Imported from wilsan007/odf-vERSION-7 (.claude/agents/semgrep-rule-creator/SKILL.md). Install upstream with npx skills add wilsan007/odf-vERSION-7 --skill semgrep-rule-creator. Copyright stays with the author.

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-sinks:
  - pattern: os.system(...)

Strictness Level

This workflow is strict - do not skip steps:

Read documentation first: See 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

Documentation

REQUIRED: Before writing any rule, use WebFetch to read all of these 4 links with Semgrep documentation:

Limitations

Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

semgrep-rule-creator

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