agentleFS
matheus-rib1108matheus-rib1108/meu-kit-claude-code/skills/seguranca-e-lei/semgrep/SKILL.md

semgrep

Skill0 starsChanged 27 days agoMITView on GitHub

Runs a Semgrep security scan over a codebase: detects languages, selects rulesets, presents the plan for explicit approval, then runs every approved ruleset through scripts/run-scans.sh, which batches the semgrep processes and writes scans.json, and merges the output to SARIF. Supports two scan modes, "run all" for full ruleset coverage and "important only" for security findings at medium-to-high confidence and impact. Uses Semgrep Pro for cross-file taint analysis when it is available. Use when asked to scan code for vulnerabilities, run a security audit with Semgrep, find bugs, or perform static analysis. For the same scan without the approval gate, use the /static-analysis:semgrep-scan workflow.

11 other projects use a version of this, 5 of them edited.

Adopted by

Most recently taken up by

Used with

Projects with it also use insecure-defaults, xlsx and 1 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • allanninalSkill

    insecure-defaults

    Detects fail-open insecure defaults (hardcoded secrets, weak auth, permissive security) that allow apps to run insecurely in production. Use when auditing security, reviewing config management, or analyzing environment variable handling.

    Also in 3 projects that use this

  • AnthropicSkill

    xlsx

    Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

    Also in 3 projects that use this

  • AnthropicSkill

    docx

    Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 10 edited versions we read keep these.

  • 3

    Distinctive

    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:

    Run a Semgrep scan with automatic language detection, parallel execution, and merged SARIF output.

    line 19
  2. Distinctive:

    All scan results, SARIF files, and temporary data are stored in a single output directory.

    line 47
  3. Distinctive:

    Use the workflow when you want the scan run.

    line 173

“Common” is measured: kept by at least 6 in 10 of the 10 edited versions of this file we could read. “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

Semgrep Security Scan

Run a Semgrep scan with automatic language detection, parallel execution, and merged SARIF output.

Essential Principles

  1. Always use --metrics=off — Semgrep sends telemetry by default; --config auto also phones home. Every semgrep command must include --metrics=off to prevent data leakage during security audits.
  2. User must approve the scan plan (Step 3 is a hard gate) — The original "scan this codebase" request is NOT approval. Present exact rulesets, target, engine, and mode; wait for explicit "yes"/"proceed" before spawning scanners.
  3. Third-party rulesets are required, not optional — Trail of Bits, 0xdea, and Decurity rules catch vulnerabilities absent from the official registry. Include them whenever the detected language matches.
  4. scripts/run-scans.sh generates the commands; do not write them yourself — it builds every semgrep line from the approved list. That is what makes --metrics=off, the --include scoping rule, and the parallel dispatch properties of the code rather than instructions. Give it the approved rulesets and let it run.
  5. Always check for Semgrep Pro before scanning — Pro enables cross-file taint tracking and catches ~250% more true positives. Skipping the check means silently missing critical inter-file vulnerabilities.
  6. Report what did not run — scans.json carries failed and skipped alongside scans. A ruleset whose repo would not clone, or whose scan exited non-zero, must appear in the report. A partial scan presented as a complete one is worse than no scan.

When to Use

  • Security audit of a codebase
  • Finding vulnerabilities before code review
  • Scanning for known bug patterns
  • First-pass static analysis

When NOT to Use

  • Binary analysis → Use binary analysis tools
  • Already have Semgrep CI configured → Use existing pipeline
  • Need cross-file analysis but no Pro license → Consider CodeQL as alternative
  • Creating custom Semgrep rules → Use semgrep-rule-creator skill
  • Porting existing rules to other languages → Use semgrep-rule-variant-creator skill

Output Directory

All scan results, SARIF files, and temporary data are stored in a single output directory.

  • If the user specifies an output directory in their prompt, use it as OUTPUT_DIR.
  • If not specified, default to ./static_analysis_semgrep_1. If that already exists, increment to _2, _3, etc.

In both cases, always create the directory with mkdir -p before writing any files.

# Resolve output directory
if [ -n "$USER_SPECIFIED_DIR" ]; then
  OUTPUT_DIR="$USER_SPECIFIED_DIR"
else
  BASE="static_analysis_semgrep"
  N=1
  while [ -e "${BASE}_${N}" ]; do
    N=$((N + 1))
  done
  OUTPUT_DIR="${BASE}_${N}"
fi
mkdir -p "$OUTPUT_DIR/raw" "$OUTPUT_DIR/results"

The output directory is resolved once at the start of Step 1 and used throughout all subsequent steps.

