{
 "public_id": "AIR-2026-0065",
 "incident_id": "2026-02-codewall-agent-mckinsey-lilli",
 "date_disclosed": "2026-03-09",
 "date_occurred": "2026-02-28",
 "title": "An autonomous pentest agent selected McKinsey's Lilli AI platform as a target and gained read/write production access",
 "class": "responsible_disclosure",
 "attack_surface": "enterprise_assistant",
 "initial_vector": "autonomous_vulnerability_discovery",
 "agent_capability_abused": [
  "autonomous_target_selection",
  "exploitation",
  "database_read_write"
 ],
 "target_product": "McKinsey Lilli",
 "target_vendor": "McKinsey & Company",
 "autonomy_level": "fully_autonomous",
 "impact_realized": false,
 "impact_type": [
  "data_exposure",
  "system_prompt_exposure"
 ],
 "blast_radius": "3.68 million RAG document chunks, internal chat messages, user accounts and system prompts for a 43,000-employee platform",
 "cve": [],
 "taxonomy": {
  "owasp_asi": [
   "ASI02"
  ],
  "mitre_atlas": [],
  "labels": [
   "agent_as_attacker",
   "autonomous_target_selection",
   "rag_store_exposure",
   "system_prompt_leak"
  ]
 },
 "defense_present": "McKinsey platform access controls",
 "defense_bypassed": true,
 "fix_shipped": "McKinsey confirmed and fixed the vulnerability within hours",
 "primary_sources": [
  "https://codewall.ai/blog/how-we-hacked-mckinseys-ai-platform",
  "https://incidentdatabase.ai/cite/1412"
 ],
 "verified_quote": "As part of our research preview, the CodeWall research agent autonomously suggested McKinsey as a target citing their public responsible diclosure policy (to keep within guardrails) and recent updates to their Lilli platform.",
 "confidence": "high",
 "notes": "AI Incident Database incident 1412. Two agentic angles at once: an autonomous agent chose and attacked a target, and the victim was itself an enterprise AI assistant. McKinsey says no client data was accessed. Vendor-published research, so treat scope claims with the usual caution.",
 "risk_category": "privacy",
 "risk_secondary": [],
 "risk_subcategory": "System Prompt Extraction",
 "risk_sub_secondary": [],
 "ai_entity": "generative",
 "agency": "agent_acted",
 "agency_debatable": false,
 "agency_reason": "the pentest agent chose the target and gained read/write production access",
 "vector_family": "other",
 "vector_detail": "autonomous_vulnerability_discovery",
 "guardrail_kind": [
  "unknown"
 ],
 "guardrail_outcome": "silent",
 "xrefs": {
  "aiid": [
   1412
  ],
  "atlas": [],
  "cve": [],
  "ghsa": []
 },
 "primary_asi": "ASI02",
 "agent_framework": "unknown",
 "model_provider": "unknown",
 "model_name": "",
 "detection_mechanism": "unknown",
 "tool_access": "unknown",
 "financial_loss_band": "unknown",
 "eai_category": "sensitive_data_exposure",
 "eai_domain": "privacy",
 "eai_secondary": [],
 "eai_reason": "subcategory: System Prompt Extraction",
 "asi_curated": [],
 "asi_scope": "in_scope",
 "asi_provenance": "rule",
 "asi_reason": "ASI02 (impact=tool_misuse)",
 "submitted_by": "EAI Internal"
}