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470 security tests for AI agent systems - MCP, A2A, L402, x402 wire-protocol testing, decision governance, AIUC-1 compliance, NIST AI 800-2 aligned

Project description

Agent Security Harness

SafeSkill 85/100 PyPI version Python 3.10+ Apache 2.0 License Tests

Even if an agent is properly authenticated and authorized, can it still be manipulated into unsafe or policy-violating behavior?

470 executable security tests across 32 modules. MCP + A2A + L402 + x402 wire-protocol testing. Decision-layer attack scenarios. One pip install away.

$ agent-security test mcp --url http://localhost:8080/mcp
Running MCP Protocol Security Tests v4.2...
 MCP-001: Tool List Integrity Check [PASS] (0.234s)
 MCP-002: Tool Registration via Call Injection [PASS] (0.412s)
 MCP-003: Capability Escalation via Initialize [FAIL] (0.156s)
...
Results: 8/10 passed (80% pass rate) - see report.json

Quick Start

pip install agent-security-harness

# If 'agent-security' is not found, add ~/.local/bin to your PATH:
export PATH="$HOME/.local/bin:$PATH"
# See it work immediately — no server needed:
agent-security test mcp --simulate

# Then test your real MCP server:
agent-security test mcp --url http://localhost:8080/mcp

# Test an x402 payment endpoint
agent-security test x402 --url https://your-x402-endpoint.com

See docs/QUICKSTART.md for mock server setup, rate limiting, MCP server mode, and CI/CD integration.


Three Layers of Agent Decision Security

Layer What it covers Example focus
Protocol Integrity Prevent spoofing, replay, downgrade, diversion, and malformed protocol behavior MCP, A2A, L402, x402 wire-level tests
Operational Governance Validate session state, capability boundaries, platform actions, trust chains, and execution context capability escalation, facilitator trust, provenance, session security
Decision Governance Test whether an agent should act at all under its authority, confidence, scope, and policy constraints autonomy scoring, scope creep, return-channel poisoning, normalization-of-deviance

How This Differs From Other Projects

Capability Invariant MCP-Scan (2K stars) Cisco MCP Scanner (865 stars) Snyk Agent Scan (2K stars) NVIDIA Garak (7K stars) This framework
What it does Scans installed MCP configs for tool poisoning YARA + LLM-as-judge for malicious tools Scans agent configs for MCP/skill security LLM model vulnerability testing Active protocol exploitation + decision governance
Approach Static analysis Static + LLM classification Config scanning Model-layer probing Wire-protocol adversarial testing
MCP coverage Tool descriptions, config files Tool descriptions, YARA rules Config files - 18 tests: real JSON-RPC 2.0 attacks
A2A coverage - - - - 13 tests
L402/x402 coverage - - - - 85 tests
Enterprise platforms - - - - 25 cloud + 20 enterprise
APT simulation - - - - GTG-1002 (17 tests)
Jailbreak/over-refusal - - - Yes 50 tests (25 + 25 FPR)
AIUC-1 certification - - - - Maps to 19 of 20 testable requirements
Research backing - Cisco blog - Papers 5 DOIs + 3 NIST submissions
MCP server mode - - - - Yes - invoke from any AI agent
Statistical testing - - - - Wilson CIs, multi-trial
Total tests Pattern matching YARA rules Config checks Model probes 470 active tests

Use both. Scan with Invariant MCP-Scan or Cisco MCP Scanner for static analysis. Test with this framework for active exploitation. They're complementary layers.


Research

Five peer-reviewed preprints and three NIST submissions underpin the methodology:

Publication DOI
Constitutional Self-Governance for Autonomous AI Agents — 12 governance mechanisms, 77 days production data, 56 agents 10.5281/zenodo.19162104
Detecting Normalization of Deviance in Multi-Agent Systems — First empirical demonstration that automated harnesses detect behavioral drift 10.5281/zenodo.19195516
Decision Load Index (DLI): A Quantitative Framework for Agent Autonomy Risk — Measuring cognitive burden of AI agent oversight 10.5281/zenodo.18217577
Normalization of Deviance in Autonomous Agent Systems — Foundational research on behavioral drift patterns 10.5281/zenodo.15105866
Cognitive Style Governance for Multi-Agent Deployments — Governance mechanisms for managing cognitive style across multi-agent systems 10.5281/zenodo.15106553

Related Projects

Constitutional Governance (WHY layer)

The constitutional-agent package provides the governance gates and hard constraints that complement this test harness. Six gates, 12 hard constraints, amendment protocol — enforced in code, not YAML policy files. pip install constitutional-agent.


Documentation

Resource Link
Expanded Quick Start docs/QUICKSTART.md
Full Test Inventory (470 tests) docs/TEST-INVENTORY.md
AIUC-1 Crosswalk docs/AIUC1-CROSSWALK.md
Advanced Capabilities docs/ADVANCED.md
MCP Server docs/mcp-server.md
CI/CD GitHub Action docs/github-action.md
Payment Attack Taxonomy docs/PAYMENT-ATTACK-TAXONOMY.md
Comparison (detailed) docs/COMPARISON.md
Privacy & Telemetry docs/PRIVACY.md

Roadmap

v3.10 -- Prove It to Auditors ✅ Shipped. v4.1 -- Compliance Evidence ✅ Shipped. v4.2 -- Incident-Tested ✅ Shipped. v4.3 -- Supply Chain + Corpus ✅ Shipped. 470 tests, 32 modules, SSP harness (8 tests), Decision Behavior Benchmark corpus (52 cases), HIDDEN_INSTRUCTION_PATTERN DRY extraction, dynamic test count, P0 bug fixes. v5.0 -- Lock the Category (H2 2026): benchmark corpus, schema standardization, longitudinal registry. Full details in ROADMAP.md.


Used By

Who Use Case
FransDevelopment / Open Agent Trust Registry OATR SDK v1.2.0 test fixtures (X4-021 through X4-030) -- Ed25519 attestation verification

Using the harness? Open a PR to add yourself, or tag us in your project.


Contributing

See CONTRIBUTING.md for guidelines, SECURITY_POLICY.md for security policy, and CONTRIBUTION_REVIEW_CHECKLIST.md for the PR checklist.

License

Apache License 2.0 -- see LICENSE.

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