Custom GPT and Agent Security
Agents do work. That means they have privileges. That means compromise has consequences. Treat agents like service accounts that can be reasoned into bad decisions.
What it is
Custom GPTs (OpenAI's brand) and custom agents (general term) are LLM-based systems with tool access — the ability to call APIs, execute code, send emails, modify systems. They differ from chatbots in that they take actions, not just produce text. Compromise of an agent through prompt injection has direct operational consequences.
Central risk
Excessive agency (LLM06). An agent with broad tool access plus prompt-injection vulnerability becomes a compromised privileged account. Mitigation requires least-privilege tool scope, action confirmation gates for high-impact operations, and audit logging.
Specific risks
- Prompt injection bypassing intended task constraints (LLM01)
- Excessive agency via over-broad tool permissions (LLM06)
- Improper output handling causing downstream injection (LLM05)
- Unbounded consumption from runaway recursive agent loops (LLM10)
- Plug-in supply-chain risk for OpenAI custom GPTs (LLM03)
Recommended controls
- Principle of least privilege for tool access tokens
- Human-in-the-loop confirmation for high-impact actions
- Action audit logging
- Recursion and resource limits
- Adversarial testing of prompt-to-action paths
- Plug-in review for custom GPTs
Posture Check checkpoint
Runtime dimension (Q21–Q25) most directly relevant. Posture Check Q21 specifically asks about rate limiting; Q23 about isolation.
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