audit-project — agentic threat model
The audit-project agent presents a moderate-to-high risk profile primarily due to its access to sensitive source code and dependency configurations, making it a prime target for indirect prompt injection and source code exfiltration.
OWASP AIVSS score rationale
| Autonomy of Action | 0.30 | |
| Goal-Driven Planning | 0.40 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.50 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.40 | |
| Opacity & Reflexivity | 0.30 |
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 underlying LLM is not specified, but it is vulnerable to indirect prompt injection via malicious code comments or repository files designed to hijack the audit process.
The agent ingests repository code, dependency trees, and configuration files. Threats include data exfiltration of proprietary source code and poisoning of the audit results via malicious dependency definitions.
Not certain from the listing — the orchestration framework is unspecified. However, insecure tool integration could allow arbitrary code execution if the agent attempts to run untrusted setup scripts or dependency resolution tools during the audit.
Not certain from the listing — deployment context (local CLI, CI/CD runner, or cloud service) is unspecified. If run in an unsandboxed CI/CD environment, a compromised agent could lead to host compromise or secret exposure.
Not certain from the listing — there is no mention of built-in guardrails, logging, or evaluation frameworks to detect drift, hallucinated vulnerabilities, or malicious prompt injections.
Not certain from the listing — access control and compliance policies depend entirely on the host environment (e.g., GitHub Actions permissions). There are no native identity or authorization controls described.
Not certain from the listing — the agent operates as a standalone plugin or tool, with no described multi-agent interactions or marketplace dependencies, minimizing ecosystem-specific cascading risks.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).