Semgrep Rule Variant Creator

Port existing Semgrep rules to new target languages with applicability analysis and test-driven validation

Port existing Semgrep rules to new target languages with proper applicability analysis and independent test-driven validation for each language variant.

Overview

The Semgrep Rule Variant Creator plugin takes an existing Semgrep rule and one or more target languages, then generates independent rule variants for each applicable language. Each variant goes through a complete 4-phase cycle ensuring quality and correctness.

Key capabilities:

• Applicability analysis before porting
• Independent 4-phase cycle per language
• Test-first methodology for each variant
• Language-specific idiom adaptation
• Proper validation before proceeding

Installation

/plugin install trailofbits/skills/plugins/semgrep-rule-variant-creator

Prerequisites

• Semgrep installed and available in PATH
• Existing Semgrep rule to port (in YAML format)
• Target languages specified

When to Use

Use this plugin when you need to:

• Port an existing Semgrep rule to one or more target languages
• Create language-specific variants of a universal vulnerability pattern
• Expand rule coverage across a polyglot codebase
• Translate rules between languages with equivalent constructs

When NOT to Use

Do NOT use this plugin for:

• Creating a new Semgrep rule from scratch (use semgrep-rule-creator instead)
• Running existing rules against code
• Languages where the vulnerability pattern fundamentally doesn’t apply
• Minor syntax variations within the same language

Input Specification

This plugin requires:

1. Existing Semgrep rule - YAML file path or YAML rule content
2. Target languages - One or more languages to port to

Example invocations:

Port the sql-injection.yaml Semgrep rule to Go and Java

Create Semgrep rule variants of my-rule.yaml for TypeScript, Rust, and C#

Port this Semgrep rule to Golang

Output Structure

For each applicable target language, produces:

<original-rule-id>-<language>/
├── <original-rule-id>-<language>.yaml     # Ported rule
└── <original-rule-id>-<language>.<ext>    # Test file

Example Output

Input:

• Rule: python-command-injection.yaml
• Target languages: Go, Java

Output:

python-command-injection-golang/
├── python-command-injection-golang.yaml
└── python-command-injection-golang.go

python-command-injection-java/
├── python-command-injection-java.yaml
└── python-command-injection-java.java

Four-Phase Workflow

Each target language goes through an independent 4-phase cycle:

1. Phase 1: Applicability Analysis

   Determine if the vulnerability pattern applies to the target language before proceeding.

   Analysis criteria:

   • Does the vulnerability class exist in the target language?
   • Does an equivalent construct exist (function, pattern, library)?
   • Are the semantics similar enough for meaningful detection?

   Verdict options:

   • APPLICABLE → Proceed with variant creation
   • APPLICABLE_WITH_ADAPTATION → Proceed but significant changes needed
   • NOT_APPLICABLE → Skip this language, document why
2. Phase 2: Test Creation

   Write tests BEFORE the rule using target language idioms.

   Create test file with:

   • Minimum 2 vulnerable cases (ruleid:)
   • Minimum 2 safe cases (ok:)
   • Language-specific edge cases

   // ruleid: sql-injection-golang
   db.Query("SELECT * FROM users WHERE id = " + userInput)
   
   // ok: sql-injection-golang
   db.Query("SELECT * FROM users WHERE id = ?", userInput)
   
3. Phase 3: Rule Creation

   Translate the original rule to the target language.

   1. Analyze AST: semgrep --dump-ast -l <lang> test-file
   2. Translate patterns to target language syntax
   3. Update metadata: language key, message, rule ID
   4. Adapt for idioms: Handle language-specific constructs
4. Phase 4: Validation

   Validate YAML and run tests to ensure correctness.

   # Validate YAML
   semgrep --validate --config rule.yaml
   
   # Run tests
   semgrep --test --config rule.yaml test-file
   

   Checkpoint: Output MUST show All tests passed.

   For taint rule debugging:

   semgrep --dataflow-traces -f rule.yaml test-file
   

Complete the full 4-phase cycle for each language before moving to the next. Do not batch languages together.

Applicability Analysis Details

Before porting, perform thorough analysis:

Does the Vulnerability Class Exist?

Examples:

• Buffer overflow: Applies to C/C++, may apply to Rust (in unsafe blocks), does NOT apply to Python/Java
• SQL injection: Applies to any language with database access
• XSS: Applies to any language generating HTML output

Does an Equivalent Construct Exist?

Parse the original rule to identify:

• Sinks: What dangerous functions/methods does it detect?
• Sources: Where does tainted data originate?
• Pattern type: Is it taint-mode or pattern-matching?

