القائمة
Verify harness changes end-to-end without docker — drive the real pinned CLI against a header-capturing stub server with the exact env resolve_auth_env() produces.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Adapt this C/C++ ASAN vulnerability pipeline to a different vulnerability class, target shape, language, or detection mechanism. Use when the user wants to port, migrate, retarget, customize, or fork the pipeline for something other than C/C++ memory-safety bugs — web apps, smart contracts, deserialization, ML systems, or any other domain.
Generate candidate fixes for verified security findings. Consumes TRIAGE.json (preferred), VULN-FINDINGS.json, or a vuln-pipeline results directory. Pipeline input is delegated to the execution-verified `vuln-pipeline patch` ladder; static-analysis input gets a per-finding patch subagent + independent reviewer and is written as inert diffs for human review. Writes PATCHES/bug_NN/{patch.diff,patch_result.json}, PATCHES.md, and PATCHES.json. Use when asked to "fix the findings", "patch these vulns", "generate fixes", or "close the loop on triage".
The front door for this repo. With no argument: a 30-second intro, then an offer to walk you through your first run on the canary target. With a question: answers it from this repo's own docs and source, cites where it looked, and hands you the next command. Use for "how do I…", "why does…", "where is…", "can this…", or just "/quickstart" to get oriented.
Build a threat model for a target codebase. Three modes: "interview" walks an application owner through the four-question framework and produces a threat model from their answers; "bootstrap" derives a threat model from the code plus past vulnerabilities (CVEs, git history, pentest reports) when no owner is available; "bootstrap-then-interview" chains the two when both owner and codebase are present. All write THREAT_MODEL.md in a shared schema. Use when asked to "threat model", "build a threat model", "map the attack surface", or "what should we be worried about in this codebase".
Triage a batch of raw security findings. Verify each is real, collapse duplicates, re-rank by derived exploitability, and tag with an owner. Takes a directory or file of scanner output and writes TRIAGE.json + TRIAGE.md sorted by what actually needs engineering attention. Use when asked to "triage findings", "validate scanner output", "prioritize vulns", or "review the backlog". Runs interactively by default; pass --auto to skip the interview.
Static source-code vulnerability scan. Reads a target directory (and THREAT_MODEL.md if present), spawns parallel review subagents per focus area, and writes VULN-FINDINGS.json + .md for /triage to consume. Read-only — no building, running, or network. For execution-verified crashes, use vuln-pipeline instead. Use when asked to "scan for vulns", "review this code for security issues", "find bugs in <dir>", or as the step between /threat-model and /triage.
| name | verify |
| description | Verify harness changes end-to-end without docker — drive the real pinned CLI against a header-capturing stub server with the exact env resolve_auth_env() produces. |
The pipeline's real surface is the in-container claude -p process and its
outbound API requests. Without docker, drive the same pinned CLI binary
directly with the env dict the harness would inject via docker -e.
harness/agent_image.py:CLAUDE_CODE_VERSION):
npm install --no-save @anthropic-ai/claude-code@<pin> in a temp dir →
binary at node_modules/@anthropic-ai/claude-code/bin/claude.exe (the
.exe name is the real native-binary entry on Linux too, filled in by the
package's postinstall — not a Windows leftover).invalid_request_error
(non-retryable, so the CLI exits fast; exit=1 is expected).python3 -c "from harness.auth import resolve_auth_env; ..." and dump to
an export-lines file with shlex.quote (values contain newlines —
NEVER pass via env $(...), word-splitting mangles them; source the file).unset ANTHROPIC_CUSTOM_HEADERS (and any
other ambient var not in the resolved dict) before sourcing — a Claude
Code session in this repo injects .claude/settings.json env into shells,
which containers never see.ANTHROPIC_BASE_URL=http://127.0.0.1:<port> CLAUDECODE= IS_SANDBOX=1 timeout 30 <cli> -p hi --model claude-sonnet-4-5 --max-turns 1, then read
the captured JSONL.tests/test_patch.py / tests/test_patch_grade.py need
docker and fail on docker-less hosts — pre-existing, not your change.-e injection leg itself can't be exercised without docker;
it's the same mechanism that carries ANTHROPIC_API_KEY in production..claude/settings.json into a
fresh temp dir and run the host claude from there (with ambient
ANTHROPIC_CUSTOM_HEADERS unset so settings.json is the only source).