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Политика конфиденциальностиСогласие на обработку ПДн|ИНН 623412173261
    Semgrep — Скилл для ИИ-агентов | AI Рассвет

    Semgrep

    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.

    Скиллы для разработки#GitHub#trailofbits/skills#skills.sh
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    Установить скилл

    Добавьте инструмент одной командой или скачайте проверенный архив версии.

    npx skills add trailofbits/skills --skill semgrep
    Скачать ZIP
    Версия
    1.0.0+d3323cefbcf6
    Автор
    Владимир Ломтев
    Репозиторий
    trailofbits/skills
    GitHub: trailofbits/skills

    Как установить

    1. 1Скопируйте команду из блока установки.
    2. 2Запустите её в терминале из каталога проекта.

    Документация

    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.

    Mode Coverage Findings Reported
    Run all All rulesets, all severity levels Everything
    Important only All rulesets, pre- and post-filtered Security 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:

    Step Action Gate Key Reference
    1 Resolve output dir, detect languages + Pro availability — Use Glob, not Bash
    2 Select scan mode + rulesets — rulesets.md
    3 Present plan, get explicit approval ⛔ HARD AskUserQuestion
    4 Run the scans — scripts/run-scans.sh
    5 Post-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

    Component Purpose
    scripts/run-scans.sh Builds 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

    Shortcut Why 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

    File Content
    rulesets.md Complete ruleset catalog and selection algorithm
    scan-modes.md Pre/post-filter criteria and jq commands
    Workflow Purpose
    scan-workflow.md Complete 5-step scan execution process
    scripts/run-scans.sh The 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
    • 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/

    Требования и возможности

    Источник пакета
    https://github.com/trailofbits/skills/tree/d3323cefbcf645678b8dc481de204b02ad3d02dc/plugins/static-analysis/skills/semgrep

    Файлы версии

    ПутьРазмерSHA256
    SKILL.md1553104df36a7685632ee...
    agents/openai.yaml12811a851b1841f3e82...
    assets/trail-of-bits-mark.svg30844bf74c789b38dcf6...
    references/rulesets.md7695e641bf7b2f32cd81...
    references/scan-modes.md70116450b636217ae7af...

    Частые вопросы

    Как установить Semgrep?
    Используйте команду npx skills add trailofbits/skills --skill semgrep или скачайте ZIP-архив.
    Можно ли скачать Semgrep бесплатно?
    Да, опубликованную версию можно скачать из маркетплейса бесплатно.

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    Установить скилл

    Добавьте инструмент одной командой или скачайте проверенный архив версии.

    npx skills add trailofbits/skills --skill semgrep
    Скачать ZIP
    Версия
    1.0.0+d3323cefbcf6
    Автор
    Владимир Ломтев
    Репозиторий
    trailofbits/skills
    GitHub: trailofbits/skills
    Self Improving AgentCaptures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.