The quantum-inspired task scheduling team takes the security of our software seriously. If you believe you have found a security vulnerability, please report it to us as described below.

Please do not report security vulnerabilities through public GitHub issues.

Instead, please report them through one of the following methods:

1. GitHub Security Advisories (Preferred)

   • Visit our Security Advisories page
   • Click "Report a vulnerability"
   • Fill out the advisory form with details

2. Email

   • Send an email to: [email protected]
   • Use PGP encryption if possible (key available upon request)

3. Private Disclosure

   • Contact maintainers directly for critical vulnerabilities
   • Use secure communication channels when possible

Please include the following information in your vulnerability report:

• Description: A clear description of the vulnerability
• Impact: What could an attacker accomplish with this vulnerability?
• Reproduction: Step-by-step instructions to reproduce the issue
• Environment:
  • Operating system and version
  • Compiler version
  • LLVM/MLIR version
  • Python version (if applicable)
  • Hardware configuration (if relevant)
• Proof of Concept: Code, screenshots, or other evidence
• Suggested Fix: If you have ideas for fixing the issue

1. Acknowledgment: We will acknowledge receipt within 48 hours
2. Initial Assessment: We will assess the vulnerability within 5 business days
3. Investigation: Our security team will investigate and develop a fix
4. Coordination: We will coordinate with you on disclosure timeline
5. Release: We will release a security update and public advisory
6. Recognition: We will acknowledge your contribution (unless you prefer anonymity)

As a quantum-inspired task scheduling system, our software has unique security considerations:

• Malicious Tasks: All task inputs are validated through our QuantumValidator system
• Resource Exhaustion: Built-in limits prevent resource exhaustion attacks
• Dependency Injection: Task dependencies are validated for correctness and security
• Input Sanitization: Task IDs and metadata are sanitized to prevent injection attacks

• Quantum State Manipulation: Superposition states are protected from external interference
• Annealing Process: Temperature and iteration limits prevent infinite loops
• Population Diversity: Controls prevent exploitation of convergence algorithms
• Cache Poisoning: Cached results are cryptographically verified

• Metrics Collection: Only authorized metrics are collected and stored
• Data Privacy: Sensitive scheduling data is anonymized in logs
• Audit Trail: Complete audit trail of all security-relevant operations
• Alert System: Real-time detection of anomalous scheduling patterns

The compiler validates all inputs to prevent:

• Buffer Overflows: Bounds checking on all array operations
• Integer Overflows: Safe arithmetic operations throughout
• Format String Attacks: Parameterized logging and error messages
• Path Traversal: Sanitized file path handling

• RAII: Resource Acquisition Is Initialization throughout C++ codebase
• Smart Pointers: Automatic memory management where possible
• Bounds Checking: Array bounds validation in debug builds
• Sanitizers: Regular testing with AddressSanitizer and MemorySanitizer

While photon-mlir-bridge is not primarily a cryptographic tool:

• Secure Communications: HTTPS for all network communications
• Credential Storage: No hardcoded secrets or credentials
• Random Number Generation: Cryptographically secure randomness where needed

// Use trusted model sources
auto model = photon::loadModel("verified_model.onnx");

// Validate model before compilation
if (!photon::validateModel(model)) {
    throw std::runtime_error("Model validation failed");
}

// Use safe compilation options
photon::CompilerConfig config{
    .enable_security_checks = true,
    .validate_outputs = true,
    .sandbox_mode = true
};

// Verify hardware authentication
auto device = photon::Device::connect("lightmatter://device");
if (!device.authenticate()) {
    throw std::runtime_error("Hardware authentication failed");
}

// Use secure communication channels
device.enableTLS(true);
device.setCredentials(cert, key);

import photon_mlir as pm

# Validate input models
model = torch.load("model.pth", weights_only=True)  # Safer loading

# Use secure compilation options
compiled = pm.compile(
    model,
    target="lightmatter_envise",
    security_mode="strict",
    validate_inputs=True
)

We use multiple static analysis tools:

• CodeQL: GitHub's semantic code analysis
• Clang Static Analyzer: C++ static analysis
• cppcheck: Additional C++ checks
• Bandit: Python security analysis
• Safety: Python dependency vulnerability scanning

Runtime security testing includes:

• AddressSanitizer: Memory error detection
• MemorySanitizer: Uninitialized memory detection
• ThreadSanitizer: Race condition detection
• Fuzzing: Input validation testing

• Automated Updates: Dependabot for dependency updates
• Vulnerability Scanning: Regular security audits
• Pinned Versions: Specific dependency versions in production
• Minimal Dependencies: Reduce attack surface

• Reproducible Builds: Deterministic build process
• Signed Releases: GPG-signed release artifacts
• Build Isolation: Sandboxed build environments
• Integrity Checks: Checksums for all artifacts

Before contributing code, ensure:

• No hardcoded secrets or credentials
• Input validation for all user-provided data
• Proper error handling without information leakage
• Memory safety best practices followed
• No use of deprecated or unsafe functions
• Security tests added for new features
• Documentation includes security considerations

• Thermal Damage: Improper phase settings can cause hardware damage
• Power Limits: Exceeding power limits can damage photonic devices
• Calibration Data: Device calibration data should be protected
• Firmware Security: Hardware firmware should be kept updated

• Large Models: Very large models may cause resource exhaustion
• Complex Optimizations: Aggressive optimizations may introduce bugs
• External Tools: Dependencies on external LLVM tools

• Hardware Communication: Unsecured network protocols
• Remote Compilation: Code execution on remote systems
• Data Transmission: Sensitive model data over networks

We track security metrics including:

• Vulnerability Response Time: Time from report to fix
• Security Test Coverage: Percentage of security-relevant code tested
• Dependency Vulnerability Count: Number of known vulnerable dependencies
• Security Scanning Frequency: How often we run security scans

• OWASP Top 10
• CWE/SANS Top 25
• NIST Cybersecurity Framework
• LLVM Security

• Security Architecture
• Threat Model
• Security Testing Guide
• Incident Response Plan

We provide security updates for the current major version and the previous major version for 12 months after a new major release.

1. Assessment: Evaluate severity using CVSS scoring
2. Priority: Critical/High vulnerabilities are fixed immediately
3. Development: Fix developed and tested in isolation
4. Review: Security fixes undergo additional review
5. Release: Emergency releases for critical vulnerabilities
6. Notification: Users notified through multiple channels

For security-related questions or concerns:

• Security Team: [email protected]
• General Contact: [email protected]
• PGP Key: Available upon request

Thank you for helping keep photon-mlir-bridge and our users safe!