CodeSafer (cleaner-code)

AI code security scanner as a Model Context Protocol (MCP) server. Detects hidden threats in AI-generated code that traditional linters miss.

Website: codesafer.org  ·  MCP Clients: Claude Code, Cursor, VS Code + Copilot, Cline

Why CodeSafer?

AI coding assistants generate code fast — but who's checking it for hidden threats?

Recent supply-chain attacks show that malicious code can hide in ways human reviewers and traditional linters routinely miss:

• Invisible Unicode characters injected into identifiers (30+ variants)
• BiDi / Trojan Source attacks that reorder how code is displayed vs. executed (CVE-2021-42574)
• Homoglyphs — Cyrillic characters masquerading as Latin (CVE-2021-42694)
• Glassworm-style Unicode steganography hiding payloads in whitespace
• Rules file backdoors planted in .cursorrules, CLAUDE.md, and other AI config files
• Typosquatted dependencies in package.json
• Obfuscation patterns — eval + base64, reverse shells, packed payloads

CodeSafer scans for all of these before the code runs on your machine.

How it works

CodeSafer runs as a local MCP server. Your AI client (Claude Code, Cursor, etc.) calls its tools when reviewing or generating code, and findings are returned inline.

Hybrid detection:

1. 8 static analysis scanners — deterministic rules for known attack categories (fast, zero false-negatives on the patterns they cover).
2. CodeBERT deep analysis — transformer model classifies code chunks as malicious/benign with confidence scores. Catches obfuscated or novel patterns that static rules miss.

Nothing leaves your machine. The AI analysis runs locally against a tokenizer server.

Features

| Capability | Details | |---|---| | Invisible character detection | 30+ Unicode variants including Zero-Width Space, Mongolian Vowel Separator | | BiDi / Trojan Source | Full CVE-2021-42574 coverage | | Homoglyph detection | Cyrillic/Greek/Latin confusables (CVE-2021-42694) | | Unicode steganography | Glassworm-style whitespace payloads | | Rules file backdoors | Scans .cursorrules, CLAUDE.md, .claude/, Cursor rules | | Dependency scanning | Typosquatting + suspicious install scripts in package.json | | Obfuscation detection | eval + base64, reverse shells, packed payloads | | AI deep analysis | CodeBERT transformer classifier with confidence scores | | MCP native | 6 MCP tools, stdio transport | | Local-first | No code uploaded — runs entirely on your machine |

MCP Tools

CodeSafer exposes six tools to your MCP client:

| Tool | Purpose | |---|---| | scan_file | Scan a single file for hidden malicious code patterns | | scan_directory | Recursively scan a directory across all source files | | scan_rules_file | Scan an AI configuration/rules file for prompt injection and Rules File Backdoor attacks | | check_dependencies | Check package.json for typosquatting, suspicious install scripts, and dependency risks | | ai_analyze | Deep AI analysis using the trained CodeBERT model (classifies chunks as malicious/benign with confidence) | | explain_finding | Get detailed explanation of a specific threat category, with attack scenarios and remediation |

Installation

Prerequisites

• Node.js 18 or later
• An MCP-compatible client (Claude Code, Cursor, VS Code + Copilot, Cline)

From source

git clone https://github.com/goldmembrane/cleaner-code.git
cd cleaner-code
npm install
npm run build

Configure your MCP client

Claude Code (~/.claude.json or project .mcp.json):

{
  "mcpServers": {
    "codesafer": {
      "command": "node",
      "args": ["/absolute/path/to/cleaner-code/dist/index.js"]
    }
  }
}

Cursor (.cursor/mcp.json):

{
  "mcpServers": {
    "codesafer": {
      "command": "node",
      "args": ["/absolute/path/to/cleaner-code/dist/index.js"]
    }
  }
}

Restart your client, and CodeSafer tools will appear in the tool picker.

Usage

Once configured, ask your AI client things like:

• "Scan this file for hidden security issues."
• "Check the dependencies in package.json for typosquatting."
• "Scan .cursorrules for a rules-file backdoor."
• "Run a deep AI analysis of src/auth.ts."
• "Explain what a Trojan Source attack is and how to fix the finding above."

The client will call the appropriate MCP tool and return findings with severity, line numbers, and remediation guidance.

Free tier & Plans

CodeSafer is free to use. Static analysis (scan_file, scan_directory, scan_rules_file, check_dependencies, explain_finding) has no limits.

AI deep analysis (ai_analyze) includes 10 free runs per session. Paid plans for higher AI quotas are available at codesafer.org.

Detection categories

CodeSafer detects threats across 9 categories:

1. Invisible Unicode characters — 30+ variants including Zero-Width Space, Zero-Width Joiner
2. BiDi / Trojan Source attacks — CVE-2021-42574
3. Homoglyphs — Cyrillic/Greek characters masquerading as Latin (CVE-2021-42694)
4. Unicode steganography — Glassworm patterns in whitespace
5. Rules file backdoors — malicious instructions in .cursorrules, CLAUDE.md, etc.
6. Dependency risks — typosquatting and suspicious install scripts
7. Obfuscation patterns — eval + base64, packed payloads, reverse shells
8. Static analysis findings — 8 deterministic scanners
9. AI deep analysis — CodeBERT transformer for novel and obfuscated threats

Project structure

cleaner-code/
├── src/
│   ├── index.ts           # MCP server entry point
│   ├── api-server.ts      # Optional HTTP API server
│   ├── types.ts           # Scanner interfaces
│   ├── utils.ts           # File collection, summary formatting
│   └── scanner/
│       ├── invisible.ts       # Invisible Unicode scanner
│       ├── bidi.ts            # BiDi / Trojan Source scanner
│       ├── homoglyph.ts       # Homoglyph scanner
│       ├── encoding.ts        # Encoding / charset scanner
│       ├── obfuscation.ts     # Obfuscation pattern scanner
│       ├── steganography.ts   # Unicode steganography scanner
│       ├── rules-backdoor.ts  # Rules file backdoor scanner
│       ├── dependency.ts      # Dependency risk scanner
│       └── ai-analyzer.ts     # CodeBERT deep analyzer
├── ml/                    # ML model assets and tokenizer
├── functions/             # Cloud function deployments
├── deploy/                # Deployment manifests
└── web/                   # Landing page assets

License

ISC — see the LICENSE file for details.

Links

• Website: codesafer.org
• Model Context Protocol: modelcontextprotocol.io
• Report issues: GitHub Issues