D-SA-A-1: Is initial security awareness or informal consideration present in AI deployment?
Basic Isolation and Access Control: Implement fundamental security measures such as authentication and rate-limiting to secure AI APIs, aligned with industry standards and best practices.
Limited Runtime Protection: Initial protections mainly focused on basic perimeter defenses and simple access restrictions.
Description
Basic Isolation and Access Control: Implement fundamental security measures such as authentication and rate-limiting to secure AI APIs, aligned with industry standards and best practices.
Limited Runtime Protection: Initial protections mainly focused on basic perimeter defenses and simple access restrictions.
D-SA-A-2
D-SA-A-2: Are informal checks occasionally performed to ensure architectural compliance?
Runtime Guardrails: Deploy comprehensive runtime guardrails including output sanitization and input validation to mitigate common vulnerabilities (e.g., OWASP Top 10 for LLM Applications).
Structured Deployment Processes: Standardize deployment procedures to ensure consistent application of security controls across all AI environments.
Description
Runtime Guardrails: Deploy comprehensive runtime guardrails including output sanitization and input validation to mitigate common vulnerabilities (e.g., OWASP Top 10 for LLM Applications).
Structured Deployment Processes: Standardize deployment procedures to ensure consistent application of security controls across all AI environments.
D-SA-A-3
D-SA-A-3: Are formal procedures established for secure AI model deployment?
AI-Driven Adversarial Detection: Integrate advanced, AI-driven anomaly detection and adversarial monitoring capabilities into deployment environments, proactively identifying and addressing threats in real-time.
Model Versioning and Rollback: Implement model versioning with swift rollback mechanisms to enable rapid incident recovery and response, particularly relevant for private or fine-tuned deployments.
Description
AI-Driven Adversarial Detection: Integrate advanced, AI-driven anomaly detection and adversarial monitoring capabilities into deployment environments, proactively identifying and addressing threats in real-time.
Model Versioning and Rollback: Implement model versioning with swift rollback mechanisms to enable rapid incident recovery and response, particularly relevant for private or fine-tuned deployments.