Semgrep

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

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

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

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

Rule Creation Workflow

1. Analyse the problem - Understand the bug pattern, determine taint vs pattern approach
2. Create test cases first - Write ruleid: and ok: annotations before the rule
3. Analyse AST - Run semgrep --dump-ast to understand code structure
4. Write the rule - Start simple, iterate
5. Test until 100% pass - No "missed lines" or "incorrect lines"
6. Optimise 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

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

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 Syntax: https://semgrep.dev/docs/writing-rules/rule-syntax
• Pattern Syntax: https://semgrep.dev/docs/writing-rules/pattern-syntax
• Registry: https://semgrep.dev/explore
• Playground: https://semgrep.dev/playground
• Docs: https://semgrep.dev/docs/