Semgrep Rule CreatorSAFE

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The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: semgrep-rule-creator
description: Creates custom Semgrep rules for detecting security vulnerabilities, bug patterns, and code patterns. Use when writing Semgrep rules or building custom static analysis detections.
allowed-tools:
  - Bash
  - Read
  - Write
  - Edit
  - Glob
  - Grep
  - WebFetch
---

# 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:
```yaml
# BAD: Matches any function call
pattern: $FUNC(...)

# GOOD: Specific dangerous function
pattern: eval(...)
```

**Missing safe cases in tests** - leads to undetected false positives:
```python
# 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:
```yaml
# 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](#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

```yaml
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`):
```python
# 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]({baseDir}/references/quick-reference.md).
- For detailed workflow and examples, you MUST see [workflow.md]({baseDir}/references/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 p

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

What the source does

Filesystem

none-observed

Network

none-observed

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (1)

AGENTS.md

Gates applied: no_behavioural_pass.