Vendor AI Connector Data Flows and Exfiltration Risk
How forgotten OAuth tokens and unmonitored AI connectors become data exfiltration highways.
How forgotten OAuth tokens and unmonitored AI connectors become data exfiltration highways.
RAG systems leak sensitive data through a structural flaw, not model safety issues.
Agents with hands turn prompt injection into unauthorized data theft at scale.
Hardware-enforced isolation protects sensitive data during cloud-based LLM inference.
Treat all LLM-generated output as untrusted input before it reaches downstream systems.
The framework misses enterprise risks in agentic AI, identity governance, and attack chaining.
Vendors silently update AI models in production, leaving deployers exposed to undetected drift.
Corrupted memory in AI agents persists across sessions, turning exploits into standing instructions.
Attackers chain three mechanisms to steal tokens from AI agents.
Agentic AI systems shift risk profiles between reviews, exposing gaps in annual vendor assessments.
Agents that take real actions demand red teaming methods fundamentally different from chatbots.
Malicious skills poisoned AI agent registries before defenses could catch up.