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security-and-hardening (addyosmani/agent-skills) — agentic threat model

8.2AIVSS 8.2 · High

This agent presents a moderate-to-high risk profile because it directly edits source code to remediate vulnerabilities, meaning a compromise or prompt injection could lead to the introduction of backdoors or malicious code into the software supply chain.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 7.3AARS uplift 1.3Factor sum 4.6/10Threat ×1.05Mitigation ×0.95
Autonomy of Action
0.60
Goal-Driven Planning
0.50
Self-Modification
0.20
Dynamic Tool Use
0.70
Persistent Memory
0.30
Contextual Awareness
0.60
Dynamic Identity
0.10
Multi-Agent Interactions
0.40
Non-Determinism
0.70
Opacity & Reflexivity
0.50

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.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — relies on an unspecified underlying foundation model from the user's environment. The primary threat is indirect prompt injection via the source code files it is tasked with reviewing, which could reprogram the model to ignore vulnerabilities or inject malicious code.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — the data operations layer is limited to reading local source code files and repository structures. There is no explicit mention of vector databases or RAG, but poisoning of the codebase being analyzed is a direct threat to the agent's output.

L3 · Agent Frameworks✓ mapped

The agent framework orchestrates file reading and writing tools to analyze and edit source code. Insecure tool integration is a major threat here; if the tool execution environment lacks strict boundaries, the agent could be manipulated into modifying arbitrary files outside the target codebase.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — as an open-source skill from a pack, deployment and sandboxing are entirely dependent on the host developer's local environment or CI/CD pipeline. If run without containerization, a compromised agent could escalate privileges on the host system.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — there are no built-in evaluation, logging, or guardrail mechanisms described. The lack of observability means unauthorized code modifications or silent failures during the hardening process might go unnoticed without manual git diff reviews.

L6 · Security & Compliance (cross-cutting)⚠ not certain from listing

Not certain from the listing — no built-in identity, authorization, or compliance policies are mentioned. It operates with the permissions of the local user running the agent-skills pack, lacking fine-grained access controls over which files it can modify.

L7 · Agent Ecosystem✓ mapped

The agent is designed as a modular skill within the 'addyosmani engineering pack'. It is highly susceptible to cascading failures or trust abuse if chained with other automated agents (e.g., an agent that automatically commits and pushes its code changes to a repository without human-in-the-loop approval).

MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).