semgrep
Run Semgrep static analysis scans and create custom detection rules. Use when asked to scan code with Semgrep, find security vulnerabilities, write custom YAML rules, or detect specific bug patterns. IMPORTANT: Also use when users ask to 'scan for bugs', 'check code quality', 'find vulnerabilities', or 'audit this code' - even without naming Semgrep. Pattern-based scanning across 30+ languages.
- License 许可
- MIT
- 最近更新
- 2026-11-02
- Stars
- ★ 0
- Forks
- 0
01 前言 Front Matter
- name
- semgrep
- description
- Run Semgrep static analysis scans and create custom detection rules. Use when asked to scan code with Semgrep, find security vulnerabilities, write custom YAML rules, or detect specific bug patterns. IMPORTANT: Also use when users ask to 'scan for bugs', 'check code quality', 'find vulnerabilities', or 'audit this code' - even without naming Semgrep. Pattern-based scanning across 30+ languages.
02 资源文件 3
- 参考文档README.md3.2 KB
- 参考文档references/quick-reference.md7.1 KB
- 参考文档references/workflow.md9.0 KB
03 SKILL.md 正文
Semgrep Static Analysis
Fast, pattern-based static analysis for security scanning and custom rule creation.
MCP Tools Available
If Semgrep MCP tools are available in your environment, prefer them for scanning:
semgrep_scan— Scan code files for security vulnerabilities using built-in rulesets. Pass absolute file paths and an optional config (e.g.,p/security-audit,auto).semgrep_scan_with_custom_rule— Scan code with a custom YAML rule you've written. Pass code content inline along with the rule.semgrep_findings— Fetch existing findings from the Semgrep AppSec Platform for a repository.semgrep_rule_schema— Get the full schema for writing Semgrep rules.get_supported_languages— List all languages Semgrep supports.
When MCP tools aren't available, fall back to the CLI commands below.
When to Use Semgrep
Ideal scenarios:
- Quick security scans (minutes, not hours)
- Pattern-based bug and vulnerability detection
- Enforcing coding standards and best practices
- Finding known vulnerability patterns (OWASP, CWE)
- Creating custom detection rules for your codebase
- Data flow analysis with taint mode
Installation (CLI)
# pip (recommended)
python3 -m pip install semgrep
# Homebrew
brew install semgrep
# Docker
docker run --rm -v "${PWD}:/src" semgrep/semgrep semgrep --config auto /src
Part 1: Running Scans
Quick Scan
semgrep --config auto . # Auto-detect rules
Using Rulesets
semgrep --config p/<RULESET> . # Single ruleset
semgrep --config p/security-audit --config p/trailofbits . # Multiple
| Ruleset | Description |
|---|---|
p/default |
General security and code quality |
p/security-audit |
Comprehensive security rules |
p/owasp-top-ten |
OWASP Top 10 vulnerabilities |
p/cwe-top-25 |
CWE Top 25 vulnerabilities |
p/trailofbits |
Trail of Bits security rules |
p/python |
Python-specific |
p/javascript |
JavaScript-specific |
p/golang |
Go-specific |
Output Formats
semgrep --config p/security-audit --sarif -o results.sarif . # SARIF
semgrep --config p/security-audit --json -o results.json . # JSON
Scan Specific Paths
semgrep --config p/python app.py # Single file
semgrep --config p/javascript src/ # Directory
semgrep --config auto --include='**/test/**' . # Include tests
Configuration
.semgrepignore
tests/fixtures/
**/testdata/
generated/
vendor/
node_modules/
Suppress False Positives
password = get_from_vault() # nosemgrep: hardcoded-password
dangerous_but_safe() # nosemgrep
Part 2: Creating Custom Rules
When to Create Custom Rules
- Detecting project-specific vulnerability patterns
- Enforcing internal coding standards
- Building security checks for custom frameworks
- Creating taint-mode rules for data flow analysis
Approach Selection
| Approach | Use When |
|---|---|
| Taint mode | Data flows from untrusted source to dangerous sink (injection vulnerabilities) |
| Pattern matching | Syntactic patterns without data flow requirements (deprecated APIs, hardcoded values) |
Prioritize taint mode for injection vulnerabilities. Pattern matching alone can't distinguish between eval(user_input) (vulnerable) and eval("safe_literal") (safe).
Quick Start: Pattern Matching
rules:
- id: hardcoded-password
languages: [python]
message: "Hardcoded password detected: $PASSWORD"
severity: ERROR
pattern: password = "$PASSWORD"
Quick Start: Taint Mode
rules:
- id: command-injection
languages: [python]
message: User input flows to command execution
severity: ERROR
mode: taint
pattern-sources:
- pattern: request.args.get(...)
- pattern: request.form[...]
pattern-sinks:
- pattern: os.system(...)
- pattern: subprocess.call($CMD, shell=True, ...)
pattern-sanitizers:
- pattern: shlex.quote(...)
