code-review-methodology
Skill26 starsChanged 32 days agoMITView on GitHub
Systematic manual source-code security review — how to find bugs by reading code. Load on "review this code/repo", a source-available target, whitebox testing, or auditing a PR/app for vulnerabilities. Signals: a codebase in scope, "SAST", "secure code review", a language repo.
3 other projects use a version of this.
Adopted by
Most recently taken up by
- NoorQureshi/SploitAgentword for word, first seen Oct 11, 2026
- NoorQureshi/security-skillsword for word, first seen Oct 11, 2026
- chenyinrusi/dsh-engineering-skillstheir own version, first seen Aug 16, 2026
Other versions3 projects use a version of this.
Word for word · 2
- NoorQureshi/security-skills★ 27100% same
- NoorQureshi/SploitAgent★ 26100% same
Edited · 0
None found.
Wrote their own version · 1
- chenyinrusi/dsh-engineering-skills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository207 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- ad-adcsSkill
- ad-dacl-abuseSkill
- ad-delegation-abuseSkill
- ad-kerberoastingSkill
- ad-pivot-arsenalSkill
- ai-agent-tool-abuseSkill
- ai-insecure-output-handlingSkill
- ai-jailbreakSkill
- ai-llm-dosSkill
- ai-mcp-securitySkill
- ai-model-extractionSkill
- ai-prompt-injectionSkill
- ai-rag-poisoningSkill
- ai-sensitive-data-disclosureSkill
- ai-supply-chainSkill
- ai-system-prompt-leakageSkill
- api-auth-attacksSkill
- api-bolaSkill
- api-fuzzingSkill
- api-graphqlSkill
- api-grpcSkill
- api-mass-assignmentSkill
- api-mongo-agg-facet-bypassSkill
- api-testing-checklistSkill
- api-versioningSkill
- automation-browserSkill
- automation-nuclei-templatesSkill
- automation-recon-pipelineSkill
- cloud-azureSkill
- cloud-container-escapeSkill
- cloud-docker-api-abuseSkill
- cloud-docker-registrySkill
- cloud-gcpSkill
- cloud-iam-privescSkill
- cloud-imds-ssrfSkill
- cloud-kubernetesSkill
- cloud-s3-exposureSkill
- code-review-cicdSkill
- code-review-cppSkill
- code-review-dangerous-sinksSkill
- code-review-dotnetSkill
- code-review-goSkill
- code-review-iacSkill
- code-review-javaSkill
- code-review-nodejsSkill
- code-review-phpSkill
- code-review-pythonSkill
- code-review-rubySkill
- code-review-rustSkill
- code-review-secrets-detectionSkill
- code-review-soliditySkill
- crypto-oracle-attacksSkill
- crypto-rsa-attacksSkill
- ctf-cryptoSkill
- ctf-forensicsSkill
- ctf-methodologySkill
- ctf-pwnSkill
- ctf-revSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 35
Auth & access control: verify every sensitive route re-checks identity AND object ownership, not just "logged in".
- Very specific: line 42
Don't drown in semgrep noise.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Source-code security review — methodology
When it applies
You have (some of) the source. Whitebox review finds classes that blackbox misses — it follows data from where it enters to where it's dangerous, across the whole codebase at once.
Why it works
Vulnerabilities are source → sink flows with missing sanitization in between. Reading code lets you see the sink (dangerous function), trace back to a user-controlled source, and confirm nothing safe happens on the path — far faster and more complete than guessing from outside.
Method
- Map the app: entry points (routes/controllers/handlers), auth/authz middleware, the ORM/ DB layer, config, and where user input enters. Note the framework — its defaults decide a lot.
- Sink-first sweep: grep for dangerous functions per language (see
code-review-dangerous-sinks) and for each hit, trace the argument back to a source.semgrep --config autofor a fast first pass. - Source-to-sink for each class: injection (query/exec/template), authz (missing owner checks → IDOR/BOLA), deserialization, SSRF (URL fetchers), file ops (path traversal/upload), crypto misuse, secrets in code.
- Auth & access control: verify every sensitive route re-checks identity AND object ownership, not just "logged in". This is where the highest-impact bugs hide.
- Track findings with
file:line, the data path, and a PoC request; confirm dynamically where possible.
Gotchas
- A dangerous sink with a constant/allowlisted argument isn't a bug — confirm the source is user-controlled.
- Framework auto-escaping (ORM params, template autoescape) can neutralize an apparent sink — check config.
- Don't drown in
semgrepnoise; triage by exploitable source→sink, not raw hit count.
Verify success
For each finding: a concrete source→sink path with missing sanitization, ideally reproduced with a request/input that triggers it.
References
OWASP Code Review Guide; Semgrep rules; "Micro-methodology for code review" (GitHub Security Lab).
Does it work?
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Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

