
Codesafer
io.github.goldmembrane由 GitHub 账号 goldmembrane 发布v1.0.1更新于 Oct 24, 2026
Scans AI-generated code for invisible Unicode, Trojan Source, and supply-chain threats.
概览
在本地扫描 AI 生成的代码和 AI 规则文件,发现隐藏 Unicode、Trojan Source、同形字、混淆和依赖威胁。
- 可以做什么
- CodeSafer 是一个本地 MCP 服务器,提供六个工具:scan_file、scan_directory、scan_rules_file、check_dependencies、ai_analyze 和 explain_finding。它结合八个针对已知攻击类别的确定性静态扫描器,以及一个 CodeBERT 变换器分类器,用于将代码片段判定为恶意或良性。结果以内联方式返回,包含严重程度、行号和修复建议,同时还会检查 .cursorrules、CLAUDE.md 等 AI 配置文件是否被植入后门。
- 适用场景
- 当助手编写或审查代码,而你希望在代码运行前做一次安全检查时使用,尤其针对隐藏 Unicode、BiDi/Trojan Source、同形字、隐写、混淆和仿冒依赖风险。它也适合审计 AI 规则和配置文件是否被注入指令。
- 运行要求
- 需要 Node.js 18 或更高版本,以及兼容 MCP 的客户端,例如 Claude Code、Cursor、VS Code + Copilot 或 Cline。它以本地 stdio 进程运行,通常用 node 指向构建后的入口文件启动。未声明任何账户、API 密钥、环境变量或请求头。
安装
在 SourceWeft 中
- 打开 控制台中的 Codesafer,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
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.
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:
- 8 static analysis scanners — deterministic rules for known attack categories (fast, zero false-negatives on the patterns they cover).
- 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
MCP Tools
CodeSafer exposes six tools to your MCP client:
Installation
Prerequisites
- Node.js 18 or later
- An MCP-compatible client (Claude Code, Cursor, VS Code + Copilot, Cline)
From source
Configure your MCP client
Claude Code (~/.claude.json or project .mcp.json):
Cursor (.cursor/mcp.json):
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
.cursorrulesfor 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:
- Invisible Unicode characters — 30+ variants including Zero-Width Space, Zero-Width Joiner
- BiDi / Trojan Source attacks — CVE-2021-42574
- Homoglyphs — Cyrillic/Greek characters masquerading as Latin (CVE-2021-42694)
- Unicode steganography — Glassworm patterns in whitespace
- Rules file backdoors — malicious instructions in
.cursorrules,CLAUDE.md, etc. - Dependency risks — typosquatting and suspicious install scripts
- Obfuscation patterns —
eval+ base64, packed payloads, reverse shells - Static analysis findings — 8 deterministic scanners
- AI deep analysis — CodeBERT transformer for novel and obfuscated threats
Project structure
License
ISC — see the LICENSE file for details.
Links
- Website: codesafer.org
- Model Context Protocol: modelcontextprotocol.io
- Report issues: GitHub Issues
来源:README.md,提交 1fee55e
工具
0版本历史
1- v1.0.1最新Sep 16, 2026
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