customize — Claude Code skill: port the vuln-pipeline to your domain
A skill to adapt the C/C++ vulnerability-finding pipeline to other languages, domains, and target shapes. Turns an opinionated demo into a template: swap the detector, prompts, and sandbox — and the pipeline hunts what you need.
npx skills add anthropics/defending-code-reference-harness --skill customize -a claude-codeWhat customize does
This is not a ready-made solution for web or smart contracts, but a worked example that shows how to build your own. Out of the box, the pipeline finds memory-safety bugs in C/C++ via AddressSanitizer: one agent crafts an input, runs the target in a sandbox, a detector fires on a crash, a second agent verifies the finding, a third analyzes exploitability.
Every stage can be swapped. Want to hunt SQL injection in web apps? Rewrite the detector to parse HTTP logs, change the prompts to look for dangerous SQL patterns, reformatted the report. Want smart contracts? Point the sandbox at Solidity, switch analysis to reentrancy and access control. The skill walks you through the source architecture, shows what's generic and what's ASAN-specific, and flags which files to edit.
The process is an interview: you describe the vulnerability class and where it lives, the skill narrows down details (how to run the target, what signals success, what goes in the report), then helps rewrite the prompts and configs. The interview covers all axes of variation: vuln class, target shape, sandbox type, grading criteria, report fields, whether to check upstream.
What it helps with
- adapt a vulnerability-finding pipeline to a new domain without rewriting from scratch
- identify which parts of the C/C++ pipeline generalize and which are ASAN-specific
- rewrite the detector, agent prompts, and sandbox for web, smart contracts, or another vuln class
- set up reporting: choose analysis sections, scoring rubrics, output format
- integrate the pipeline into CI or an appsec platform
Example prompts for the agent
- Help me adapt this pipeline to find reentrancy bugs in Solidity contracts.
- I want to retarget it for SQL injection in Django apps — where do I start?
- How do I port the pipeline to Java deserialization? Which files change?
How to install customize
1Skills CLI (Vercel)
npx skills add anthropics/defending-code-reference-harness --skill customize -a claude-code2Manually: put the files in place
~/.claude/skills/customize/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/customize/
1Skills CLI (Vercel)
npx skills add anthropics/defending-code-reference-harness --skill customize -a codex2Manually: put the files in place
.agents/skills/customize/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add anthropics/defending-code-reference-harness --skill customize -a cursor2Manually: put the files in place
.cursor/skills/customize/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install anthropics/defending-code-reference-harness customize2Manually: put the files in place
.github/skills/customize/SKILL.md1Skills CLI (Vercel)
npx skills add anthropics/defending-code-reference-harness --skill customize -a gemini-cli2Platform CLI
gemini skills install https://github.com/anthropics/defending-code-reference-harness --path .claude/skills/customizeManually: put the files in place
.devin/skills/customize/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add anthropics/defending-code-reference-harness --skill customize -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
From the same set6
The whole set →Similar
Questions about customize
How do I install customize in Claude Code?
Run npx skills add anthropics/defending-code-reference-harness --skill customize -a claude-code. The skill loads into ~/.claude/skills/customize/SKILL.md and becomes available as a tool inside Claude Code.
What does customize do?
It's not an automatic adaptation tool, but a code-guided reference. The skill conducts an interview to learn which vulnerability class you want to hunt and where, then walks through the source C/C++ architecture and flags which files—prompts, detector, Dockerfile—need changes for your domain.
What domains can I retarget to?
Any: web vulns (SQLi, XSS, SSRF), deserialization RCE, smart contracts (reentrancy, access control), ML systems (prompt injection), protocols, crypto. The requirement is that you can run the target in an isolated sandbox (Docker, VM, testnet) and define a detection signal (crash, exception, differential mismatch, invariant violation).
