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Vuln Scan

  • 882 installs
  • 6.9k repo stars
  • Updated August 4, 2026
  • anthropics/defending-code-reference-harness

vuln-scan is a Claude Code skill that runs a static source-code vulnerability scan of a target directory and writes VULN-FINDINGS.json + .md for triage.

About

This skill runs a static source-code vulnerability scan of a target directory. It reads THREAT_MODEL.md if present, spawns parallel review subagents per focus area covering memory safety, injection, and auth/crypto/data issues, and writes VULN-FINDINGS.json and .md for triage to consume. It is read-only and does not build, run, or reach the network; for execution-verified crashes it points to vuln-pipeline instead.

  • Static source-code vulnerability scan across parallel review subagents
  • Reads THREAT_MODEL.md for scoping and writes VULN-FINDINGS.json + .md for triage
  • Read-only: no building, running, or network access

Vuln Scan by the numbers

  • 882 all-time installs (skills.sh)
  • Ranked #422 of 2,203 Security skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
At a glance

vuln-scan capabilities & compatibility

Capabilities
security audit · vuln scan · code review
From the docs

What vuln-scan says it does

Static vulnerability review of a source tree. Produces `VULN-FINDINGS.json` (+ a human-readable `.md`) that `/triage` ingests directly.
SKILL.md
**This skill does not execute code.** It reads source and reasons about it.
SKILL.md
Unless `--single`, spawn **one Task subagent per focus area** in parallel. Cap at 10 concurrent.
SKILL.md
npx skills add https://github.com/anthropics/defending-code-reference-harness --skill vuln-scan

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Listed on Skillselion
Installs882
repo stars6.9k
Last updatedAugust 4, 2026
Repositoryanthropics/defending-code-reference-harness

What it does

Run a read-only static vulnerability scan of a source tree and write findings for triage to consume.

Who is it for?

Static source-code review of a target tree to find candidate vulnerabilities across memory safety, injection, and auth/crypto/data.

Skip if: Execution-verified findings; for ASAN crashes and reproducing PoCs it points the user at vuln-pipeline instead.

When should I use this skill?

Asked to 'scan for vulns', 'review this code for security issues', 'find bugs in <dir>', or as the step between threat-model and triage.

What you get

  • VULN-FINDINGS.json
  • VULN-FINDINGS.md

By the numbers

  • one Task subagent per focus area, capped at 10 concurrent
  • auto --single fallback on targets under 15 source files
  • 3-10 recon focus areas proposed

Files

SKILL.mdMarkdownGitHub ↗

/vuln-scan

Static vulnerability review of a source tree. Produces VULN-FINDINGS.json (+ a human-readable .md) that /triage ingests directly.

This skill does not execute code. It reads source and reasons about it. For execution-verified findings (ASAN crashes, reproducing PoCs), point the user at vuln-pipeline run <target> — see README Step 2.

Tool fallbacks. Prefer the dedicated Glob and Grep tools. Some sessions do not provision them — allowed-tools is a permission filter, not a loader, so listing them here does not make them appear. When Glob/Grep are unavailable, fall back to the read-only Bash commands whitelisted above: rg --files <scope> / ls -R for enumeration, rg -n / grep -rn for search, wc / head / file for sniffing. These are the ONLY permitted Bash commands; do not write helper scripts or pipe target content into a shell interpreter.

Arguments

  • <target-dir> (required) — directory to scan. Relative or absolute.
  • --focus <area> — scan only this focus area (repeatable). Skips recon.
  • --single — no subagent fan-out; one sequential pass. Use on tiny targets

or when debugging the prompt.

  • --extra <file> — append the contents of <file> to the review brief

(after the category list). Use to add org-specific vulnerability classes, compliance checks, or stack-specific patterns. Plain text; same shape as the category blocks below.

  • --no-score — skip the Step 3b confidence pass (saves a round of

subagents). Findings keep the scanner's self-reported confidence only.

Step 1 — Scope

1. Resolve <target-dir>. If it doesn't exist or has no source files, stop with an error. 2. Look for <target-dir>/THREAT_MODEL.md. If present, parse its section 3 "Entry points & trust boundaries" table and section 4 "Threats" table for focus areas and threat classes. This is the preferred scoping input. 3. If no THREAT_MODEL.md and no --focus: do a quick recon — list the source tree, read entry points and dispatch code, and propose 3-10 focus areas using the pattern <subsystem> (<function/file>) — <key operations>. Same shape as harness/prompts/recon_prompt.py. 4. If --focus was given, use exactly those.

