Brain Emulation is currently in research phase (pre-v1.0). While we take security seriously, this project is intended for educational and research purposes, not production deployment.
| Version | Supported | Status |
|---|---|---|
| main | ✅ | Active development |
| < 1.0 | ❌ | Pre-release, no security guarantees |
Note: Once v1.0 is released, we will establish a formal security update policy.
We appreciate responsible disclosure of security vulnerabilities. Please do not open public GitHub issues for security concerns.
Email: security@todosloscobardesdelvalle.com
Subject Line: [SECURITY] Brain Emulation - Brief Description
Please provide:
- Description: Clear description of the vulnerability
- Impact: What could an attacker achieve?
- Reproduction Steps: Step-by-step instructions to reproduce
- Affected Components: Which files/modules are affected
- Suggested Fix (optional): If you have ideas for mitigation
- Your Contact Info: For follow-up questions
Subject: [SECURITY] Brain Emulation - WebSocket Command Injection
Description:
The WebSocket server in server.py does not validate command types,
allowing arbitrary JSON commands to be executed.
Impact:
An attacker could inject malicious commands to manipulate network
parameters or cause denial of service.
Reproduction:
1. Connect to WebSocket server at ws://localhost:9001
2. Send: {"cmd": "__import__", "value": "os"}
3. Server executes arbitrary Python code
Affected Components:
- server.py, lines 238-350 (WebSocket handler)
Suggested Fix:
Implement command whitelist and JSON schema validation.
- Acknowledgment: Within 48 hours of report
- Initial Assessment: Within 1 week
- Fix Development: Depends on severity (see below)
- Public Disclosure: 90 days after patch release (coordinated disclosure)
| Severity | Fix Timeline | Example |
|---|---|---|
| Critical | 7 days | Remote code execution, data exfiltration |
| High | 30 days | Authentication bypass, privilege escalation |
| Medium | 60 days | Information disclosure, denial of service |
| Low | 90 days | Minor configuration issues, non-exploitable bugs |
✅ What We Have:
- WebSocket server with localhost binding by default
- Basic input validation for network parameters
- JSON message format for structured communication
❌ What We're Missing (known limitations):
- No authentication mechanism for WebSocket connections
- No rate limiting for commands
- No encryption for WebSocket traffic (use WSS in production)
- No input sanitization for JSON commands
- No audit logging
- No session management
This project is a research tool with the following security limitations:
-
No Authentication: WebSocket server accepts all connections
- Risk: Anyone on localhost can connect and control the simulation
- Mitigation: Do not expose the server to untrusted networks
-
No Input Validation: Commands are not fully validated
- Risk: Malformed JSON could crash the server
- Mitigation: Use only trusted clients
-
No Rate Limiting: No protection against DoS attacks
- Risk: Rapid command injection could overwhelm the server
- Mitigation: Deploy behind a proxy with rate limiting
-
No Encryption: Data transmitted in plaintext
- Risk: Network eavesdropping possible
- Mitigation: Use WSS (WebSocket Secure) for sensitive deployments
What we protect against:
- Accidental misconfigurations
- Basic input validation errors
- Unintended network exposure
What we DON'T protect against (not in scope for research phase):
- Determined attackers with network access
- Insider threats
- Social engineering
- Physical access attacks
- Supply chain attacks
If you must deploy this in a less-trusted environment:
# Bind only to localhost (default)
# server.py line 397: websockets.serve(handler, "127.0.0.1", 9001)
# Do NOT expose to 0.0.0.0 without authenticationimport ssl
ssl_context = ssl.SSLContext(ssl.PROTOCOL_TLS_SERVER)
ssl_context.load_cert_chain('cert.pem', 'key.pem')
await websockets.serve(handler, "127.0.0.1", 9001, ssl=ssl_context)from collections import defaultdict
import time
rate_limiter = defaultdict(list)
def check_rate_limit(client_id, max_requests=10, window=1.0):
now = time.time()
# Remove old requests outside window
rate_limiter[client_id] = [t for t in rate_limiter[client_id] if now - t < window]
if len(rate_limiter[client_id]) >= max_requests:
return False # Rate limit exceeded
rate_limiter[client_id].append(now)
return Trueimport secrets
API_KEYS = {"your-secret-key-here"}
async def authenticate(websocket):
auth_msg = await websocket.recv()
auth_data = json.loads(auth_msg)
return auth_data.get("api_key") in API_KEYSPlanned security improvements for future versions:
- JSON schema validation for all commands
- Rate limiting implementation
- Basic API key authentication
- Audit logging for all commands
- WSS (TLS/SSL) support
- Session management
- Role-based access control (RBAC)
- Full input sanitization
- Security documentation and threat modeling
- JWT-based authentication
- OAuth2 integration
- Intrusion detection system
- Security audit trail
- Automated vulnerability scanning
We follow a coordinated disclosure policy:
- Report received → We acknowledge within 48 hours
- Vulnerability confirmed → We develop a fix
- Patch released → We notify you before public release
- Public disclosure → 90 days after patch, or earlier with agreement
Security researchers who responsibly disclose vulnerabilities will be:
- Credited in CONTRIBUTORS.md (with permission)
- Acknowledged in release notes
- Listed in a Security Hall of Fame (coming soon)
If you're using this project:
✅ Do:
- Run the server on localhost only
- Use trusted networks
- Keep dependencies updated (
pip install --upgrade) - Review code before running
❌ Don't:
- Expose the WebSocket server to the internet
- Use this in production systems
- Process untrusted user input
- Connect to untrusted WebSocket servers
✅ Do:
- Validate all inputs
- Use parameterized queries (if adding database)
- Follow principle of least privilege
- Add tests for security-critical code
- Use safe deserialization methods
❌ Don't:
- Use
eval()orexec()on user input - Trust client-side validation alone
- Store secrets in code or git
- Ignore security warnings from tools
We use automated tools to monitor dependencies:
- Dependabot: Automated dependency updates
- Safety: Python dependency vulnerability scanner
- Bandit: Python code security scanner
See .github/workflows/test.yml for our CI/CD security checks.
For security questions (non-vulnerability):
- Open a GitHub Discussion: https://github.com/Zae-Project/brain-emulation/discussions
- Tag with
securitylabel
For vulnerabilities:
Last Updated: January 22, 2026 Version: 1.0.0 Next Review: March 2026