SecureAI — LLM Audit Trail for Compliance

Prove your AI compliance before the Pentagon asks

SecureAI creates immutable audit trails for every LLM interaction in your organization, automatically flagging unauthorized AI tool usage (like ChatGPT in classified environments) and generating compliance reports for CMMC 2.0, NIST 800-171, and defense contractor audits. Deploy in 48 hours as a transparent proxy—no code changes required—and demonstrate to regulators that your teams aren't leaking sensitive data through consumer AI tools.

Key Benefits:

- Tamper-proof audit logs with cryptographic timestamping that satisfy DoD cybersecurity requirements and survive legal discovery

- Real-time blocking of unauthorized LLM endpoints (ChatGPT, personal Claude accounts) while allowing approved enterprise AI tools

- Air-gapped deployment option for classified networks with offline compliance reporting and zero external dependencies

MVP Scope: Phase 1: OpenAI/Anthropic API logging proxy + basic audit dashboard + unauthorized ChatGPT detection. Phase 2: Add local model support + compliance report generation. Phase 3: Air-gapped deployment + forensics portal. Target: Government contractors needing Pentagon supply chain compliance proof within 90 days.

Tech Stack: Go/Rust (proxy interception layer), PostgreSQL + TimescaleDB (immutable audit logs), Kubernetes (deployment orchestration), TensorFlow/PyTorch (model fingerprinting), React + D3.js (compliance dashboard), HashiCorp Vault (secrets management), gRPC (secure inter-service communication), FIPS 140-2 certified HSM integration

Components:

- {'name': 'LLM API Interception & Logging Engine', 'description': 'Proxy layer that captures all LLM API calls (OpenAI, Anthropic, local models), user prompts, model responses, latency, tokens, and metadata. Supports both cloud and air-gapped environments.', 'key_features': ['Real-time packet inspection', 'Model-agnostic logging', 'Classified environment support', 'Zero-trust architecture']}

- {'name': 'Compliance Dashboard & Audit Trail', 'description': "Immutable audit log with tamper-proof timestamping, user attribution, and regulatory report generation (FedRAMP, NIST, DoD 5220.22-M). Enables investigators to prove which tools were/weren't used.", 'key_features': ['Blockchain-backed timestamps', 'Role-based access control', 'Automated compliance reports', 'Chain-of-custody documentation']}

- {'name': 'Unauthorized AI Detection Engine', 'description': 'ML classifier that identifies unauthorized LLM usage patterns (ChatGPT fingerprints, API signatures, behavioral anomalies) and flags policy violations in real-time.', 'key_features': ['Model fingerprinting', 'Behavioral anomaly detection', 'Policy rule engine', 'Alert escalation workflows']}

- {'name': 'Classified Environment Isolation Module', 'description': 'Air-gapped deployment option with local-only processing, no external calls, and FIPS 140-2 encryption for defense contractors and government agencies.', 'key_features': ['On-premise only option', 'FIPS 140-2 compliance', 'Offline operation', 'Supply chain transparency']}

- {'name': 'Investigation & Forensics Portal', 'description': 'Searchable interface for security teams to investigate specific incidents, reconstruct prompt/response chains, and generate court-admissible evidence reports.', 'key_features': ['Full-text search', 'Timeline reconstruction', 'Export to legal formats', 'Redaction tools for classified content']}

Quality assessment: Strong market fit (defense contractors, CMMC compliance) with concrete technical approach (proxy-based logging, model-agnostic), but artifact is incomplete (cuts off mid-sentence), lacks depth on immutability mechanisms and threat model, and originality is moderate since compliance logging for LLMs is an emerging but not novel category.