awesome-copilot/skills/agent-owasp-compliance/SKILL.md

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agent-owasp-compliance

Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"

Agent OWASP ASI Compliance Check

Evaluate AI agent systems against the OWASP Agentic Security Initiative (ASI) Top 10 — the industry standard for agent security posture.

Overview

The OWASP ASI Top 10 defines the critical security risks specific to autonomous AI agents — not LLMs, not chatbots, but agents that call tools, access systems, and act on behalf of users. This skill checks whether your agent implementation addresses each risk.

Codebase → Scan for each ASI control:
  ASI-01: Prompt Injection Protection
  ASI-02: Tool Use Governance
  ASI-03: Agency Boundaries
  ASI-04: Escalation Controls
  ASI-05: Trust Boundary Enforcement
  ASI-06: Logging & Audit
  ASI-07: Identity Management
  ASI-08: Policy Integrity
  ASI-09: Supply Chain Verification
  ASI-10: Behavioral Monitoring
→ Generate Compliance Report (X/10 covered)

The 10 Risks

Risk	Name	What to Look For
ASI-01	Prompt Injection	Input validation before tool calls, not just LLM output filtering
ASI-02	Insecure Tool Use	Tool allowlists, argument validation, no raw shell execution
ASI-03	Excessive Agency	Capability boundaries, scope limits, principle of least privilege
ASI-04	Unauthorized Escalation	Privilege checks before sensitive operations, no self-promotion
ASI-05	Trust Boundary Violation	Trust verification between agents, signed credentials, no blind trust
ASI-06	Insufficient Logging	Structured audit trail for all tool calls, tamper-evident logs
ASI-07	Insecure Identity	Cryptographic agent identity, not just string names
ASI-08	Policy Bypass	Deterministic policy enforcement, no LLM-based permission checks
ASI-09	Supply Chain Integrity	Signed plugins/tools, integrity verification, dependency auditing
ASI-10	Behavioral Anomaly	Drift detection, circuit breakers, kill switch capability

---

Check ASI-01: Prompt Injection Protection

Look for input validation that runs before tool execution, not after LLM generation.

import re
from pathlib import Path

def check_asi_01(project_path: str) -> dict:
    """ASI-01: Is user input validated before reaching tool execution?"""
    positive_patterns = [
        "input_validation", "validate_input", "sanitize",
        "classify_intent", "prompt_injection", "threat_detect",
        "PolicyEvaluator", "PolicyEngine", "check_content",
    ]
    negative_patterns = [
        r"eval\(", r"exec\(", r"subprocess\.run\(.*shell=True",
        r"os\.system\(",
    ]

    # Scan Python files for signals
    root = Path(project_path)
    positive_matches = []
    negative_matches = []

    for py_file in root.rglob("*.py"):
        content = py_file.read_text(errors="ignore")
        for pattern in positive_patterns:
            if pattern in content:
                positive_matches.append(f"{py_file.name}: {pattern}")
        for pattern in negative_patterns:
            if re.search(pattern, content):
                negative_matches.append(f"{py_file.name}: {pattern}")

    positive_found = len(positive_matches) > 0
    negative_found = len(negative_matches) > 0

    return {
        "risk": "ASI-01",
        "name": "Prompt Injection",
        "status": "pass" if positive_found and not negative_found else "fail",
        "controls_found": positive_matches,
        "vulnerabilities": negative_matches,
        "recommendation": "Add input validation before tool execution, not just output filtering"
    }

What passing looks like:

# GOOD: Validate before tool execution
result = policy_engine.evaluate(user_input)
if result.action == "deny":
    return "Request blocked by policy"
tool_result = await execute_tool(validated_input)

What failing looks like:

# BAD: User input goes directly to tool
tool_result = await execute_tool(user_input)  # No validation

---

Check ASI-02: Insecure Tool Use

Verify tools have allowlists, argument validation, and no unrestricted execution.

What to search for:

• Tool registration with explicit allowlists (not open-ended)
• Argument validation before tool execution
• No subprocess.run(shell=True) with user-controlled input
• No eval() or exec() on agent-generated code without sandbox

Passing example:

ALLOWED_TOOLS = {"search", "read_file", "create_ticket"}

def execute_tool(name: str, args: dict):
    if name not in ALLOWED_TOOLS:
        raise PermissionError(f"Tool '{name}' not in allowlist")
    # validate args...
    return tools[name](**validated_args)

---

Check ASI-03: Excessive Agency

Verify agent capabilities are bounded — not open-ended.

What to search for:

• Explicit capability lists or execution rings
• Scope limits on what the agent can access
• Principle of least privilege applied to tool access

Failing: Agent has access to all tools by default. Passing: Agent capabilities defined as a fixed allowlist, unknown tools denied.

---

Check ASI-04: Unauthorized Escalation

Verify agents cannot promote their own privileges.

What to search for:

• Privilege level checks before sensitive operations
• No self-promotion patterns (agent changing its own trust score or role)
• Escalation requires external attestation (human or SRE witness)

Failing: Agent can modify its own configuration or permissions. Passing: Privilege changes require out-of-band approval (e.g., Ring 0 requires SRE attestation).

---

Check ASI-05: Trust Boundary Violation

In multi-agent systems, verify that agents verify each other's identity before accepting instructions.

