/agent-attack-surface
When to Use
- Threat modelling a new LLM agent feature
- Security review before giving agent internet/file/tool access
- "What's the blast radius if this agent is compromised?"
- Designing trust boundaries between multiple agents
Do NOT use for
- Single-turn chatbots with no tool use
- Internal-only LLM use with no external data ingestion
Agent Attack Surface Model
┌─────────────────────────────────┐
EXTERNAL │ Untrusted Input Zone │
ATTACKERS ─────▶│ - user input │
│ - fetched URLs / files │ [ENTRY POINTS]
│ - tool results │
│ - other agents' output │
└──────────────┬──────────────────┘
│ ← Injection boundary (LLM01, LLM07)
┌──────────────▼──────────────────┐
│ Agent Context Window │
│ - system prompt │ [TRUST CORE]
│ - tool call history │
│ - memory (L1/L2) │
└──────────────┬──────────────────┘
│ ← Agency boundary (LLM08)
┌──────────────▼──────────────────┐
PRODUCTION ◀─────│ Action Zone │
SYSTEMS │ - file writes │ [BLAST RADIUS]
│ - API calls / deploys │
│ - sub-agent spawns │
│ - memory writes │
└─────────────────────────────────┘
Entry Point Classification
HIGH RISK — always scan with prompt-jailbreak-guard + tool-poisoning-guard:
- User-submitted text (free-form)
- Content fetched via WebFetch / URL retrieval
- File content read from untrusted paths
- Tool result from MCP server not in mcp-whitelist.json
- Other agent's output (agent-to-agent channel)
MEDIUM RISK — validate structure:
- Structured API response (validate schema strictly)
- Database query result (parameterized only, LLM02 output law)
- GitHub PR/Issue content (can contain injection in description)
LOW RISK — treat as trusted:
- Hardcoded system prompt in vault / env var
- Output of local deterministic tools (git status, ls)
- Pre-vetted agent tool schemas (validated at registration)
Blast Radius Scoring
Score each agent action from 0–5 before execution:
+1 Modifies files outside current task directory
+1 Makes network call to external endpoint
+1 Spawns sub-agent or delegates to another agent
+1 Action is irreversible (no git revert path)
+1 Action touches credentials, secrets, or PII
Score 0–1 = proceed
Score 2–3 = log + surface to human
Score 4–5 = block, require YAMTAM_IRREVERSIBLE_OK=1 + human acknowledgement
MITRE ATLAS Techniques for Agent Systems
AML.T0051 LLM Prompt Injection
→ Defense: prompt-jailbreak-guard.md, LLM01 separation
AML.T0054 LLM Jailbreak
→ Defense: system prompt hardening, refusal training eval
AML.T0057 LLM Plugin Compromise
→ Defense: agent-tool-poisoning-guard.md, mcp-whitelist.json
AML.T0040 ML Supply Chain Compromise
→ Defense: slsa-artifact-law.md, dependency-vetting-law.md
AML.T0043 Craft Adversarial Data
→ Defense: fuzz-testing-constraints.md, adversarial-prompt-testing skill
AML.T0048 Exfiltration via LLM API
→ Defense: secure-logger.sh --scan-egress, network-egress monitoring
Trust Boundary Rules
Rule 1: External data → agent context boundary
ALL external data must pass injection scan before entering context window.
Rule 2: Agent context → action boundary
Agent cannot take Tier X/P actions without scope declaration + human gate.
Rule 3: Agent → sub-agent boundary
Sub-agent inherits parent scope minus one tier (Tier P parent → Tier X child).
Sub-agent cannot escalate permissions beyond what parent holds.
Rule 4: Agent → memory boundary
Only REVIEWED facts (score ≥ 2/5 rubric) enter L1 memory.
Untrusted external content never enters L1 directly.
Anti-Fake-Pass Checklist
❌ Entry point classified LOW RISK because "users are trusted" (insider threat)
❌ Blast radius calculation skipped because action "seems safe"
❌ Sub-agent granted same permissions as root agent (no tier reduction)
❌ MITRE ATLAS threat model not updated when new tool/MCP server added
❌ External URL content added to agent memory without injection scan
❌ Trust boundary diagram not updated when new agent-to-agent channel added
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