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

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:

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