Local MCP server scanning AI-generated code for hidden security threats using static rules and CodeBERT AI analysis.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
One-click editor setup isnβt available for this listing yet β we donβt have a confirmed install command, and weβd rather show nothing than point your editor at the wrong package or host. Follow the projectβs own setup instructions, linked above.
Inspect callable tools, capabilities, and parameters exposed to AI agents by 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 Β Β·Β MCP Clients: Claude Code, Cursor, VS Code + Copilot, Cline
AI coding assistants generate code fast β 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:
.cursorrules, CLAUDE.md, and other AI config filespackage.jsoneval + base64, reverse shells, packed payloadsCodeSafer scans for all of these before the code runs on your machine.
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:
Nothing leaves your machine. The AI analysis runs locally against a tokenizer server.
| 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 β runs entirely on your machine |
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 |
Claude Code (~/.claude.json or project .mcp.json):
Cursor (.cursor/mcp.json):
Restart your client, and CodeSafer tools will appear in the tool picker.
Once configured, ask your AI client things like:
.cursorrules for a rules-file backdoor."src/auth.ts."The client will call the appropriate MCP tool and return findings with severity, line numbers, and remediation guidance.
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.
CodeSafer detects threats across 9 categories:
.cursorrules, CLAUDE.md, etc.eval + base64, packed payloads, reverse shellsISC β see the LICENSE file for details.
Factual signals from GitHub, npm, and our automated checks β not a rating.
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