analyze
Analyze recon output with AI to suggest high-value targets and attack strategies. Usage: /analyze <target>
@h-mmerInstall SkillSecurity
Skill
/chain
Build deep exploit chains — dispatches chain-builder agent. Given bug A, recursively walks the chain graph. Usage: /chain (then describe bug A)
Claude Code
$ npx -y skills add H-mmer/pentest-agents --skill chain --agent claude-code
Codex
$ npx skills add H-mmer/pentest-agents --skill chain -a codex -y
Cursor
$ npx skills add H-mmer/pentest-agents --skill chain -a cursor -y
Gemini CLI
$ npx skills add H-mmer/pentest-agents --skill chain -a gemini-cli -y
GitHub Copilot
$ npx skills add H-mmer/pentest-agents --skill chain -a github-copilot -y
OpenCode
$ npx skills add H-mmer/pentest-agents --skill chain -a opencode -y
Windsurf
$ npx skills add H-mmer/pentest-agents --skill chain -a windsurf -y
SKILL.md
chain.SKILL.mdname: chain
description: "Build deep exploit chains — dispatches chain-builder agent. Given bug A, recursively walks the chain graph. Usage: /chain (then describe bug A)"
disable-model-invocation: false
Build exploit chain from: $ARGUMENTS
Process
1. Read brain for current target context: `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py brief <target>`
2. Get bug A description:
- If `$ARGUMENTS` contains a bug description → use it
- Else if brain has a recent confirmed finding → use that
- Else → ask user to describe the confirmed bug
3. Read `rules/chain-table.md` — the capability→next-bug table
4. Read `policy.md` — extract policy preamble for the agent
5. **ALWAYS dispatch `chain-builder` agent** (model: inherit) with:
- The confirmed bug A description (exact HTTP request/response)
- The full chain table from `rules/chain-table.md`
- Policy preamble (scope + required headers + restrictions)
- Brain context (tech stack, tested endpoints, known capabilities)
- Writeup intelligence: call `search_writeups "chain <bug class> escalation"` if MCP available
6. After agent returns:
- If chain found:
- `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py record <target> confirmed "chain: <summary>" "<full chain>"`
- Show chain to user with combined impact and CVSS
- Suggest: `/validate` then `/report`
- If dead end:
- `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py record <target> exhausted "chain from <bug A>" "<candidates tried>"`
- Show what was tried and why it failed
No inline chain logic. No capability table. The chain-builder agent does all the work.
Top-Tier Chain Standard
A chain is valuable only when each link grants a concrete capability.
Before dispatching, classify bug A as one capability:
- identity control: login, link, session, token, role, invite
- data read: PII, secrets, tenant data, internal API response
- data write: config, webhook, template, profile, billing, integration
- execution: script, server-side call, command, workflow run, model/tool action
- network pivot: SSRF, callback, metadata, internal host reachability
Ask the chain-builder for three paths: fastest proof, highest impact, and safest policy-compliant path. Kill chains that require guessing, prohibited data access, or unbounded scanning. A reportable chain must include end-to-end reproduction, where link 2 consumes the capability from link 1 rather than merely coexisting with it.
Read more
name: chain description: "Build deep exploit chains — dispatches chain-builder agent. Given bug A, recursively walks the chain graph. Usage: /chain (then describe bug A)" disable-model-invocation: false
Build exploit chain from: $ARGUMENTS
Process
1. Read brain for current target context: `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py brief <target>`
2. Get bug A description:
- If `$ARGUMENTS` contains a bug description → use it
- Else if brain has a recent confirmed finding → use that
- Else → ask user to describe the confirmed bug
3. Read `rules/chain-table.md` — the capability→next-bug table
4. Read `policy.md` — extract policy preamble for the agent
5. **ALWAYS dispatch `chain-builder` agent** (model: inherit) with:
- The confirmed bug A description (exact HTTP request/response)
- The full chain table from `rules/chain-table.md`
- Policy preamble (scope + required headers + restrictions)
- Brain context (tech stack, tested endpoints, known capabilities)
- Writeup intelligence: call `search_writeups "chain <bug class> escalation"` if MCP available
6. After agent returns:
- If chain found:
- `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py record <target> confirmed "chain: <summary>" "<full chain>"`
- Show chain to user with combined impact and CVSS
- Suggest: `/validate` then `/report`
- If dead end:
- `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py record <target> exhausted "chain from <bug A>" "<candidates tried>"`
- Show what was tried and why it failed
No inline chain logic. No capability table. The chain-builder agent does all the work.
Top-Tier Chain Standard
A chain is valuable only when each link grants a concrete capability.
Before dispatching, classify bug A as one capability:
- identity control: login, link, session, token, role, invite
- data read: PII, secrets, tenant data, internal API response
- data write: config, webhook, template, profile, billing, integration
- execution: script, server-side call, command, workflow run, model/tool action
- network pivot: SSRF, callback, metadata, internal host reachability
Ask the chain-builder for three paths: fastest proof, highest impact, and safest policy-compliant path. Kill chains that require guessing, prohibited data access, or unbounded scanning. A reportable chain must include end-to-end reproduction, where link 2 consumes the capability from link 1 rather than merely coexisting with it.
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Bug bounty agent framework for Claude Code, Codex, Gemini, Cursor, Windsurf, Copilot, and OpenClaw — 48 agents, 26 commands, 19 CLI tools, 2 MCP servers, autonomous hunt loops, exploit chain builder.
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Questions about chain.
- Which coding agents can use chain?
- chain installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.