semgrep-rule-creator

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: # 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 " + $VAR) # GOOD: Matches all os.system calls with taint tracking mode: taint pattern-sources: - pattern: input(...) pattern-sinks: - pattern: os.system(...) Strictness Level This workflow is strict - do not skip steps: Read documentation first : See Documentation before writing Semgrep rules Test-first is mandatory : Never write a rule without tests 100% test pass is required : "Most tests pass" is not acceptable Optimization comes last : Only simplify patterns after all tests pass Avoid generic patterns : Rules must be specific, not match broad patterns Prioritize taint mode : For data flow vulnerabilities One YAML file - one Semgrep rule : Each YAML file must contain only one Semgrep rule; don't combine multiple rules in a single file No generic rules : When targeting a specific language for Semgrep rules - avoid generic pattern matching ( languages: generic ) Forbidden todook and todoruleid test annotations : todoruleid: <rule-id> and todook: <rule-id> annotations in tests files for future rule improvements are forbidden Overview This skill guides creation of Semgrep rules that detect security vulnerabilities and code patterns. Rules are created iteratively: analyze the problem, write tests first, analyze AST structure, write the rule, iterate until all tests pass, optimize the rule. Approach selection: Taint mode (prioritize): Data flow issues where untrusted input reaches dangerous sinks Pattern matching : Simple syntactic patterns without data flow requirements Why prioritize taint mode? Pattern matching finds syntax but misses context. A pattern eval($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 7 links with Semgrep documentation: Rule Syntax Pattern Syntax Testing Rules Taint analysis Advanced techniques for taint analysis Constant propagation Trail of Bits Testing Handbook - Semgrep chapter