eight problem-led walkthroughs from challenge to outcome.",href:"/use-cases",kind:"page"}]},{key:"whitepapers",title:"Whitepapers & research",desc:"Longer-form thinking on AI activity security and identity for AI agents.",items:[],onRequest:"Early copies of our research are available on request."},{key:"security-insights",title:"Security insights & blog",desc:"Practitioner writing from the ARGUS team.",items:[],onRequest:"Ask us for a briefing on any AI-security topic — our practitioners write from live engagements."},{key:"compliance",title:"Compliance & trust",desc:"How the platform is built, isolated and operated.",items:[{title:"Security & Trust",desc:"Tenant isolation, access control, audit, responsible AI and our compliance approach.",href:"/security",kind:"page"},{title:"Privacy policy",desc:"What we collect on this site and in the platform, and why.",href:"/privacy",kind:"page"}]},{key:"faq",title:"FAQs",desc:"Straight answers on packaging, trials, deployment and integrations.",items:[{title:"Frequently asked questions",desc:"Packaging, trials, deployment, integrations, AI and data handling.",href:"/resources/faq",kind:"page"}]},{key:"case-studies",title:"Case studies",desc:"Customer outcomes, published with permission.",items:[],onRequest:"Customer outcomes are published with their approval. Ask us for a walkthrough on your own scenario."},{key:"videos",title:"Videos & product demos",desc:"Recorded walkthroughs of the platform and modules.",items:[{title:"Guided product tour",desc:"Six steps from signal to governed response.",href:"/#tour",kind:"page"}],onRequest:"Live demos are available now — a product specialist walks y

8ou through the platform on your own scenarios."},{key:"release-notes",title:"Release notes",desc:"What changed, when.",items:[],onRequest:"Release notes are published with each general-availability release. Ask us for the current change summary."}],Kg=[{group:"Platform and packaging",items:[{q:"What is ARGUS ONE?",a:"An AI activity security platform. It gives every AI agent, assistant and model an identity, records what it does, and brings identity security for AI agents, AI-driven phishing defense, data protection for AI flows, AI exposure validation and AI governance into one correlated record. It complements the SIEM, EDR and identity tools you already run rather than replacing them. ARGUS ONE CORE is the foundation; five add-on modules extend it."},{q:"Is ARGUS ONE one product or six?",a:"One platform. CORE is always present. AI Identity & Trust, AI Phishing Protection, AI DataGuard, AI Offensive and AI Governance are modules that switch on inside the same platform and write to the same findings, risk and investigation records."},{q:"Can I buy a module without CORE?",a:"No. Every module runs on CORE, which provides the registry, telemetry, detection engine, investigations and automation the modules rely on. You can buy CORE alone, CORE plus any selection of modules, or ARGUS ONE Complete."},{q:"How is licensing sized?",a:"Licensing is sized to your environment — the monitored AI assets and event volume — and the modules you select. Pricing is provided by quote; request a demo and we will scope it with you."},{q:"Do you offer trials?",a:`Yes. Customers can start a ${z.trialDays}-day trial of any module from inside the platform, without a payment method. Trials are provisioned on the server, so they follow your organisation, not one browser.`}]},{group:"Deployment and security",items:[{q:"How is ARGUS ONE deployed?",a:"ARGUS ONE is delivered as a multi-tenant SaaS hosted on Microsoft Azure. Each customer is a separate tenant with database row-level isolation. Other deployment arrangements are discussed under the Enterprise option."},{q:"How are tenants isolated?",a:"Every tenant-scoped table is protected by Postgres row-level security policies, and each request runs in a database session bound to the caller's tenant. Platform-owner and tenant roles are separate."},{q:"Which certifications do you hold?",a:"ARGUS ONE is not yet independently certified against SOC 2 or ISO 27001. Our controls are designed with those frameworks in mind, and we share security documentation and our certification roadmap with prospects under NDA. We do not publish claims we cannot evidence."},{q:"How do you use AI, and what happens to my data?",a:"AI features such as Argus Copilot process tenant data only to answer the request, and every prompt and recommendation is logged inside your tenant. High-risk actions proposed by the platform can be routed to a human approvals queue. AI features are cost-gated per tenant."},{q:"Can the offensive module damage my environment?",a:"Live execution in AI Offensive is disabled by default. When a tenant enables it, execution is role-restricted, blocked from internal address ranges by a network guard, and every campaign start is audited."}]},{group:"Integrations and operations",items:[{q:"What integrates today?",a:"Outbound: Splunk, Microsoft Sentinel, generic webhooks, Cortex XSOAR, Tines, PagerDuty, Slack, Microsoft Teams, ServiceNow, Jira and email. Inbound: AWS Security Hub, Microsoft Defender for Cloud, Google Security Command Center, SIEM forwarders, the ARGUS Collector, SCIM 2.0 and the REST API. Mailbox and repository connectors are planned. The full list with status is on the Platform page."},{q:"Which roles does the platform support?",a:"Admin, Analyst, IR Lead, GRC Lead, CISO and Read Only, with role checks on every module write and an audit record for each."},{q:"How do I get support?",a:`Customers have an in-product support path and a named contact under Enterprise terms. Prospects can reach us at ${z.contactEmail}.`}]}],Jg=[{title:"Tenant isolation",points:["Postgres row-level security policies on every tenant-scoped table.","Each request runs in a database session bound to the caller's tenant.","Platform-owner and customer-tenant roles are separate; admin impersonation is explicit and audited."]},{title:"Access control and authentication",points:["Role-based access control: Admin, Analyst, IR Lead, GRC Lead, CISO, Read Only.","Role checks on every module write, with an audit record for each.","Multi-factor authentication with one-time codes, session management and SCIM 2.0 provisioning."]},{title:"Audit and integrity",points:["Append-only audit log of security and administrative actions.","Hash-chained execution ledger for AI agent steps.","Change manifest for configuration changes made by the platform."]},{title:"Secure architecture and delivery",points:["Hosted on Microsoft Azure; TLS for all traffic.","Integration credentials encrypted at rest.","Every build generates a software bill of materials and is scanned for critical vulnerabilities before it can deploy; production promotion is a separate, manual step.","Public endpoints are rate-limited; authentication endpoints have brute-force protection."]},{title:"Responsible AI",points:["AI features assist analysts; recommendations and prompts are logged in the tenant.","High-risk agent actions can be routed to a human approvals queue before they run.","Offensive execution is off by default, role-restr

8icted and network-guarded when enabled.","AI usage is cost-gated per tenant."]},{title:"Data protection and privacy",points:["Customer data stays within the customer's tenant.","Configurable data retention and legal holds.","Demo-request data is used only to respond to the request; see the privacy policy."]},{title:"Compliance approach",points:["ARGUS ONE is not yet independently certified against SOC 2 or ISO 27001.","Controls are designed with those frameworks in mind; security documentation and the certification roadmap are shared under NDA.","The platform itself helps customers map controls to NIST AI RMF, EU AI Act, ISO 42001 and SOC 2 — that is a product capability, not a claim about our own certification."]}],Cn=[{label:"Platform",href:"/product"},{label:"Modules",href:"/product#modules",menu:!0},{label:"Use Cases",href:"/use-cases"},{label:"Pricing",href:"/pricing"},{label:"Resources",href:"/resources"}],dd=[{title:"Products",links:[{label:"Platform 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