[ML] Add Sandbox2 security integration for PyTorch inference

[valeriy42]

Overview

This PR introduces Sandbox2 security integration to enhance the security posture of the PyTorch inference process in the ML-CPP codebase.

Changes

Security Enhancements

• Sandbox2 Integration: Added comprehensive Sandbox2 security framework integration
• Process Isolation: Implemented secure process spawning with privilege dropping
• Security Testing: Added comprehensive test suite to validate security constraints

Build System Updates

• CMake Integration: Updated build system to include Sandbox2 dependencies
• Third-party Dependencies: Added Abseil and Sandbox2 as third-party dependencies
• License Compliance: Added proper license files for all new dependencies

Key Components

• Core implementation for secure process spawning
• Comprehensive test suite validating security constraints
• Updated CMakeLists.txt files across multiple components
• Proper license attribution for all dependencies

Security Benefits

• Process Isolation: PyTorch inference processes run in isolated sandboxes
• Privilege Dropping: Processes run with minimal required privileges
• Resource Constraints: Sandbox2 enforces memory, CPU, and system call limitations
• Attack Surface Reduction: Malicious PyTorch models cannot escape sandbox constraints

Testing

• Added comprehensive unit tests validating security constraints
• Tests verify privilege dropping, resource limits, and sandbox enforcement
• All existing tests continue to pass

Dependencies

• Sandbox2: Google's sandboxing framework for Linux
• Abseil: Google's C++ common libraries (required by Sandbox2)

This enhancement significantly improves the security posture of the ML-CPP system by ensuring that PyTorch inference processes cannot compromise the host system.

[prodsecmachine]

✅ Snyk checks have passed. No issues have been found so far.

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