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kaandgnshkaandgnsh/Claude-Blue/skills/appsec/sast-triage/SKILL.md

sast-triage

Skill0 starsChanged 13 days agoMITView on GitHub

Run and triage static application security testing (Semgrep, CodeQL, SonarQube, Bandit, gosec, Brakeman) — reachability of sources to sinks, framework-provided protections, true/false positive decisions, suppression hygiene and custom rules. Use when a SAST scan produces findings to review, when tuning SAST noise in CI, or writing a custom rule for a recurring bug class.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Does data reach the sink unsanitized?: Follow the dataflow path the tool reports.

    line 28
  2. Distinctive:

    Never suppress a whole rule globally because of one FP.

    line 35

≈ “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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

SAST Triage

Running scanners

semgrep scan --config p/default --config p/owasp-top-ten --sarif -o semgrep.sarif .
semgrep scan --config p/secrets .                       # secrets ruleset
codeql database create db --language=python --source-root .
codeql database analyze db codeql/python-queries:codeql-suites/python-security-extended.qls --format=sarif-latest --output=codeql.sarif
bandit -r src/ -f json -o bandit.json                    # Python
gosec -fmt sarif -out gosec.sarif ./...                  # Go

Upload SARIF to the code host (GitHub code scanning, GitLab) so findings appear inline in PRs.

Triage decision per finding

  1. Is the source attacker-controlled? (HTTP input, file upload, message queue) — or constant/config/admin-only?
  2. Does data reach the sink unsanitized? Follow the dataflow path the tool reports; check for validation, parameterization, framework auto-escaping (Django/Jinja2 autoescape, React JSX), allow-lists.
  3. Is the code reachable in production? (dead code, tests, scripts, feature-flagged off).
  4. Decide: TP (ticket with fix), FP (suppress with reason), won't-fix (risk-accepted with approver).

Suppression hygiene

  • Inline suppressions with a reason: # nosemgrep: python.lang.security.audit.subprocess-shell-true -- command is constant.
  • Never suppress a whole rule globally because of one FP; tune the rule (path exclusions for tests, pattern-not for known safe wrappers).
  • Review suppressions periodically.

Custom Semgrep rule example

rules:
  - id: corp-missing-ownership-check
    languages: [python]
    severity: WARNING
    message: Order fetched by ID without owner filter — possible IDOR (CWE-639)
    patterns:
      - pattern: Order.objects.get(id=$ID)
      - pattern-not-inside: |
          Order.objects.get(id=$ID, owner=$USER)

Metrics

TP rate per rule (drop/tune rules < 20% TP), time-to-fix by severity, new vs. existing findings (gate only on new findings in PRs to avoid blocking on legacy debt).

Related skills

secure-code-review, sca-dependency-risk, release-gate, github-actions-hardening

References

Download now (ZIP)

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