Tell the user the focus areas you'll scan and the source-file count before fanning out.

Step 2 — Fan out

Unless --single, spawn one Task subagent per focus area in parallel. Cap at 10 concurrent. Each subagent gets the review brief below with its focus area filled in. On tiny targets (<15 source files), fall through to --single automatically.

Review brief (per subagent)

You are conducting authorized static security review of source code. Your
focus area: **{focus_area}**. Other agents cover other areas; duplication
is wasted effort.

TARGET: {target_dir}
TRUST BOUNDARY: {from THREAT_MODEL.md section 3, or "untrusted input → process memory"}

TASK: read the source in your focus area and identify candidate
vulnerabilities. This is static review — do NOT build, run, or probe
anything. Reason from the code.

REPORTING BAR: report anything with a plausible exploit path. Skip style
concerns, best-practice gaps, and purely theoretical issues with no attack
story at all — but if you're unsure whether something is real, REPORT IT
with a low confidence score rather than dropping it. A downstream triage
step does the rigorous verification; your job is to not miss things.

WHAT TO LOOK FOR:

  MEMORY SAFETY (C/C++ and unsafe/FFI blocks) — HIGH VALUE:
  - heap-buffer-overflow / stack-buffer-overflow / global-buffer-overflow
  - heap-use-after-free / double-free
  - integer overflow feeding an allocation or index
  - format-string bugs
  - unbounded recursion or allocation driven by untrusted size fields

  INJECTION & CODE EXECUTION — HIGH VALUE:
  - SQL / command / LDAP / XPath / NoSQL / template injection
  - path traversal in file operations
  - unsafe deserialization (pickle, YAML, native), eval injection
  - XSS (reflected, stored, DOM-based) — but see React/Angular note below

  AUTH, CRYPTO, DATA — HIGH VALUE:
  - authentication or authorization bypass, privilege escalation
  - TOCTOU on a security check
  - hardcoded secrets, weak crypto, broken cert validation
  - sensitive data (secrets, PII) in logs or error responses

  LOW VALUE — note briefly, keep looking:
  - null-pointer deref at small fixed offsets with no attacker control
  - assertion failures / clean error returns (correct handling, not a bug)

DO NOT REPORT (common false positives — skip even if technically present):
  - volumetric DoS / rate-limiting / resource-exhaustion — BUT unbounded
    recursion, algorithmic-complexity blowup, or ReDoS driven by untrusted
    input ARE reportable
  - memory-safety findings in memory-safe languages outside unsafe/FFI
  - XSS in React/Angular/Vue unless via dangerouslySetInnerHTML,
    bypassSecurityTrustHtml, v-html, or equivalent raw-HTML escape hatch
  - findings in test files, fixtures, build scripts, docs, or .ipynb
  - missing hardening / best-practice gaps with no concrete exploit
  - env vars and CLI flags as the attack vector (operator-controlled)
  - regex injection, log spoofing, open redirect, missing audit logs
  - outdated third-party dependency versions

{if --extra <file> was given: append its contents here verbatim}

For each finding you DO report, trace: where does the untrusted input
enter, what path reaches the sink, and what condition triggers it.

OUTPUT — one block per finding, nothing else:

<finding>
<id>F-{focus_idx:02d}-{n:02d}</id>
<file>{relative/path}</file>
<line>{line_number}</line>
<category>{heap-buffer-overflow | use-after-free | integer-overflow | sql-injection | command-injection | path-traversal | deserialization | xss | auth-bypass | hardcoded-secret | ...}</category>
<severity>{HIGH | MEDIUM | LOW}</severity>
<confidence>{0.0-1.0}</confidence>
<title>{one line}</title>
<description>{root cause, attacker control, trigger condition, data flow from entry to sink. Cite line numbers.}</description>
<exploit_scenario>{concrete attack: what input, from where, causing what outcome}</exploit_scenario>
<recommendation>{specific fix: parameterize the query, bounds-check before memcpy, etc.}</recommendation>
</finding>

SEVERITY: HIGH = directly exploitable → RCE, data breach, auth bypass.
MEDIUM = significant impact under specific conditions. LOW = defense-in-
depth.

If you find nothing reportable in your area after a thorough read, emit a
single <finding> with category=none and a one-line note of what you covered.

