Episode 57 — GenAI/ML Services in Scope: Risks, Controls, Evidence
When generative artificial intelligence and machine learning enter scope, the risk profile expands to include data leakage through prompts, model inversion, training data provenance, and integrity of model outputs embedded in business processes. The exam will expect a structured approach: classify data permitted for prompts, enforce least-privilege access to models and vector stores, and implement content filters and rate limits to reduce abuse. Treat model artifacts as code with versioning, signatures, and promotion gates, and separate development sandboxes from production inference endpoints. Validate that third-party model providers meet vendor risk requirements and that contractual terms address data use, retention, and deletion. For Processing Integrity, test deterministic wrappers or guardrails around non-deterministic outputs, and define approval paths where model suggestions can affect customer commitments. Record who can change model parameters, upload training data, or enable new plugins, and require peer review for those changes just as you would for code.
Evidence must be exam-ready and reproducible. Produce policy excerpts governing prompt content, redaction, and acceptable use; export access logs showing who invoked which model with what scopes; and retain change records for dataset curation, fine-tuning runs, and model promotion decisions. Capture evaluation reports that measure output quality against defined acceptance criteria and bias tests, and show that failed evaluations block release. For privacy and confidentiality, provide data flow diagrams that highlight where personal or restricted data could enter prompts, and pair that with sanitization proofs and retention settings for provider-side logs. Demonstrate monitoring with alerts on anomalous token usage, unusually large context windows, or restricted category prompts. Finally, maintain a model registry linking versions to controls, datasets, tests, incidents, and rollback plans so auditors can follow a complete chain from design intent through operating evidence in the same way they would for traditional software. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
