Why AI Agents Expand the Security Perimeter
AI agents do more than generate text. They call tools, query databases, retrieve documents, execute code, and communicate with external services. Every connection introduces a potential path for model exfiltration or credential leakage.
Model exfiltration includes direct theft of model weights, systematic extraction of proprietary behavior, and reconstruction of sensitive training data through repeated queries. Attackers may also inject instructions that persuade an agent to reveal system prompts, internal files, access tokens, or confidential context.
API keys are especially vulnerable because agents often need credentials at runtime. If those secrets appear in prompts, logs, traces, exception messages, or tool outputs, a malicious user may be able to recover them. Conventional application controls remain necessary, but agentic systems require additional safeguards that account for probabilistic decisions and dynamic tool chains.
Separate Agent Reasoning From Secrets
