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MCP server · Security

io.github.goldmembrane/codesafer

Scans AI-generated code for invisible Unicode, Trojan Source, and supply-chain threats.

Unclaimed security
37Low

Scored 6 months ago · breakdown

About io.github.goldmembrane/codesafer

io.github.goldmembrane/codesafer is an MCP server in the Security category: scans AI-generated code for invisible Unicode, Trojan Source, and supply-chain threats.

Install

Claude Code
claude mcp add io-github-goldmembrane-codesafer -- npx -y cleaner-code
npx
npx -y cleaner-code

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Tools (6)

ai_analyzeDeep AI analysis using the trained CodeBERT model (classifies chunks as malicious/benign with confidence)

Parameters not published.

check_dependenciesCheck `package.json` for typosquatting, suspicious install scripts, and dependency risks

Parameters not published.

explain_findingGet detailed explanation of a specific threat category, with attack scenarios and remediation

Parameters not published.

scan_directoryRecursively scan a directory across all source files

Parameters not published.

scan_fileScan a single file for hidden malicious code patterns

Parameters not published.

scan_rules_fileScan an AI configuration/rules file for prompt injection and Rules File Backdoor attacks

Parameters not published.

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Security checks

  • ✓README presentThe repository ships documentation.

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README

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.

npm Node

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

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About io.github.goldmembrane/codesafer

How do I install io.github.goldmembrane/codesafer?

Run claude mcp add io-github-goldmembrane-codesafer -- npx -y cleaner-code, then add the server to your MCP client's configuration.

Is io.github.goldmembrane/codesafer safe to use with an AI agent?

Its trust score is 37 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is io.github.goldmembrane/codesafer still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.