Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add hypnguyen1209/offensive-claude --skill ai-agent-redteamgit clone --depth 1 https://github.com/hypnguyen1209/offensive-claudeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hypnguyen1209/offensive-claude/ai-agent-redteam)<a href="https://agentmods.dev/skills/hypnguyen1209/offensive-claude/ai-agent-redteam"><img src="https://agentmods.dev/badge/skills/hypnguyen1209/offensive-claude/ai-agent-redteam/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hypnguyen1209/offensive-claude/ai-agent-redteam"><img src="https://agentmods.dev/badge/skills/hypnguyen1209/offensive-claude/ai-agent-redteam.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Server-Side Request Forgery · line 85 Code accesses a cloud instance metadata endpoint (e.g. 169.254.169.254). A single request can return temporary IAM credentials, making this a high-value SSRF target for credential theft.Fix: Remove access to cloud metadata endpoints unless strictly required. If metadata is needed, restrict it (e.g. IMDSv2 with hop limit) and never expose returned credentials.
- high Server-Side Request Forgery · line 102 Code accesses a cloud instance metadata endpoint (e.g. 169.254.169.254). A single request can return temporary IAM credentials, making this a high-value SSRF target for credential theft.Fix: Remove access to cloud metadata endpoints unless strictly required. If metadata is needed, restrict it (e.g. IMDSv2 with hop limit) and never expose returned credentials.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00055 | $0.02281 |
| Opus 5 | $0.00028 | $0.01141 |
| Sonnet 5 | $0.00011 | $0.00456 |
| Haiku 4.5 | $0.00006 | $0.00228 |
Grade B, and why
ai-agent-redteam scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Cloud metadata endpointmediumServer-side request forgery
One request to 169.254.169.254 can return temporary IAM credentials.
python scripts/agency_tool_fuzzer.py --endpoint $AGENT_URL --tools surface.json --ssrf-canary http://169.254.169.254/ Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
How it starts
The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Agent Red Teaming
Offensive testing of autonomous LLM agents — systems that combine model reasoning with
tools, memory, retrieval, and multi-step planning. This is distinct from model-level testing
(see ai-security): the attack surface here is the agentic pipeline — untrusted data channels,
tool/MCP integrations, persistent memory, and delegated authority. Assumes authorized engagement.
When to Activate
- Pentesting an LLM agent with tool/function-calling, an MCP client, or a code interpreter
- Testing RAG / email / browser assistants for indirect or zero-click prompt injection
- Auditing MCP server integrations for tool poisoning, rug-pull, or line-jumping
- Assessing persistent memory / long-term context for poisoning and belief drift
- Evaluating excessive agency: confused-deputy, SSRF/RCE-via-tool, over-privileged actions
- Running automated jailbreak campaigns (PAIR/TAP/Crescendo/Best-of-N) and measuring ASR
- Standing up a repeatable PyRIT/Garak/Promptfoo harness mapped to OWASP Agentic Top 10 / ATLAS
Technique Map
| Technique | ATT&CK | CWE | Reference | Script |
|---|---|---|---|---|
| Indirect / zero-click prompt injection (EchoLeak-class) | T1566.002 / AML.T0051.001 | CWE-1427 | references/indirect-prompt-injection.md | scripts/indirect_injection_forge.py |
| RAG corpus poisoning & markdown/image exfiltration | T1567 / AML.T0070 | CWE-1426 | references/indirect-prompt-injection.md | scripts/indirect_injection_forge.py |
| Browser-agent hijack (Comet/CometJacking, Atlas) | T1071.001 / AML.T0051 | CWE-1427 | references/indirect-prompt-injection.md | scripts/indirect_injection_forge.py |
| MCP tool poisoning / line-jumping | T1059 / AML.T0053 | CWE-1427 | references/mcp-tool-poisoning.md | scripts/mcp_tool_poison_server.py |
| MCP rug-pull (silent redefinition) | T1554 / AML.T0010 | CWE-494 | references/mcp-tool-poisoning.md | scripts/mcp_tool_poison_server.py |
| Persistent memory poisoning (MINJA/MemoryGraft) | T1565.001 / AML.T0070 | CWE-349 | references/memory-context-poisoning.md | scripts/memory_poison_minja.py |
| Excessive agency / confused-deputy tool abuse | T1548 / AML.T0053 | CWE-862 | references/excessive-agency-tool-abuse.md | scripts/agency_tool_fuzzer.py |
| Tool output → SSRF / RCE chaining | T1059 / AML.T0054 | CWE-918 / CWE-94 | references/excessive-agency-tool-abuse.md | scripts/agency_tool_fuzzer.py |
| Automated multi-turn jailbreak (Crescendo/TAP/PAIR) | AML.T0054 / AML.T0071 | CWE-1426 | references/automated-jailbreak-multiturn.md | scripts/multiturn_jailbreak.py |
| Best-of-N / encoding obfuscation jailbreak | AML.T0054 | CWE-1426 | references/automated-jailbreak-multiturn.md | scripts/multiturn_jailbreak.py |
| Harness & ASR scoring (PyRIT/Garak/Promptfoo) | AML.T0071 | CWE-1426 | references/agent-redteam-tooling.md | scripts/agent_redteam_harness.py |
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/agent-redteam-tooling.md 7.7 KB
- references/automated-jailbreak-multiturn.md 7.3 KB
- references/excessive-agency-tool-abuse.md 7.9 KB
- references/indirect-prompt-injection.md 9.2 KB
- references/mcp-tool-poisoning.md 8.0 KB
- references/memory-context-poisoning.md 8.1 KB
- scripts/agency_tool_fuzzer.py 6.6 KB runs code
- scripts/agent_redteam_harness.py 11 KB runs code
- scripts/indirect_injection_forge.py 7.3 KB runs code
- scripts/mcp_tool_poison_server.py 6.6 KB runs code
- scripts/memory_poison_minja.py 6.2 KB runs code
- scripts/multiturn_jailbreak.py 9.9 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 113 lines · 55 tokens per session scan B 899b65bebdc3
ai-agent-redteam is a skill published in the GitHub repository hypnguyen1209/offensive-claude (357 stars, last pushed 25d ago), licensed MIT. It adds 55 tokens to every session and 2,281 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 1 finding (cloud metadata endpoint). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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