Source text
SKILL.md · Apache-2.0
--- name: customize description: 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. --- # Customize the vuln-pipeline This pipeline ships as an opinionated C/C++ + AddressSanitizer demo. Its real shape is more general: **an agent crafts an input, runs a target in a sandbox, a detector fires, a second agent verifies, a third agent analyzes exploitability.** Every noun in that sentence can be swapped. Your job is to interview the user, figure out which nouns they want to swap, and rewrite the relevant files. The existing C/C++ code is the worked example. You don't need a playbook for each domain — read what's there, understand what's generic vs. ASAN-specific, and adapt. ## STEP 1 — Read the pipeline (do this BEFORE asking anything) Skim these files so your questions are grounded: - `README.md` — pipeline overview (recon → find → grade → judge → report) - `harness/cli.py` — orchestration; shows how stages wire together and what lands on disk - `harness/find.py`, `harness/grade.py`, `harness/report.py` — the three container-agent loops; mostly generic plumbing - `harness/prompts/find_prompt.py`, `harness/prompts/grade_prompt.py` — **the C/C++-specific parts**; bug taxonomy, quality tiers, grading rubric - `harness/prompts/report_prompt.py`, `harness/prompts/report_grader_prompt.py` — **also C/C++-specific**; exploitability sections (primitive, heap layout, escalation path) and the rubric that scores them - `harness/prompts/judge_prompt.py` — triage prompt; keys on ASAN excerpts and memory-safety crash classes - `harness/prompts/system_prompt.py` — authorization block; hard-codes "C/C++ target" and "sanitizer output" - `harness/asan.py` — stack-trace parser for dedup/judge signatures; ASAN-specific regex - `harness/artifacts.py` — `CrashArtifact`, `GraderVerdict`, `JudgeVerdict`, `ReportVerdict` data contracts - `harness/config.py`, `targets/drlibs/config.yaml` — target config schema - `targets/README.md` — how a target directory is structured (Dockerfile + config.yaml + entry wrapper) You don't need `agent.py`, `docker_ops.py`, `recon.py`, `judge.py`, or `novelty.py` in detail — they're generic plumbing (judge/novelty domain-specificity lives in the prompts and the asan parser, not the flow). One caution: part of `harness/` doubles as shared infrastructure — `dnr_harness/` (the detection-and-response pipeline) imports `agent.py`, `sandbox.py`, `docker_ops.py`, `agent_image.py`'s `build`/`ensure_base`, `auth.py`, `cli.py`'s `resolve_target_dir`/`terminate_subprocesses`, and `prompts/system_prompt.py`'s `load_engagement_context`. A domain port should touch only the domain-specific files (the prompts, `asan.py`, `artifacts.py`, target Dockerfiles); treat any edit to the shared files as a change to both pipelines. ## STEP 2 — Interview the user Use **AskUserQuestion** to gather requirements. Start with broad context, then narrow to technical specifics based on what they say. ### Round 1 — Context (always ask these first, together) Two open-ended questions to understand who you're talking to and what they're after. Expect most answers to come via **Other** as free text — the options are there to prompt thinking, not to constrain. **Question A — Operating context** - header: `Context` - question: `What's your operating environment? Who will run this pipeline and why?` - options: a few archetypes as inspiration — e.g. "Pentesting firm — client engagements, need reportable findings", "Internal appsec team — scan our own services in CI", "Smart-contract auditor — pre-deployment reviews", "Security researcher — hunting novel bug classes". These tell you what output format, grading rigor, and workflow integration matter. **Question B — Goal** - header: `Goal` - question: `Describe in your own words what you want this pipeline to find. What kind of target, what kind of bugs?