Compliance
SOC 2 Compliance for AI Applications
Meeting Trust Services Criteria for LLM-powered systems
SOC 2 compliance demonstrates that your organization has implemented security controls to protect customer data. For AI applications, this means showing auditors that your LLM systems are monitored, secured, and governed appropriately.
Does SOC 2 apply to AI applications?
Yes, SOC 2 applies to AI applications that process customer data. If your LLM-powered service handles sensitive information, you need to demonstrate security controls over the AI system, including access controls, monitoring, change management, and incident response for AI-specific risks.
Trust Services Criteria for AI
SOC 2 evaluates controls across five categories. Here's how they apply to AI systems:
What SOC 2 controls apply to LLMs?
Key SOC 2 controls for LLMs include: CC6 (Logical Access) for API key management and model access, CC7 (System Operations) for monitoring AI outputs and detecting anomalies, CC8 (Change Management) for prompt and model version control, and CC9 (Risk Mitigation) for AI-specific risks like hallucinations and data leakage.
Security (Required) — Access controls for AI systems, API key management, encryption of prompts and responses, monitoring for unauthorized access.
Availability — Uptime monitoring for AI services, failover procedures, capacity planning for inference workloads.
Processing Integrity — Validation that AI outputs are accurate and complete, hallucination detection, quality monitoring.
Confidentiality — Protection of sensitive data in prompts and responses, PII detection and handling.
Privacy — Data subject rights, consent management, data retention policies for AI interactions.
Evidence for Auditors
What evidence do auditors need for AI systems?
Auditors need: audit logs of all AI interactions, documentation of AI risk assessments, evidence of output monitoring and anomaly detection, access control records for AI systems, incident response procedures for AI failures, and change management records for prompts and model updates.
Key evidence items include:
- Immutable audit logs of all LLM interactions
- Risk classification results showing safety monitoring
- Drift detection alerts and resolution records
- API key rotation and access control logs
- Incident response records for AI-related issues
- Change management for prompt updates
Type I vs Type II
What is the difference between SOC 2 Type I and Type II for AI?
SOC 2 Type I evaluates control design at a point in time—suitable for new AI deployments. SOC 2 Type II evaluates operating effectiveness over 6-12 months—required for mature AI systems. Type II provides stronger assurance that AI controls actually work in practice.
DriftRail for SOC 2
DriftRail helps with SOC 2 compliance by providing:
- Immutable audit logs with database-level tamper protection
- One-click SOC 2 compliance reports mapping to Trust Services Criteria
- Automated risk classification for processing integrity evidence
- Drift detection and alerting for anomaly monitoring
- Export capabilities for auditor review