Agent skill
implementing-semgrep-for-custom-sast-rules
Write custom Semgrep SAST rules in YAML to detect application-specific vulnerabilities, enforce coding standards, and integrate into CI/CD pipelines.
Install this agent skill to your Project
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SKILL.md
Implementing Semgrep for Custom SAST Rules
Overview
Semgrep is an open-source static analysis tool that uses pattern-matching to find bugs, enforce code standards, and detect security vulnerabilities. Custom rules are written in YAML using Semgrep's pattern syntax, making it accessible without requiring compiler knowledge. It supports 30+ languages including Python, JavaScript, Go, Java, and C.
When to Use
- When deploying or configuring implementing semgrep for custom sast rules capabilities in your environment
- When establishing security controls aligned to compliance requirements
- When building or improving security architecture for this domain
- When conducting security assessments that require this implementation
Prerequisites
- Python 3.8+ or Docker
- Semgrep CLI installed
- Target codebase in a supported language
Installation
# Install via pip
pip install semgrep
# Install via Homebrew
brew install semgrep
# Run via Docker
docker run -v "${PWD}:/src" returntocorp/semgrep semgrep --config auto /src
# Verify
semgrep --version
Running Semgrep
# Auto-detect rules for your code
semgrep --config auto .
# Use Semgrep registry rules
semgrep --config r/python.lang.security
# Use custom rule file
semgrep --config my-rules.yaml .
# Use multiple configs
semgrep --config auto --config ./custom-rules/ .
# JSON output
semgrep --config auto --json . > results.json
# SARIF output for GitHub
semgrep --config auto --sarif . > results.sarif
# Filter by severity
semgrep --config auto --severity ERROR .
Writing Custom Rules
Basic Pattern Matching
# rules/sql-injection.yaml
rules:
- id: sql-injection-string-format
languages: [python]
severity: ERROR
message: |
Potential SQL injection via string formatting.
Use parameterized queries instead.
pattern: |
cursor.execute(f"..." % ...)
metadata:
cwe: ["CWE-89"]
owasp: ["A03:2021"]
category: security
fix: |
cursor.execute("SELECT * FROM users WHERE id = %s", (user_id,))
Pattern Operators
rules:
- id: hardcoded-secret-in-code
languages: [python, javascript, typescript]
severity: ERROR
message: Hardcoded secret detected in source code
patterns:
- pattern-either:
- pattern: $VAR = "..."
- pattern: $VAR = '...'
- metavariable-regex:
metavariable: $VAR
regex: (?i)(password|secret|api_key|token|aws_secret)
- pattern-not: $VAR = ""
- pattern-not: $VAR = "changeme"
- pattern-not: $VAR = "PLACEHOLDER"
metadata:
cwe: ["CWE-798"]
category: security
Taint Analysis
rules:
- id: xss-taint-tracking
languages: [python]
severity: ERROR
message: User input flows to HTML response without sanitization
mode: taint
pattern-sources:
- pattern: request.args.get(...)
- pattern: request.form.get(...)
- pattern: request.form[...]
pattern-sinks:
- pattern: return render_template_string(...)
- pattern: Markup(...)
pattern-sanitizers:
- pattern: bleach.clean(...)
- pattern: escape(...)
metadata:
cwe: ["CWE-79"]
owasp: ["A03:2021"]
Multiple Language Rule
rules:
- id: insecure-random
languages: [python, javascript, go, java]
severity: WARNING
message: |
Using insecure random number generator. Use cryptographically
secure alternatives for security-sensitive operations.
pattern-either:
# Python
- pattern: random.random()
- pattern: random.randint(...)
# JavaScript
- pattern: Math.random()
# Go
- pattern: math/rand.Intn(...)
# Java
- pattern: new java.util.Random()
metadata:
cwe: ["CWE-330"]
Enforce Coding Standards
rules:
- id: require-error-handling
languages: [go]
severity: WARNING
message: Error return value not checked
pattern: |
$VAR, _ := $FUNC(...)
fix: |
$VAR, err := $FUNC(...)
if err != nil {
return fmt.Errorf("$FUNC failed: %w", err)
}
- id: no-console-log-in-production
languages: [javascript, typescript]
severity: WARNING
message: Remove console.log before merging to production
pattern: console.log(...)
paths:
exclude:
- "tests/*"
- "*.test.*"
JWT Security Rules
rules:
- id: jwt-none-algorithm
languages: [python]
severity: ERROR
message: JWT decoded without algorithm verification - allows token forgery
patterns:
- pattern: jwt.decode($TOKEN, ..., algorithms=["none"], ...)
metadata:
cwe: ["CWE-347"]
- id: jwt-no-verification
languages: [python]
severity: ERROR
message: JWT decoded with verification disabled
patterns:
- pattern: jwt.decode($TOKEN, ..., options={"verify_signature": False}, ...)
metadata:
cwe: ["CWE-345"]
Rule Testing
# rules/test-sql-injection.yaml
rules:
- id: sql-injection-format-string
languages: [python]
severity: ERROR
message: SQL injection via format string
pattern: |
cursor.execute(f"...{$VAR}...")
# Test annotation in test file:
# test-sql-injection.py
def bad_query(user_id):
# ruleid: sql-injection-format-string
cursor.execute(f"SELECT * FROM users WHERE id = {user_id}")
def good_query(user_id):
# ok: sql-injection-format-string
cursor.execute("SELECT * FROM users WHERE id = %s", (user_id,))
# Run rule tests
semgrep --test rules/
# Test specific rule
semgrep --config rules/sql-injection.yaml --test
CI/CD Integration
GitHub Actions
name: Semgrep SAST
on: [pull_request]
jobs:
semgrep:
runs-on: ubuntu-latest
container:
image: returntocorp/semgrep
steps:
- uses: actions/checkout@v4
- name: Run Semgrep
run: |
semgrep --config auto \
--config ./custom-rules/ \
--sarif --output results.sarif \
--severity ERROR \
.
- name: Upload SARIF
uses: github/codeql-action/upload-sarif@v3
with:
sarif_file: results.sarif
GitLab CI
semgrep:
stage: test
image: returntocorp/semgrep
script:
- semgrep --config auto --config ./custom-rules/ --json --output semgrep.json .
artifacts:
reports:
sast: semgrep.json
Configuration File
# .semgrep.yaml
rules:
- id: my-org-rules
# ... rules here
# .semgrepignore
tests/
node_modules/
vendor/
*.min.js
Best Practices
- Start with auto config then add custom rules for org-specific patterns
- Test rules with
# ruleid:and# ok:annotations - Use taint mode for data flow vulnerabilities (XSS, SQLi, SSRF)
- Include metadata (CWE, OWASP) for vulnerability classification
- Provide fix suggestions with the
fixkey where possible - Exclude test files to reduce false positives
- Version control rules in a shared repository
- Run in CI as a blocking check for ERROR severity findings
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