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test-driven-development — agentic threat model

8.1AIVSS 8.1 · High

This agent skill enforces a strict TDD loop but lacks built-in sandboxing or execution guards, presenting a high risk of arbitrary code execution if the underlying agent runs generated tests in an unsecure environment.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 7.5AARS uplift 0.62Factor sum 2.5/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.30
Goal-Driven Planning
0.50
Self-Modification
0.10
Dynamic Tool Use
0.40
Persistent Memory
0.10
Contextual Awareness
0.30
Dynamic Identity
0.00
Multi-Agent Interactions
0.10
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.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — The skill is an instruction-only surface, meaning it relies entirely on an underlying foundation model. If that model is susceptible to prompt injection or jailbreaking, the TDD mandate can be bypassed or manipulated.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — There is no mention of data operations, RAG, or vector stores. However, if the agent accesses a codebase, poisoned source files or malicious test inputs could exploit the code-generation process.

L3 · Agent Frameworks✓ mapped

The framework orchestrates a strict red-green-refactor planning loop. Vulnerabilities include framework-level bypasses where prompt injection overrides the 'watch-it-fail' mandate, or insecure tool integration when executing the generated tests.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — The skill dictates the logic but not the execution environment. If the host agent runs the 'watch-it-fail' verification tests outside of a secure sandbox, it risks remote code execution (RCE) from generated malicious code.

L5 · Evaluation & Observability✓ mapped

The core mechanism relies on 'watch-it-fail' verification as an evaluation metric. A major threat is evaluation gaming, where the agent writes trivial, self-passing, or mocked tests to satisfy the loop without implementing actual secure logic.

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

Not certain from the listing — Being a free, open-source instruction-only skill, there are no built-in identity, authorization, or compliance controls defined at this layer.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — No multi-agent interactions are specified, though if integrated into a larger development ecosystem, a compromised TDD agent could propagate malicious code to downstream deployment agents.

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