` - options: 2–3 concrete examples (e.g. "Web vulnerabilities like SQLi/XSS in HTTP services", "Reentrancy and access-control bugs in Solidity contracts", "Deserialization RCE in Java microservices"). The context answer calibrates your follow-ups: a pentesting firm probably cares about CVSS scoring and SARIF output; a researcher may want differential testing and novel detection signals; an internal team likely wants CI integration and low false-positive rates. ### Round 2 — Technical follow-ups (adaptive — derive from round-1 answers) Parse their round-1 answers against the **axes of variation** below. For each axis left ambiguous, ask a targeted follow-up. Batch up to 4 questions per AskUserQuestion call. Common follow-ups: - **Detection signal** — "How will the pipeline know it found something?" (crash, exception, canary file appears, DNS callback, differential mismatch, invariant violation) - **PoC shape** — "What does a proof-of-concept look like?" (single file, HTTP request sequence, transaction list, test-pipeline code) - **Isolation** — "Where does the target run?" (Docker, VM, testnet, remote sandbox, or no execution — static-only) - **Grading criteria** — "What makes a finding high-quality vs. low-quality in this domain?" - **Exploitability analysis** — "What sections should a report contain?" The C/C++ report has primitive · reachability · heap layout · escalation path · constraints. A web-vuln report might want injection vector · auth bypass · data exposure · chaining potential. Ask what they need, or whether they want the report stage at all. - **Novelty/upstream check** — "Should the pipeline check if a finding is already fixed upstream?" The C/C++ version shallow-clones the target's GitHub and checks `git log <commit>..HEAD -- <crash_file>`. Only applies if targets have a canonical upstream and a sensible "crashing file" to key on — many domains won't. - **Scope** — "Replace the C/C++ support entirely, or keep it alongside the new domain via a profile system?" Keep going until you can fill in every row of the architecture map in STEP 3. If an answer is vague, ask a narrower follow-up rather than guessing. ## Background — axes of variation (context for formulating follow-ups) These are the dimensions along which customers might want to deviate from the C/C++ demo. Use this list to spot gaps in the user's description and generate follow-up questions — do **not** present it as a menu. **Vulnerability class:** memory safety · web/API (SQLi, XSS, SSRF, XXE, path traversal, IDOR) · deserialization RCE · logic/race (TOCTOU, privilege escalation) · crypto (weak RNG, timing, nonce reuse) · DoS (ReDoS, hash flooding) · smart contracts (reentrancy, access control, front-running) · ML/AI (prompt injection, jailbreaks, data extraction) · protocol parsing **Target shape:** CLI binary + file · HTTP service · library via test harness · network daemon · smart contract · browser extension · mobile app **Detection mechanism:** crash/abort · uncaught exception · sanitizer hooks (Jazzer/Atheris) · outcome-based (canary file, DNS callback, shell spawn) · differential testing · invariant violation · taint tracking **Input modality:** single file · HTTP request chain · multi-file archive · stdin stream · args + env + config combo · transaction sequence **Isolation boundary:** Docker container · full VM · remote sandbox · local testnet · none (static analysis) **Dedup signature:** (crash_type, top_frame) · (vuln_type, endpoint, param) · (function, state_transition) · (component, precondition) **Report structure:** primitive/heap/escalation (memory safety) · vector/auth/exposure (web) · invariant/path/impact (contracts) · or drop the report stage entirely if find+grade is the deliverable **Output format:** result.json + poc.bin · SARIF · Nuclei template · prose report **Patch verification signal:** ASAN-clean exit · uncaught-exception-free · sanitizer hook silent (Jazzer/Atheris) · canary file untouched · invariant assertion holds · differential output matches reference. This is what `_t1_passes()` in `patch_grade.py` encodes — "the bug is gone" for the new domain. ## Background — architecture map (what changes vs. what stays) | File | C/C++-specific? | What it does | |---|---|---| | `harness/prompts/find_prompt.py` | **Yes — rewrite** | Bug taxonomy, quality tiers, ASAN output format, exit-code examples | | `harness/prompts/grade_prompt.py` | **Yes — rewrite** | 5-criterion rubric assumes ASAN traces and Unix signal exit codes | | `harness/prompts/report_prompt.py` | **Yes — rewrite** | Exploitability sections: primitive, heap layout, escalation path — memory-safety-specific | | `harness/prompts/report_grader_prompt.py` | **Yes — rewrite** | Scores the above sections; rubric is tied to the section set | | `harness/prompts/judge_prompt.py` | **Yes — rewrite** | Triage keys on ASAN excerpts and crash-class taxonomy | | `harness/prompts/patch_prompt.py` | **Yes — rewrite** | Asks for `git diff -- '*.c' '*.h'`, assumes ASAN trace, `memcpy`-style root-cause guidance | | `harness/prompts/system_prompt.py` | **Yes — rewrite** | Authorization block says "C/C++ target", "sanitizer output" | | `harness/asan.py` | **Yes — rewrite** | Regex for `#N 0xHEX in func /path:line` frames; feeds dedup, judge, novelty | | `targets/README.md` + Dockerfile template | **Yes — rewrite** | `gcc -fsanitize=address`, `entry.c` wrapper pattern | | `harness/patch_grade.py` | Light edit | `_t1_passes()` checks `AddressSanitizer:` substring; rest of the verification ladder is generic | | `harness/report.py` | Light edit | `_SECTIONS` tuple and token lists need to match the new report structure; flow is generic | | `harness/novelty.py` | Light edit | `crash_file_from_frame()` is ASAN-specific; git-log logic is generic. Drop entirely if no upstream. | | `harness/config.py` | Light edit | May need new fields (`profile`, `run_command` instead of `binary_path`); `attack_surface` likely stays | | `harness/artifacts.py` | Light edit | `crash_type`/`exit_code` semantics may shift; `ReportVerdict.section_scores` keys must match new sections | | `harness/dedup.py` | Light edit | Signature function needs the new parser; grouping logic is generic | | `harness/prompts/recon_prompt.py` | Light edit | Mostly language-agnostic; scrub C idioms | | `harness/cli.py` | **Unchanged** | Orchestration is domain-neutral | | `harness/agent.py` | **Unchanged** | Agent runner is generic | | `harness/docker_ops.py` | **Unchanged** | Container plumbing is generic (may need changes if isolation ≠ Docker) | | `harness/find.py`, `grade.py`, `recon.py`, `judge.py`, `patch.py` | **Unchanged** | Flow is generic; only injected prompts change | ## STEP 3 — Present a plan and get confirmation Before editing anything, summarize back to the user: 1. **What you understood** — restate their goal in one sentence 2. **What will change** — list each file you'll edit with a one-line rationale 3. **What stays** — reassure them the orchestration core is untouched; call out explicitly if the plan does reach into the shared files listed above (they also serve `dnr_harness/`) and why 4. **Open questions** — anything you're still unsure about Wait for explicit approval. If they adjust the plan, incorporate and re-confirm. ## STEP 4 — Execute Edit the files per the approved plan. Work through them in dependency order: prompts and parser first (they're standalone), then config/artifacts, then the target template, then README. Commit incrementally if the user wants checkpoints. ## STEP 5 — Validate 1. Add a canary target under `targets/<domain>-canary/` with 2–3 planted bugs of the new class 2. Run: `bin/vp-sandboxed run <domain>-canary --model <model-id> --runs 3 --parallel --stream --max-turns 50` (use Claude Opus unless the user specifies a different model). Run `./scripts/setup_sandbox.sh` once first if the sandbox isn't already set up. 3. Confirm all planted bugs are found and graded PASS 4. Confirm judge triage worked: `cat results/<domain>-canary/<ts>/reports/judge_log.jsonl` — expect one NEW per distinct bug, DUP_SKIP for repeats 5. Confirm reports landed: `ls results/<domain>-canary/<ts>/reports/bug_*/report.json` and spot-check section scores 6. Run `vuln-pipeline dedup results/<domain>-canary/` and confirm signatures group correctly
© anthropics · Apache-2.0 · anthropics/defending-code-reference-harness