Topic starter
02/08/2026 11:45 am
TL;DR: Agentic systems expand the attack surface beyond a single chat interface because agents can chain actions, use tools, persist context, and inherit permissions across multiple steps, according to Terra. The security problem is no longer just input testing, but validating how action-taking systems behave over time and where identity, privilege, and tool trust break down.
Editorial analysis by NHI Mgmt Group, based on content published by terra: “Everything You Need To Know About Pentest of Agentic Systems”.
Key questions
Q: How should security teams pentest agentic systems differently from web applications?
A: Security teams should test agentic systems as action-taking runtimes, not just as input surfaces.
Q: Why do agentic systems create more risk than AI features embedded in web apps?
A: Agentic systems create more risk because they can act across multiple steps, use tools, persist context, and inherit broader permissions than a normal AI feature.
Q: What are the signs that an agentic system's security controls are failing?
A: Warning signs include broad inherited permissions, unreviewed tool additions, memory that can be influenced by untrusted content, and actions that continue after the original user request should have ended.
Practitioner guidance
- Define the agent boundary before testing Separate AI-enabled features from true agents, then document which components can act, which can only respond, and which tools each one may invoke.
- Test delegated privilege, not just prompts Build test cases for task-scoped access, inherited permissions, and tool execution paths that can exceed the intended user action.
- Exercise memory and retrieval abuse paths Validate whether poisoned stored content, retrieved documents, or tool outputs can influence later decisions or persist across sessions.
Bottom line: Agentic systems widen the attack surface because they can retrieve data, call tools, retain context, and make decisions across multiple steps.
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02/08/2026 12:56 pm
Agentic system pentesting is a separate security discipline, not an extension of web testing. The visible chat layer is only one control surface in systems that can retrieve data, invoke tools, persist memory, and chain actions over time. That makes request-response testing structurally incomplete. Practitioners need a testing model that follows the agent's execution path, not just its user interface.
A few things that frame the scale:
- Only 13% of organisations feel extremely prepared for the reality of agentic AI despite the majority racing toward autonomous adoption, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: What should teams do when an agent can access tools, APIs, and memory at the same time?
A: Treat the combined capability as a high-risk control boundary and require explicit ownership for each tool, data source, and permission path. The operational question is not whether the agent is useful, but whether each enabled action is necessary, observable, and revocable. Without that structure, one compromised context can propagate through the whole workflow.
👉 Read our full editorial: Pentesting agentic systems needs a different security model