$OUTPUT_DIR/
├── rulesets.json                # The approved plan (Step 3), read by run-scans.sh (Step 4)
├── scans.json                   # What ran, failed, skipped, and covered nothing (Step 4)
├── raw/                         # Per-scan raw output (unfiltered)
│   ├── python-python.json        # <language>-<ruleset> for language-scoped rules
│   ├── python-python.sarif
│   ├── python-django.json
│   ├── python-django.sarif
│   ├── all-security-audit.json   # all-<ruleset> for cross-language rules, run once
│   ├── all-security-audit.sarif
│   └── ...
└── results/                     # Final merged output
    └── results.sarif

Prerequisites

Required: Semgrep CLI (semgrep --version). If not installed, see Semgrep installation docs.

Optional: Semgrep Pro — enables cross-file taint tracking, inter-procedural analysis, and additional languages (Apex, C#, Elixir). Check with:

# --metrics=off because Principle 1 has no exceptions, and this is the first semgrep command
# of a run. stderr is kept because "OSS only" has several causes (logged out, no subscription,
# registry blocked) and the run downgrades silently for all of them.
if PRO_ERR=$(semgrep --pro --validate --metrics=off --config p/default 2>&1); then
  echo "Pro available"
else
  echo "OSS only"
  echo "  reason: $(printf '%s' "$PRO_ERR" | tail -n 3)"
fi

Limitations: OSS mode cannot track data flow across files. Pro mode uses -j 1 for cross-file analysis (slower per ruleset, but parallel rulesets compensate).

Scan Modes

Select mode in Step 2. Mode affects both the scan flags and post-processing.

ModeCoverageFindings Reported
Run allAll rulesets, all severity levelsEverything
Important onlyAll rulesets, pre- and post-filteredSecurity vulns only, medium-high confidence/impact

Important only applies two filter layers:

  1. Pre-filter: --severity WARNING --severity ERROR (CLI flag)
  2. Post-filter: JSON metadata — keeps only category=security, confidence∈{MEDIUM,HIGH}, impact∈{MEDIUM,HIGH}

See scan-modes.md for metadata criteria and jq filter commands.

Orchestration Architecture

┌──────────────────────────────────────────────────────────────────┐
│ MAIN SESSION (this skill)                                        │
│ Step 1: Detect languages + check Pro availability                │
│ Step 2: Select scan mode + rulesets (ref: rulesets.md)           │
│ Step 3: Present plan + rulesets, get approval [⛔ HARD GATE]     │
│ Step 4: Run scripts/run-scans.sh with the approved rulesets      │
│ Step 5: Post-filter, merge, report, delete repos/                │
└──────────────────────────────────────────────────────────────────┘
         │ Step 4: Bash
         ▼
┌──────────────────────────────────────────────────────────────────┐
│ scripts/run-scans.sh                                             │
│   clone       each third-party repo once, into repos/            │
│   generate    one semgrep command per ruleset                    │
│                ├── python     p/python, p/django   --include=*.py│
│                ├── javascript p/javascript         --include=*.js│
│                ├── docker     p/dockerfile                       │
│                └── cross-language  p/security-audit, p/secrets,  │
│                                    the cloned repos  (no filter) │
│   run         in batches of --jobs, exit code read per process   │
│   write       scans.json — scans, failed, skipped                │
└──────────────────────────────────────────────────────────────────┘

The approval gate stays in the session; the script is execution only and asks nothing. The approved list reaches it as a JSON file, so the scan cannot reach a ruleset the user declined.

Cross-language rulesets go in one shared unit rather than being repeated per language. p/security-audit, p/secrets, and the third-party repos scan the whole target unscoped, so running them once per language ran the identical command N times and left the SARIF merge to dedup the copies.

Running it as a Workflow

This plugin ships /static-analysis:semgrep-scan, which runs the whole scan end to end: detect languages and Pro, select rulesets from rulesets.md, run scripts/run-scans.sh, merge and report. Pass it a JSON object, not prose:

/static-analysis:semgrep-scan {"target": "/abs/path", "mode": "run-all"}

It does not stop for ruleset approval. Invoking it with a target is the opt-in, the same way /variant-analysis:variants works. That is safe to do because the scan is read-only over the target — no --autofix, every write inside the output directory — so the approval gate below is a scope confirmation rather than a safety one. What ran is recorded in rulesets.json and scans.json either way.

Use the workflow when you want the scan run; work the five steps below when the ruleset selection itself matters and you want to see and edit the list first.

Workflow

Follow the detailed workflow in scan-workflow.md. Summary:

StepActionGateKey Reference
1Resolve output dir, detect languages + Pro availability—Use Glob, not Bash
2Select scan mode + rulesets—rulesets.md
3Present plan, get explicit approval⛔ HARDAskUserQuestion
4Run the scans—scripts/run-scans.sh
5Post-filter, merge, report, clean up—Merge script (below)

Task enforcement: On invocation, create 5 tasks with blockedBy dependencies (each step blocks the previous). Step 3 is a HARD GATE — mark complete ONLY after user explicitly approves.

