{
 "license": "CC-BY-4.0",
 "attribution": "Fide AI, Agentic Cyber Explorer",
 "url": "https://agentic-cyber-explorer.pages.dev/findings/architectural-isolation-bounds-injection/",
 "asOf": "2026-09-26",
 "id": "architectural-isolation-bounds-injection",
 "claim": "Separating an agent's control flow from untrusted data can give provable protection against control-flow hijacking at a modest utility cost.",
 "evidenceKind": "measured",
 "scope": "One design (CaMeL) on AgentDojo; does not stop manipulation within permitted data flows, and has not been independently attacked at scale.",
 "topics": [
  "prompt-injection"
 ],
 "atlas": [
  "untrusted-content",
  "tools"
 ],
 "evidence": [
  {
   "event": "deepmind-camel-2025",
   "note": "Solved 77% of AgentDojo tasks with provable security; about 7 points below an undefended agent."
  }
 ],
 "relations": [],
 "statusHistory": [
  {
   "status": "reported",
   "on": "2025-03-24",
   "why": "Google DeepMind introduces CaMeL.",
   "event": "deepmind-camel-2025",
   "kind": "evidence"
  }
 ],
 "halfLifeDays": 540,
 "wouldChange": "An independent adaptive evaluation of CaMeL or a successor.",
 "fideQuestions": [],
 "methods": [
  "control-data-isolation",
  "indirect-prompt-injection"
 ],
 "review": "assistant-drafted",
 "addedOn": "2026-09-25"
}