LLM Security Review — Page 5

Enterprises need visibility into third-party AI risks traditional vendor platforms can't detect.

A shared vocabulary turns risk checklist into tool comparison grid.

Enterprises need new rules to spot AI features hidden inside trusted vendor software.

Rethink vendor questionnaires to catch AI risks standard security checklists miss.

Standard vendor risk software misses AI-specific threats like prompt injection and model drift.

Routine SaaS updates quietly embed AI features that dodge traditional vendor review.

Attackers use hidden instructions to turn agent tools into data exfiltration channels.

Data pasted into unapproved AI tools trains models that can't be unlearned or audited.

Regulators now require LLM systems to log prompts, decisions, and outputs—not just API calls.

System prompts leak secrets because models can't distinguish instructions from user input.

Attackers hide instructions in documents to trick AI systems into leaking data through rendering.