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quickstart

Get started with vulnerability review through a guided practice target, from threat modeling to scanning and triage. Ask questions about the pipeline and receive answers grounded in its documentation and source, with references and a next command.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

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.

연동 도구Docker
설치 방법 보기

이럴 때 유용합니다

  • Learn the vulnerability review workflow
  • Try a first scan on the bundled practice target
  • Find commands with supporting documentation
  • Understand pipeline settings and requirements

포함된 파일(1)

  • SKILL.md5.7 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

/quickstart

Two modes, picked by whether $ARGUMENTS is empty.

  • Empty → Intro mode. Short orientation, then offer the guided first run.
  • Non-empty → Help mode. Treat $ARGUMENTS as the operator's question.

Intro mode

Keep it short and a little warm; this is the first thing a new operator sees.

Say roughly:

Welcome! This repo takes you from finding your first vulnerability to patching at scale, using a set of Claude Code skills and an autonomous pipeline. Two ways in: interactive skills (no setup, safe, start here) and the autonomous pipeline (Docker, scales to hundreds of parallel agents).

The ramp-up:

| Day 1 | Threat-model + first static scan + triage | | Day 2 | Run the reference pipeline (C/C++) | | Day 3-4 | Customize it for your stack | | Week 2 | Autonomous scanning, triage, and patching |

Day-1 goal: threat-model, scan, and triage the bundled canary target. Most teams get there before lunch.

Remind them to export CLAUDE_CODE_SUBAGENT_MODEL=<model-id> so subagents use the same model as the session.

Then AskUserQuestion with three options:

  1. Walk me through Day 1 on the canary (~10 min) → run "Guided first run" below.
  2. I have a question → ask what it is, then switch to Help mode.
  3. I'll read the README → point at README.md Step 1 and stop.

Guided first run

Runs the three Step-1 skills on targets/canary, pausing after each to show what landed on disk. These only read/write files in the repo; no sandbox needed.

  1. /threat-model bootstrap targets/canary via Task. When done, open THREAT_MODEL.md, show the focus areas, explain in 2-3 sentences how this steers the scan.
  2. /vuln-scan targets/canary via Task. When done, open targets/canary/VULN-FINDINGS.md, summarize the count and top 2-3 findings, point at VULN-FINDINGS.json.
  3. /triage targets/canary/VULN-FINDINGS.json via Task. When done, open TRIAGE.md, explain what changed vs. raw findings (verified, deduped, re-ranked).

Pause for the operator between each (AskUserQuestion); don't barrel through. Close with a one-line recap of the three artifacts on disk, then point at README Step 2 for the execution-verified pipeline. Never run vuln-pipeline or anything that executes target code here; that's Step 2 and needs Docker + a sandbox.


Help mode

Answer the operator's question using this repo as ground truth: README, docs/*.md, harness/*.py, dnr_harness/*.py, targets/*/config.yaml, .claude/skills/*. Don't answer from general knowledge when the repo has a specific answer.

Routing map

If the question is about…Read firstThen offer
running the pipelinedocs/pipeline.md, README Step 2the recon / run command
too many findings, triagedocs/triage.md/triage <path>
porting, Java/Go/Rust/etc.docs/customizing.md, README Step 3/customize
safety, sandbox, Dockerdocs/security.mdcite; no action
rate limits, 429, token budgetdocs/pipeline.md: Rate limits, docs/troubleshooting.md#rate-limitscite the numbers
duplicates, dedupdocs/troubleshooting.md#duplicate-findingsknown_bugs: hint
CLI flags, "what does --X do"harness/cli.py (grep the argparse)exact flag + example
which model, subagent pinningdocs/troubleshooting.md: Subagentsthe export line
best practices, promptingdocs/best-practices.md, docs/prompting.mdcite the principle
threat model, attack surface, scopedocs/threat-model.md/threat-model bootstrap <target-dir>
scan, audit, find vulns.claude/skills/vuln-scan/SKILL.md/vuln-scan <target-dir>
"how do I start"README Step 1offer Guided first run
patching, fix, diff, re-attackdocs/patching.md, README Step 4/patch <input>
threat hunting, incident response, logsdocs/detection-response.md/dnr-hunt or /dnr-respond
autonomous D&R, dnrcanarydocs/detection-response.md, targets/dnrcanary/README.mdthe dnr-pipeline run command
binary, embedded, other domainsdocs/other-use-cases.mdcite section
anything elseREADME Table of contentsbest-match doc

Answer format

  1. Direct answer in 2-5 sentences.
  2. > source: the file(s) and section you used.
  3. Next action: one copy-pasteable command or skill invocation, if one applies. If none does, say so.
  4. If the question is ambiguous, ask one clarifying question; don't guess.

Constraints

  • Never fabricate CLI flags or file paths. If unsure, Grep for it in harness/cli.py or the target configs and quote what you find.
  • If the repo doesn't answer the question, say so plainly and suggest the operator open a GitHub issue on this repo.
  • Keep the Q&A dry and cited. Save the warmth for Intro mode.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

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같은 저장소의 스킬

customize

무료

Adapt a C/C++ vulnerability pipeline to another language, target, or detection method. The workflow gathers requirements, proposes file changes for approval, updates the implementation, and validates it against a test target containing known bugs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Adapt the pipeline for web application vulnerabilities
  • Plan a port for smart contract auditing
  • Change detection signals and report criteria
anthropics/defending-code-reference-harness7.6천2026년 8월 7일 업데이트

dnr-hunt

무료

Hunt for signs of compromise in web and application logs without an initial alert. Establish normal activity, record investigative hypotheses, check source code, and reproduce issues locally before producing incident records and a report.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Hunting for compromise without an initial alert
  • Tracing related activity across application logs
  • Distinguishing attack attempts from successful exploitation
anthropics/defending-code-reference-harness7.6천2026년 8월 7일 업데이트

Investigate an alert or suspicious identifier using logs and source code. Assess attack success, measure affected data and users, test the suspected flaw locally, and produce a response plan for human review and execution.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Investigating a security alert
  • Measuring affected records and customers
  • Checking a suspected flaw with a local proof of concept
anthropics/defending-code-reference-harness7.6천2026년 8월 7일 업데이트

patch

무료

Turn security findings into candidate code fixes with review results and summaries. Depending on the input, use independent source review or a pipeline with execution checks, then provide diffs for a person to review and apply.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Generating candidate fixes from triaged findings
  • Preparing diffs for the highest-priority vulnerabilities
  • Independently reviewing proposed security fixes
anthropics/defending-code-reference-harness7.6천2026년 8월 7일 업데이트

Build a threat model that identifies valuable assets, attack entry points, potential threats, and mitigation priorities. Use source code and past vulnerabilities, an interview with the application owner, or a combination of both.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Reviewing security risks during system design
  • Assessing an inherited codebase without its owner
  • Refining a code-based draft with the application owner
anthropics/defending-code-reference-harness7.6천2026년 8월 7일 업데이트

triage

무료

Turn raw security findings into a ranked list for engineering review. Check claims against source code, merge duplicates, assess how feasible exploitation is, and assign component owners, with results in JSON and Markdown.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Validating security scanner findings
  • Merging duplicate findings across scans
  • Prioritizing a vulnerability backlog
anthropics/defending-code-reference-harness7.6천2026년 8월 7일 업데이트

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