Merge command (Step 5):

# run-all
uv run --no-project {baseDir}/scripts/merge_sarif.py "$OUTPUT_DIR/raw" "$OUTPUT_DIR/results/results.sarif" \
  --scans "$OUTPUT_DIR/scans.json"

# important-only, once the JSON post-filter has run over every file in raw/
uv run --no-project {baseDir}/scripts/merge_sarif.py "$OUTPUT_DIR/raw" "$OUTPUT_DIR/results/results.sarif" \
  --important --scans "$OUTPUT_DIR/scans.json"

--scans drops the output of scans listed under .failed. A scan that died part-way may still have written a .sarif, and under --important that file has no post-filter beside it, which is an error rather than an empty filter. Without the flag one dead scan denies every healthy scan a merged result. The excluded files are named on stdout, so they can go in the report.

The post-filter reads metadata SARIF does not carry, so it cannot be re-run against the merged file; --important instead keeps the findings the JSON filter kept, matched on (rule, file, line). Without it results.sarif is unfiltered while the JSON side is not.

Workflow and agents

ComponentPurpose
scripts/run-scans.shBuilds every scan command from the approved rulesets, runs them in batches, and writes scans.json

Step 4 is a Bash call. No subagent runs any part of the scan: exit codes and finding counts are read from the processes and the JSON they wrote.

Rationalizations to Reject

ShortcutWhy It's Wrong
"User asked for scan, that's approval"Original request ≠ plan approval. Present plan, use AskUserQuestion, await explicit "yes"
"Step 3 task is blocking, just mark complete"Lying about task status defeats enforcement. Only mark complete after real approval
"I already know what they want"Assumptions cause scanning wrong directories/rulesets. Present plan for verification
"Just use default rulesets"User must see and approve exact rulesets before scan
"Add extra rulesets without asking"Modifying approved list without consent breaks trust
"Third-party rulesets are optional"Trail of Bits, 0xdea, Decurity catch vulnerabilities not in official registry — REQUIRED
"Use --config auto"Sends metrics; less control over rulesets
"I'll just run the semgrep commands myself"run-scans.sh is what enforces --metrics=off, the --include rule and the output-directory --exclude. Hand-written commands drop them silently
"The script failed, I'll run semgrep directly to get something"A non-zero exit means no scan succeeded. Report that and stop; a hand-run subset reads as a full scan
"Some scans failed, the run still finished"failed and skipped are part of scans.json. Report them or the user reads a partial scan as a clean one
"Pro is too slow, skip --pro"Cross-file analysis catches 250% more true positives; worth the time
"Semgrep handles GitHub URLs natively"URL handling fails on repos with non-standard YAML; always clone first
"Cleanup is optional"Cloned repos pollute the user's workspace and accumulate across runs
"Use . or relative path as target"Subagents need absolute paths to avoid ambiguity
"Let the user pick an output dir later"Output directory must be resolved at Step 1, before any files are created

Reference Index

FileContent
rulesets.mdComplete ruleset catalog and selection algorithm
scan-modes.mdPre/post-filter criteria and jq commands
WorkflowPurpose
scan-workflow.mdComplete 5-step scan execution process
scripts/run-scans.shThe scan runner Step 4 calls

Success Criteria

  • Output directory resolved (user-specified or auto-incremented default)
  • All generated files stored inside $OUTPUT_DIR
  • Languages detected with file counts; Pro status checked
  • Scan mode selected by user (run all / important only)
  • Rulesets include third-party rules for all detected languages
  • User explicitly approved the scan plan (Step 3 gate passed)
  • run-scans.sh exited 0 and wrote $OUTPUT_DIR/scans.json
  • failed and skipped from scans.json are empty, or listed in the report
  • Scans marked partial in scans.json are none, or listed in the report — they ran with some of their rules failing to compile
  • Every semgrep command used --metrics=off
  • Approved plan written to $OUTPUT_DIR/rulesets.json at the Step 3 gate, and passed to the scanner unchanged
  • coveredNothing from scans.json is empty, or listed in the report
  • oversized from scans.json is empty, or listed in the report — those files exceed --max-target-bytes and no ruleset opened them
  • Raw per-scan outputs stored in $OUTPUT_DIR/raw/
  • results.sarif exists in $OUTPUT_DIR/results/ and is valid JSON
  • Important-only mode: post-filter applied before merge, merge run with --important, unfiltered results preserved in raw/
  • Results summary reported with severity and category breakdown
  • Cloned repos (if any) cleaned up from $OUTPUT_DIR/repos/

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

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.