Step 3 — Collate

1. Collect <finding> blocks from all subagents. Drop category=none placeholders. 2. Light dedupe — if two findings cite the same file:line with the same category, keep the one with the longer description and note the duplicate id. (Heavy dedupe is /triage's job; don't over-engineer here.) 3. Assign stable ids F-001, F-002, ... in (severity desc, file, line) order.

Step 3b — Confidence pass (skip if --no-score)

A cheap second-opinion read that ranks findings by signal quality. Nothing is dropped — this pass calibrates confidence so humans and /triage see high-signal findings first. Spawn one Task subagent per finding in parallel with the brief below. Shallow: re-read and score, not a full reachability trace.

Scoring brief (per finding)

You are giving ONE candidate security finding an independent confidence
score. You are NOT deciding whether to keep it — every finding is kept.
You are deciding how likely it is to survive rigorous triage.

FINDING:
{the full <finding> block}

TARGET: {target_dir} (you may Read/Grep inside it; do NOT execute)

STEP 1 — Re-read the cited code. Open {file} around line {line}. Does the
code actually do what the description claims?

STEP 2 — Check against common false-positive patterns (volumetric DoS,
memory-safe language, test/fixture/doc file, framework auto-escape, env-var
vector, missing-hardening-only, regex/log injection, outdated dep). A match
lowers confidence sharply but does not auto-zero it.

STEP 3 — Score 1-10 that this is a real, actionable vulnerability:
  1-3  likely false positive or noise
  4-5  plausible but speculative
  6-7  credible, needs investigation
  8-10 high confidence, clear pattern

OUTPUT (exactly this, nothing else):
  CONFIDENCE: <1-10>
  REASON: <one line>

Resolve: overwrite each finding's confidence with the score (normalized to 0.0-1.0) and attach confidence_reason. Re-sort findings by (confidence desc, severity desc, file, line) and reassign ids F-001.. in that order. Compute low_confidence_count = findings with confidence < 0.4, for the summary line.

Step 4 — Write output

Write both files to <target-dir>/:

`VULN-FINDINGS.json` — the /triage ingest shape:

{
  "target": "<target-dir>",
  "scanned_at": "<iso8601>",
  "focus_areas": ["..."],
  "findings": [
    {
      "id": "F-001",
      "file": "relative/path.c",
      "line": 123,
      "category": "heap-buffer-overflow",
      "severity": "HIGH",
      "confidence": 0.9,
      "title": "...",
      "description": "...",
      "exploit_scenario": "...",
      "recommendation": "...",
      "confidence_reason": "..."
    }
  ],
  "summary": {"total": 0, "high": 0, "medium": 0, "low": 0, "low_confidence": 0}
}

Findings are sorted by confidence desc (then severity, file, line), so the top of the file is the highest-signal material.

`VULN-FINDINGS.md` — human-readable: a summary table (id | severity | category | file:line | title), then one ### F-NNN section per finding with the full description.

Step 5 — Hand back

Tell the user:

1. Counts: N findings (H/M/L split, X low-confidence), across K focus areas, from M source files. 2. Top 3 by confidence, one line each. 3. Next step: > /triage <target-dir>/VULN-FINDINGS.json --repo <target-dir> 4. Remind: these are static candidates, not verified. For execution-verified crashes, vuln-pipeline run <target> (README Step 2).

Constraints

  • Never execute target code. No Bash, no builds, no docker, no network.

If the user asks you to "reproduce" or "confirm with a PoC," decline and point at vuln-pipeline.

  • Don't fabricate line numbers. Every file:line you emit must be

something you Read or Grep'd. If unsure of the exact line, cite the function and say so in the description.

  • Stay in `<target-dir>`. Don't follow symlinks or .. out of it.
  • Findings are candidates for /triage, not final verdicts. **This skill

never drops a finding** — Step 3b only ranks. /triage does the rigorous N-vote verification and is where false positives actually get removed.

Provenance

The focus-area recon pattern and memory-safety quality tiers are lifted from this repo's own harness/prompts/find_prompt.py and harness/prompts/recon_prompt.py — the same logic the autonomous pipeline uses, applied statically. The broader category menu, DO-NOT-REPORT exclusions, per-finding confidence pass, and exploit_scenario/recommendation output fields are adapted from `anthropics/claude-code-security-review`'s /security-review command.

Related skills

FAQ

Does it execute the target?

No. It is read-only static review with no building, running, or network access; for execution-verified crashes it points to vuln-pipeline.

How does it scope the scan?

It parses THREAT_MODEL.md entry-point and threat tables if present, otherwise does a quick recon and proposes 3-10 focus areas.

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