Then research the target language:

• What are the equivalent dangerous functions?
• What are the common source patterns?
• Are there language-specific idioms to consider?

Example Analysis

Original: Python os.system(user_input)
Target: Go exec.Command(user_input)

VERDICT: APPLICABLE
REASONING: Both execute shell commands with user input. Vulnerability is
identical (command injection). Detection logic (taint from input to exec)
translates directly.

Example Variant Creation

Let’s port a Python SQL injection rule to Go:

python-sql-injection.yaml (Original)

rules:
  - id: sql-injection
    languages: [python]
    severity: ERROR
    message: SQL query constructed from user input
    mode: taint
    pattern-sources:
      - pattern: request.args.get(...)
    pattern-sinks:
      - pattern: cursor.execute($QUERY, ...)

rules:
  - id: sql-injection-golang
    languages: [go]
    severity: ERROR
    message: SQL query constructed from user input
    mode: taint
    pattern-sources:
      - pattern: r.URL.Query().Get(...)
      - pattern: r.FormValue(...)
    pattern-sinks:
      - pattern: $DB.Query($QUERY, ...)
      - pattern: $DB.Exec($QUERY, ...)

package main

import (
    "database/sql"
    "net/http"
)

func handler1(w http.ResponseWriter, r *http.Request, db *sql.DB) {
    // ruleid: sql-injection-golang
    id := r.URL.Query().Get("id")
    db.Query("SELECT * FROM users WHERE id = " + id)
}

func handler2(w http.ResponseWriter, r *http.Request, db *sql.DB) {
    // ruleid: sql-injection-golang
    id := r.FormValue("id")
    db.Exec("DELETE FROM users WHERE id = " + id)
}

func handler3(w http.ResponseWriter, r *http.Request, db *sql.DB) {
    // ok: sql-injection-golang
    id := r.URL.Query().Get("id")
    db.Query("SELECT * FROM users WHERE id = ?", id)
}

func handler4(w http.ResponseWriter, r *http.Request, db *sql.DB) {
    // ok: sql-injection-golang
    db.Query("SELECT * FROM users WHERE id = 1")
}

Key Differences from Rule Creator

Aspect	semgrep-rule-creator	semgrep-rule-variant-creator
Input	Bug pattern description	Existing rule + target languages
Output	Single rule+test	Multiple rule+test directories
Workflow	Single creation cycle	Independent cycle per language
Phase 1	Problem analysis	Applicability analysis

Rationalizations to Reject

When porting Semgrep rules, reject these common shortcuts:

Rationalization	Why It Fails	Correct Approach
”Pattern structure is identical”	Different ASTs across languages	Always dump AST for target language
”Same vulnerability, same detection”	Data flow differs between languages	Analyze target language idioms
”Rule doesn’t need tests since original worked”	Language edge cases differ	Write NEW test cases for target
”Skip applicability - it obviously applies”	Some patterns are language-specific	Complete applicability analysis first
”I’ll create all variants then test”	Errors compound, hard to debug	Complete full cycle per language
”Library equivalent is close enough”	Surface similarity hides differences	Verify API semantics match
”Just translate the syntax 1:1”	Languages have different idioms	Research target language patterns

Strictness Principles

Non-negotiable requirements:

• Applicability analysis is mandatory: Don’t assume patterns translate
• Each language is independent: Complete full cycle before moving to next
• Test-first for each variant: Never write a rule without test cases
• 100% test pass required: “Most tests pass” is not acceptable

Commands

Task	Command
Run tests	semgrep --test --config rule.yaml test-file
Validate YAML	semgrep --validate --config rule.yaml
Dump AST	semgrep --dump-ast -l <lang> <file>
Debug taint flow	semgrep --dataflow-traces -f rule.yaml file

Foundational Knowledge

The semgrep-rule-creator plugin is the authoritative reference for Semgrep rule creation fundamentals. Consult it for guidance on:

• When to use taint mode vs pattern matching
• Test-first methodology
• Anti-patterns to avoid
• Iterating until tests pass
• Rule optimization

When porting a rule, you’re applying these same principles in a new language context.

Related Plugins

• semgrep-rule-creator - Create new Semgrep rules from scratch
• static-analysis - Run existing Semgrep rules against code
• variant-analysis - Find similar vulnerabilities across codebases

Additional Resources

• Semgrep Pattern Examples - Per-language pattern references
• Semgrep Testing Rules - Testing annotations
• Trail of Bits Testing Handbook - Advanced patterns

Author

Maciej Domanski ([e-mail])