AI Threat Bulletin

Continuous monitoring of vendor LLM deployments closes gaps left by static security frameworks.

Law firms need layered controls to govern AI vendor risk that procurement checklists cannot address.

Vendors change models secretly; gateways alone cannot stop indirect injection.

Runtime checks can catch injected instructions that document screening misses.

Most enterprise injection detectors miss threats hidden in RAG corpora and tool outputs.

Regulators now demand continuous oversight of AI vendor changes, not just completed questionnaires.

Sensitive data can leak through LLM logs even without malicious intent.

Attackers can infer whether someone's data trained an AI model through its ordinary responses.

Permission debt and prompt injection create dual pathways for attackers to steal data from Copilot.

Defenders must filter inputs and monitor outputs outside the model to block prompt extraction.