signed-audit-trails-recipe — agentic threat model
This agent is a low-risk educational skill focused on demonstrating secure audit trails and policy enforcement. Its primary risk is limited to the potential for misguiding developers if the recipe itself contains implementation flaws.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.30 | |
| Dynamic Identity | 0.40 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.20 | |
| Opacity & Reflexivity | 0.20 |
Scored with the canonical OWASP AIVSS formula (AIVSS calculator reference); agentic risk factors estimated from the agent’s described capabilities.
MAESTRO 7-layer threat model
Per-layer threats for this agent. Layers tagged “not certain from listing” are general, caveated commentary where the public description didn’t pin that layer.
Not certain from the listing — The recipe is model-agnostic but references Claude Code tool calls. It does not directly address foundation model vulnerabilities like adversarial prompt injection, though the cryptographic signatures help verify that the output was indeed generated and signed by an authorized agent session.
Not certain from the listing — There is no explicit RAG or vector database mentioned. However, the recipe addresses data integrity and lineage/provenance gaps directly by using JCS-canonical, hash-chained Ed25519 receipts to prevent tampering of the audit trail.
Focuses heavily on securing the agent framework layer by demonstrating Cedar policy evaluation before tool execution. This directly mitigates tool misuse and insecure tool integration by enforcing authorization policies on Claude Code tool calls.
Not certain from the listing — The recipe integrates with CI/CD and SLSA composition, implying deployment-time verification. However, the actual sandboxing or hosting infrastructure of the agent executing the recipe is not specified.
Directly addresses observability and logging by providing a walkthrough for tamper detection, offline verification, and cryptographically signed audit trails, eliminating common logging blind spots and preventing log alteration.
Strongly aligned with security and compliance. It implements decentralized identity/authorization concepts via Cedar policies and Ed25519 signatures, directly supporting compliance frameworks requiring non-repudiation and strict auditability.
Not certain from the listing — While it mentions being a companion to the protect-mcp runtime plugin, it does not explicitly detail multi-agent orchestration or address cascading failures in complex agent-to-agent ecosystems.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).