← offensive-ai-security (Claude-Red)
offensive-ai-security (Claude-Red) — agentic threat model
This agent acts as an offensive security testing assistant focused on prompt injection and jailbreaks; while its knowledge base is highly specialized for exploitation, its risk posture is primarily advisory as it guides adversarial crafting rather than executing automated, multi-step cyberattacks independently.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.30 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.50 | |
| 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.
Directly targets this layer by generating adversarial prompt-injection and jailbreak payloads designed to bypass alignment and safety guardrails of target foundation models.
Not certain from the listing — likely relies on static, pre-loaded knowledge from the author's offensive-checklist (ai.md) rather than dynamic RAG or vector store operations, though it may advise on how to exploit target RAG systems.
Focuses on identifying and exploiting vulnerabilities in target agent frameworks (such as insecure tool integration and model abuse), but does not appear to possess complex internal orchestration or tool-calling capabilities of its own.
Not certain from the listing — the agent is described as an offensive skill/guide, suggesting it runs within a standard, non-sandboxed chat interface without direct infrastructure access or execution environments.
Not certain from the listing — there are no mentioned built-in evaluation, logging, or guardrail mechanisms to prevent the agent itself from being abused or to monitor its output for malicious payload generation.
Not certain from the listing — lacks explicit compliance controls, access policies, or safety filters, which is typical for open-source offensive security tools designed for penetration testing.
Not certain from the listing — does not indicate multi-agent coordination or marketplace integration, operating primarily as a standalone conversational assistant.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).