SKILL.md

Semgrep Rule Creator

Create production-quality Semgrep rules with proper testing and validation.

When to Use

Ideal scenarios:

Writing Semgrep rules for specific bug patterns

Writing rules to detect security vulnerabilities in your codebase

Writing taint mode rules for data flow vulnerabilities

Writing rules to enforce coding standards

When NOT to Use

Do NOT use this skill for:

Running existing Semgrep rulesets

General static analysis without custom rules (use static-analysis skill)

Rationalizations to Reject

When writing Semgrep rules, reject these common shortcuts:

"The pattern looks complete" → Still run semgrep --test --config <rule-id>.yaml <rule-id>.<ext> to verify. Untested rules have hidden false positives/negatives.

"It matches the vulnerable case" → Matching vulnerabilities is half the job. Verify safe cases don't match (false positives break trust).

"Taint mode is overkill for this" → If data flows from user input to a dangerous sink, taint mode gives better precision than pattern matching.

"One test is enough" → Include edge cases: different coding styles, sanitized inputs, safe alternatives, and boundary conditions.

"I'll optimize the patterns first" → Write correct patterns first, optimize after all tests pass. Premature optimization causes regressions.

"The AST dump is too complex" → The AST reveals exactly how Semgrep sees code. Skipping it leads to patterns that miss syntactic variations.

Anti-Patterns

Too broad - matches everything, useless for detection:

# BAD: Matches any function call

pattern: $FUNC(...)

# GOOD: Specific dangerous function

pattern: eval(...)

Missing safe cases in tests - leads to undetected false positives:

# BAD: Only tests vulnerable case

# ruleid: my-rule

dangerous(user_input)

# GOOD: Include safe cases to verify no false positives

# ruleid: my-rule

dangerous(user_input)

# ok: my-rule

dangerous(sanitize(user_input))

# ok: my-rule

dangerous("hardcoded_safe_value")

Overly specific patterns - misses variations:

# BAD: Only matches exact format

pattern: os.system("rm " + $VAR)

# GOOD: Matches all os.system calls with taint tracking

mode: taint

pattern-sources:

  - pattern: input(...)

pattern-sinks:

  - pattern: os.system(...)

Strictness Level

This workflow is strict - do not skip steps:

Read documentation first: See [Documentation](#documentation) before writing Semgrep rules

Test-first is mandatory: Never write a rule without tests

100% test pass is required: "Most tests pass" is not acceptable

Optimization comes last: Only simplify patterns after all tests pass

Avoid generic patterns: Rules must be specific, not match broad patterns

Prioritize taint mode: For data flow vulnerabilities

One YAML file - one Semgrep rule: Each YAML file must contain only one Semgrep rule; don't combine multiple rules in a single file

No generic rules: When targeting a specific language for Semgrep rules - avoid generic pattern matching (languages: generic)

**Forbidden todook and todoruleid test annotations**: todoruleid: <rule-id> and todook: <rule-id> annotations in tests files for future rule improvements are forbidden

Overview

This skill guides creation of Semgrep rules that detect security vulnerabilities and code patterns. Rules are created iteratively: analyze the problem, write tests first, analyze AST structure, write the rule, iterate until all tests pass, optimize the rule.

Approach selection:

Taint mode (prioritize): Data flow issues where untrusted input reaches dangerous sinks

Pattern matching: Simple syntactic patterns without data flow requirements

Why prioritize taint mode? Pattern matching finds syntax but misses context. A pattern eval($X) matches both eval(user_input) (vulnerable) and eval("safe_literal") (safe). Taint mode tracks data flow, so it only alerts when untrusted data actually reaches the sink—dramatically reducing false positives for injection vulnerabilities.

Iterating between approaches: It's okay to experiment. If you start with taint mode and it's not working well (e.g., taint doesn't propagate as expected, too many false positives/negatives), switch to pattern matching. Conversely, if pattern matching produces too many false positives on safe cases, try taint mode instead. The goal is a working rule—not rigid adherence to one approach.

Output structure - exactly 2 files in a directory named after the rule-id:

<rule-id>/

├── <rule-id>.yaml     # Semgrep rule

└── <rule-id>.<ext>    # Test file with ruleid/ok annotations

Quick Start

rules:

  - id: insecure-eval

    languages: [python]

    severity: HIGH

    message: User input passed to eval() allows code execution

    mode: taint

    pattern-sources:

      - pattern: request.args.get(...)

    pattern-sinks:

      - pattern: eval(...)

Test file (insecure-eval.py):

# ruleid: insecure-eval

eval(request.args.get('code'))

# ok: insecure-eval

eval("print('safe')")

Run tests (from rule directory): semgrep --test --config <rule-id>.yaml <rule-id>.<ext>

Quick Reference

For commands, pattern operators, and taint mode syntax, see quick-reference.md.

For detailed workflow and examples, you MUST see workflow.md

Workflow

Copy this checklist and track progress:

Semgrep Rule Progress:

- [ ] Step 1: Analyze the Problem

- [ ] Step 2: Write Tests First

- [ ] Step 3: Analyze AST structure

- [ ] Step 4: Write the rule

- [ ] Step 5: Iterate until all tests pass (semgrep --test)

- [ ] Step 6: Optimize the rule (remove redundancies, re-test)

- [ ] Step 7: Final Run