binary-analysis-patterns — agentic threat model
This agent skill acts as a specialized knowledge base and workflow guide for binary reverse-engineering, presenting low direct agentic risk due to its lack of active execution capabilities, though it could be leveraged to analyze or optimize malicious binaries.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.30 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.30 | |
| 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.
The skill relies on an underlying foundation model to interpret binary patterns and compiler idioms. Threats include adversarial inputs designed to bypass safety filters regarding malware analysis or to generate exploit payloads based on decompilation patterns.
Utilizes a bundled 'references/' file containing reverse-engineering patterns. Risk of local data poisoning if an attacker modifies this reference file to inject malicious analysis patterns or misleading workflow instructions.
Not certain from the listing — the skill references Ghidra, IDA Pro, and Binary Ninja workflows, but it is unclear if the agent directly executes these tools via an orchestration framework or merely provides conceptual guidance to a human operator.
Not certain from the listing — if the agent runs in an environment where it actively decompiles untrusted binaries, it requires strict sandboxing to prevent host compromise from binary-parser exploits (e.g., buffer overflows in decompilers).
Not certain from the listing — there are no mentioned logging, guardrails, or observability mechanisms to detect if the agent is being used to analyze proprietary/sensitive intellectual property or malicious code.
Not certain from the listing — no compliance frameworks, access controls, or licensing verification mechanisms are described for this open-source skill.
As an 'Agent Skill', this is designed to be integrated into other agentic workflows. The primary ecosystem risk is another agent delegating binary analysis tasks to this skill without validating the safety or origin of the target executable.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).