Pattern Syntax Quick Reference
| Syntax | Description | Example |
|---|---|---|
... |
Match anything | func(...) |
$VAR |
Capture metavariable | $FUNC($INPUT) |
<... ...> |
Deep expression match | <... user_input ...> |
| Operator | Description |
|---|---|
pattern |
Match exact pattern |
patterns |
All must match (AND) |
pattern-either |
Any matches (OR) |
pattern-not |
Exclude matches |
pattern-inside |
Match only inside context |
pattern-not-inside |
Match only outside context |
metavariable-regex |
Regex on captured value |
Testing Rules
Test-first is mandatory. Create test files with annotations:
# test_rule.py
def test_vulnerable():
user_input = request.args.get("id")
# ruleid: my-rule-id
cursor.execute("SELECT * FROM users WHERE id = " + user_input)
def test_safe():
user_input = request.args.get("id")
# ok: my-rule-id
cursor.execute("SELECT * FROM users WHERE id = ?", (user_input,))
Run tests:
semgrep --test --config rule.yaml test-file
Command Reference
| Task | Command |
|---|---|
| Run tests | semgrep --test --config rule.yaml test-file |
| Validate YAML | semgrep --validate --config rule.yaml |
| Dump AST | semgrep --dump-ast -l <lang> <file> |
| Debug taint flow | semgrep --dataflow-traces -f rule.yaml file |
Rule Creation Workflow
- Analyze the problem - Understand the bug pattern, determine taint vs pattern approach
- Create test cases first - Write
ruleid:andok:annotations before the rule - Analyze AST - Run
semgrep --dump-astto understand code structure - Write the rule - Start simple, iterate
- Test until 100% pass - No "missed lines" or "incorrect lines"
- Optimize patterns - Remove redundancies only after tests pass
Output structure:
<rule-id>/
├── <rule-id>.yaml # Semgrep rule
└── <rule-id>.<ext> # Test file
Detailed References
Official Semgrep Documentation:
- Rule Syntax - Complete YAML structure, operators, and options
- Rule Schema - Full JSON schema specification
Local References:
- Workflow Guide - Complete step-by-step rule creation process
- Quick Reference - Pattern operators and taint components
Anti-Patterns to Avoid
Too broad:
# BAD: Matches any function call
pattern: $FUNC(...)
# GOOD: Specific dangerous function
pattern: eval(...)
Missing safe cases:
# BAD: Only tests vulnerable case
# ruleid: my-rule
dangerous(user_input)
# GOOD: Include safe cases
# ruleid: my-rule
dangerous(user_input)
# ok: my-rule
dangerous(sanitize(user_input))
Rationalizations to Reject
| Shortcut | Why It's Wrong |
|---|---|
| "Semgrep found nothing, code is clean" | Semgrep is pattern-based; can't track complex cross-function data flow |
| "The pattern looks complete" | Untested rules have hidden false positives/negatives |
| "It matches the vulnerable case" | Matching vulnerabilities is half the job; verify safe cases don't match |
| "Taint mode is overkill" | For injection vulnerabilities, taint mode gives better precision |
| "One test case is enough" | Include edge cases: different coding styles, sanitized inputs, safe alternatives |
CI/CD Integration
GitHub Actions
name: Semgrep
on:
push:
branches: [main]
pull_request:
schedule:
- cron: '0 0 1 * *'
jobs:
semgrep:
runs-on: ubuntu-latest
container:
image: returntocorp/semgrep
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Run Semgrep
run: |
if [ "${{ github.event_name }}" = "pull_request" ]; then
semgrep ci --baseline-commit ${{ github.event.pull_request.base.sha }}
else
semgrep ci
fi
env:
SEMGREP_RULES: >-
p/security-audit
p/owasp-top-ten
p/trailofbits
Resources
Rule Writing:
- Rule Syntax: https://semgrep.dev/docs/writing-rules/rule-syntax
- Pattern Syntax: https://semgrep.dev/docs/writing-rules/pattern-syntax
- Rule Schema: https://github.com/semgrep/semgrep-interfaces/blob/main/rule_schema_v1.yaml
General:
- Registry: https://semgrep.dev/explore
- Playground: https://semgrep.dev/playground
- Docs: https://semgrep.dev/docs/
- Trail of Bits Rules: https://github.com/trailofbits/semgrep-rules
04 同仓库更多 Skills
clarify-requirements
Resolve genuine pre-execution ambiguity by scanning repo context, generating 1-6 grounded options, and asking 1-3 focused questions via AskUserQuestion. NOT for mid-task use (injection risk); NOT when the goal is already unambiguous; use to disambiguate vague prompts before any file edits.
openmm-md
Run FREE, open-source, Windows-native GPU molecular dynamics via the openmm-md MCP (OpenMM + CUDA on the local NVIDIA GPU). Use for protein / protein-ligand MD when you want a free stack or are on Windows without a Schrodinger license. Covers the full workflow (prepare, solvate, minimize, equilibrate, production, analyze, mmgbsa) AND an honest decision guide vs Schrodinger Desmond, including how to run Desmond legitimately on Linux or a cloud GPU with a real license. This is a deliberately LESSER free alternative and does NOT replace the schrodinger MCP tools. Do NOT use it to pick a free tool when a validated FEP+, WaterMap, IFD-MD, or Prime MM-GBSA result is actually required.
visual-review
Take screenshots of web pages and UI using Playwright for visual review and iteration
status
Diagnostic status report — shows metaswarm installation state, project setup, and potential issues
start
Use when starting work on any task, when the user mentions metaswarm, or when the user wants to begin tracked development work
setup
Interactive project setup — detects your project, configures metaswarm, writes project-local files