菜单
Red-team an AI agent's skill / plugin / MCP supply chain — can a poisoned skill doc, a malicious MCP server, or a dependency-confused package become persistent executable instruction? Authorized testing of agents you own or are permitted to test.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
Security-audit an AI agent's OWN framework code for classic appsec vulnerabilities the LLM can't defend — path traversal, command injection, SSRF, fail-open security controls, missing/late auth, unsafe deserialization — especially at the untrusted-input boundaries (channels, file/media handlers, config & skill loaders) that run around and before the model. The LLM layer is often hardened; the plumbing around it usually isn't. Authorized testing of agents you own or are permitted to test.
Orchestrate a static + dynamic, exploit-validated red-team of an AI agent — read the source to find candidate vulnerable paths, then run the dynamic skills to confirm or refute each one empirically. The arbiter of truth is whether the exploit works, not a model vote. Authorized testing of agents you own or are permitted to test.
The end-to-end methodology for red-teaming a specific AI agent — adaptively, exploit-validated, and honestly. Read THIS target's own code, stand up a disposable harness, and prove or refute each weakness through a real attacker-reachable entry point. This is the orchestration + discipline that makes a finding credible, not a list of payloads. Authorized testing of agents you own or are permitted to test.
Red-team an AI agent for prompt injection — does content the agent is asked to process (email, page, ticket, tool result) override its actual task? Authorized testing of agents you own or are permitted to test.
Red-team an AI agent's tools — can it be coerced (often via injection) into calling a tool it shouldn't, with attacker-influenced arguments, or into acting as a confused deputy with its own privileges? Authorized testing of agents you own or are permitted to test.
Red-team an AI agent's tool-execution isolation — do tools run un-sandboxed on the host, and does the sandbox silently disable itself when a dependency is missing? Authorized testing of agents you own or are permitted to test.
基于 SOC 职业分类
| name | rt7-supply-chain |
| description | Red-team an AI agent's skill / plugin / MCP supply chain — can a poisoned skill doc, a malicious MCP server, or a dependency-confused package become persistent executable instruction? Authorized testing of agents you own or are permitted to test. |
| license | Apache-2.0 |
| tags | ["ai-agent-security","red-team","supply-chain","skills","mcp","RT-7"] |
| safety | authorized-targets-only |
Agents download and run external code and instructions — auto-created skills, community-imported skills, MCP servers, plugins, dependencies. RT-7 checks whether a poisoned item becomes trusted, persistent, executable instruction inside the agent.
Follow every rule in ../README.md. Use a benign test skill/server you author
that only prints a marker; authorized target, disposable environment, no real credentials, no
destructive payloads. Otherwise stop.
SUPPLY-PROOF-<random>.Discipline (see redteam-an-agent Phase 4): run a battery — vary framings and repeat. One hit isn't confirmed; one miss isn't refuted. Confirm via an observable effect (a marker that returns / lands on disk), not the model's own words, and report the measured rate (e.g. 5/8), never "always".
The import path, whether a signature/review gate existed, and the marker. Grade and disclose to help defenders — the finding and fix, not a weaponized payload.
Sign and pin skills; review before import; sandbox skill/plugin execution; no fetch-and-run from arbitrary URLs; pin dependencies and resolve from trusted indexes.