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SECURITY.md

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Security Policy

Supported Versions

Version Supported
0.1.x ✅

Reporting a Vulnerability

The COOLJAPAN ecosystem takes security seriously. If you discover a security vulnerability in Tensorlogic, please report it responsibly.

How to Report

DO NOT open a public GitHub issue for security vulnerabilities.

Instead, please report security issues to:

  • Email: security@cool-japan.org (or open a private security advisory on GitHub)
  • Subject: [SECURITY] Tensorlogic - Brief description

What to Include

Please include the following information in your report:

  1. Description: Clear description of the vulnerability
  2. Impact: Potential impact and severity assessment
  3. Reproduction: Step-by-step instructions to reproduce the issue
  4. Environment: Rust version, OS, and relevant configuration
  5. Proposed Fix: If you have a suggested solution (optional)

Response Timeline

  • Initial Response: Within 48 hours
  • Status Update: Within 7 days
  • Fix Timeline: Depends on severity
    • Critical: Within 7 days
    • High: Within 14 days
    • Medium: Within 30 days
    • Low: Next release cycle

Disclosure Policy

  • We follow coordinated disclosure practices
  • We will work with you to understand and address the issue
  • We will credit reporters in security advisories (unless anonymity is requested)
  • Please allow us reasonable time to fix issues before public disclosure

Security Considerations

Scope

Tensorlogic is a planning layer that compiles logic rules to tensor equations. Security considerations include:

  1. Input Validation: Malformed logic expressions could cause panics or excessive resource consumption
  2. Resource Limits: Large graphs may consume excessive memory or CPU
  3. Dependency Security: We audit dependencies regularly
  4. Type Safety: Rust's type system provides strong guarantees, but unsafe code requires careful review

Out of Scope

  • Theoretical attacks on logic compilation algorithms (research papers welcome)
  • Issues in upstream dependencies (report to those projects)
  • Performance issues without security implications

Security Features

  • No Unsafe Code in planning layer (IR, compiler, infer traits)
  • Dependency Auditing: Regular cargo audit checks
  • Static Analysis: Clippy with strict lints enabled
  • Minimal Attack Surface: Planning layer has no network or filesystem access

Backend Security

The SciRS2 backend may use:

  • SIMD operations (platform-specific)
  • GPU operations (future)
  • Numerical computations that could overflow or lose precision

We validate inputs and provide safe abstractions over low-level operations.

Data Governance

The OxiRS bridge handles:

  • GraphQL query parsing
  • RDF/SPARQL execution
  • SHACL constraint validation

These components have their own security policies. See the OxiRS documentation for details.

Best Practices for Users

Input Validation

Always validate untrusted input before compiling:

use tensorlogic_compiler::compile_to_einsum;

// Validate before compilation
if expr_is_too_large(&expr) {
    return Err("Expression exceeds size limit");
}

let graph = compile_to_einsum(&expr)?;

Resource Limits

Set appropriate limits for production use:

const MAX_GRAPH_NODES: usize = 10000;
const MAX_TENSOR_SIZE: usize = 100_000_000;

if graph.nodes.len() > MAX_GRAPH_NODES {
    return Err("Graph too large");
}

Dependency Management

  • Keep dependencies up to date
  • Run cargo audit regularly
  • Review security advisories for the COOLJAPAN ecosystem

Safe Deployment

  • Run with minimal privileges
  • Isolate execution environments (containers, VMs)
  • Monitor resource usage
  • Implement timeout mechanisms for long-running operations

Security Audits

We perform regular security reviews:

  • Code Review: All PRs reviewed for security implications
  • Dependency Audits: Monthly cargo audit checks
  • Static Analysis: Continuous Clippy and rustfmt enforcement
  • Fuzzing: Planned for Phase 8 (validation & scale)

Known Limitations

Current known limitations (not vulnerabilities):

  1. No Resource Limits: Early versions do not enforce graph size limits
  2. No Timeout Mechanisms: Long compilations may run indefinitely
  3. Limited Input Validation: Assumes well-formed expressions

These will be addressed in future releases.

Updates and Advisories

Security advisories will be published:

  • As GitHub Security Advisories
  • In release notes
  • On the COOLJAPAN security mailing list (when available)

Contact

For security-related questions:

For non-security issues:

  • Open a public GitHub issue
  • See CONTRIBUTING.md for guidelines

Thank you for helping keep Tensorlogic secure!