What to search for:

• Agent identity verification (DIDs, signed tokens, API keys)
• Trust score checks before accepting delegated tasks
• No blind trust of inter-agent messages
• Delegation narrowing (child scope <= parent scope)

Passing example:

def accept_task(sender_id: str, task: dict):
    trust = trust_registry.get_trust(sender_id)
    if not trust.meets_threshold(0.7):
        raise PermissionError(f"Agent {sender_id} trust too low: {trust.current()}")
    if not verify_signature(task, sender_id):
        raise SecurityError("Task signature verification failed")
    return process_task(task)

---

Check ASI-06: Insufficient Logging

Verify all agent actions produce structured, tamper-evident audit entries.

What to search for:

• Structured logging for every tool call (not just print statements)
• Audit entries include: timestamp, agent ID, tool name, args, result, policy decision
• Append-only or hash-chained log format
• Logs stored separately from agent-writable directories

Failing: Agent actions logged via print() or not logged at all. Passing: Structured JSONL audit trail with chain hashes, exported to secure storage.

---

Check ASI-07: Insecure Identity

Verify agents have cryptographic identity, not just string names.

Failing indicators:

• Agent identified by agent_name = "my-agent" (string only)
• No authentication between agents
• Shared credentials across agents

Passing indicators:

• DID-based identity (did:web:, did:key:)
• Ed25519 or similar cryptographic signing
• Per-agent credentials with rotation
• Identity bound to specific capabilities

---

Check ASI-08: Policy Bypass

Verify policy enforcement is deterministic — not LLM-based.

What to search for:

• Policy evaluation uses deterministic logic (YAML rules, code predicates)
• No LLM calls in the enforcement path
• Policy checks cannot be skipped or overridden by the agent
• Fail-closed behavior (if policy check errors, action is denied)

Failing: Agent decides its own permissions via prompt ("Am I allowed to...?"). Passing: PolicyEvaluator.evaluate() returns allow/deny in <0.1ms, no LLM involved.

---

Check ASI-09: Supply Chain Integrity

Verify agent plugins and tools have integrity verification.

What to search for:

• INTEGRITY.json or manifest files with SHA-256 hashes
• Signature verification on plugin installation
• Dependency pinning (no @latest, >= without upper bound)
• SBOM generation

---

Check ASI-10: Behavioral Anomaly

Verify the system can detect and respond to agent behavioral drift.

What to search for:

• Circuit breakers that trip on repeated failures
• Trust score decay over time (temporal decay)
• Kill switch or emergency stop capability
• Anomaly detection on tool call patterns (frequency, targets, timing)

Failing: No mechanism to stop a misbehaving agent automatically. Passing: Circuit breaker trips after N failures, trust decays without activity, kill switch available.

---

Compliance Report Format

# OWASP ASI Compliance Report
Generated: 2026-04-01
Project: my-agent-system

## Summary: 7/10 Controls Covered

| Risk | Status | Finding |
|------|--------|---------|
| ASI-01 Prompt Injection | PASS | PolicyEngine validates input before tool calls |
| ASI-02 Insecure Tool Use | PASS | Tool allowlist enforced in governance.py |
| ASI-03 Excessive Agency | PASS | Execution rings limit capabilities |
| ASI-04 Unauthorized Escalation | PASS | Ring promotion requires attestation |
| ASI-05 Trust Boundary | FAIL | No identity verification between agents |
| ASI-06 Insufficient Logging | PASS | AuditChain with SHA-256 chain hashes |
| ASI-07 Insecure Identity | FAIL | Agents use string names, no crypto identity |
| ASI-08 Policy Bypass | PASS | Deterministic PolicyEvaluator, no LLM in path |
| ASI-09 Supply Chain | FAIL | No integrity manifests or plugin signing |
| ASI-10 Behavioral Anomaly | PASS | Circuit breakers and trust decay active |

## Critical Gaps
- ASI-05: Add agent identity verification using DIDs or signed tokens
- ASI-07: Replace string agent names with cryptographic identity
- ASI-09: Generate INTEGRITY.json manifests for all plugins

## Recommendation
Install agent-governance-toolkit for reference implementations of all 10 controls:
pip install agent-governance-toolkit

---

Quick Assessment Questions

Use these to rapidly assess an agent system:

1. Does user input pass through validation before reaching any tool? (ASI-01)
2. Is there an explicit list of what tools the agent can call? (ASI-02)
3. Can the agent do anything, or are its capabilities bounded? (ASI-03)
4. Can the agent promote its own privileges? (ASI-04)
5. Do agents verify each other's identity before accepting tasks? (ASI-05)
6. Is every tool call logged with enough detail to replay it? (ASI-06)
7. Does each agent have a unique cryptographic identity? (ASI-07)
8. Is policy enforcement deterministic (not LLM-based)? (ASI-08)
9. Are plugins/tools integrity-verified before use? (ASI-09)
10. Is there a circuit breaker or kill switch? (ASI-10)

If you answer "no" to any of these, that's a gap to address.

---

Related Resources

• OWASP Agentic AI Threats
• Agent Governance Toolkit — Reference implementation covering 10/10 ASI controls
• agent-governance skill — Governance patterns for agent systems