Organisations should prioritise the surfaces with high exploitability and high impact first. In the source material, memory systems, tool execution, external data sources, orchestration, inter-agent communication, and configuration are all candidates for immediate attention. That sequencing helps teams focus budget and testing effort on the paths most likely to produce compromise, data loss, or privilege escalation.
How to think about the first wave of agentic AI attack surfaces
Prioritisation should start with the surfaces that combine high blast radius with easy abuse, not the ones that are merely visible in architecture diagrams. For most agentic systems, that means treating memory, tool execution, orchestration, external data ingestion, inter-agent communication, and configuration as the first candidates because they can turn a small compromise into broad data exposure, unsafe actions, or privilege escalation.
The practical question is which surface lets an attacker influence the agent most cheaply and most broadly. A surface that can change decisions, inject instructions, or widen access is more urgent than one that only affects a single narrow function.
Which surfaces usually rise to the top first?
Memory is often high priority because it can persist poisoned context, carry sensitive data across sessions, and amplify a single bad write into repeated unsafe behavior. Tool execution is next because it is where the agent crosses from reasoning into action, so weak authorization, unscoped tools, or unsafe command execution can immediately become real-world impact.
External data sources and configuration deserve similar attention because they often shape what the agent trusts before it acts. If those inputs can be manipulated, the attacker does not need to defeat the whole system, only the assumptions the system uses to decide.
Orchestration and multi-agent systems and A2A security become critical when one compromised component can influence many others through delegation or chained requests. That same logic is why teams should also examine the agent's authorization model early, especially where least privilege for AI agents has not been enforced per action.
How to rank attack surfaces without overcomplicating the process
A useful way to sequence the work is to score each surface on two axes: exploitability and impact. Exploitability asks how easy it is to reach, manipulate, or poison the surface. Impact asks what happens if it is abused, including data leakage, policy bypass, unauthorized actions, or lateral movement across other agents and systems.
That approach usually puts memory, tools, and orchestration ahead of lower-leverage surfaces because they tend to be both reachable and consequential. It also helps teams avoid a common mistake, which is spending most of the first review cycle on general observability while leaving the actual action paths under-tested.
For teams using agentic AI security controls, the goal is to map each surface to the kind of failure it can produce, then test the highest-leverage paths first. A surface that can affect memory, tool use, or delegation should usually outrank one that only creates nuisance-level instability.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Agentic AI Top 10 provides the primary governance reference for this topic.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Agentic AI Top 10 | ASI03 — Identity & Privilege Abuse | Agent surfaces here can expand privilege or misuse delegated authority. |
| ASI06 — Memory & Context Poisoning | Memory is a top-priority surface because poisoned context can steer later actions. | |
| ASI02 — Tool Misuse | Tool execution is a primary attack surface because unsafe tools enable direct harmful actions. | |
| Recommendation — Enforce per-action authorization and remove standing privilege from agent workflows. Isolate writable memory and restrict what the agent can persist or consume. Constrain tools with scoped permissions and explicit approval for risky actions. | ||
Practitioner Guidance
What to prioritise: Start with the surfaces that can both change agent behavior and produce an irreversible outcome, especially memory writes, tool calls, orchestration hops, and externally sourced context. Those are the places where a small control gap becomes a systemic one.
What to verify: Confirm whether each high-priority surface has its own access scope, input validation, logging, and rollback or containment path. If you cannot tell who changed it, what it influenced, and how to reverse it, it is not ready for production trust.
Decision rule: If a surface can cause the agent to take action on behalf of a user, system, or workflow, rank it ahead of passive surfaces even if the passive surface is easier to inspect. Action-bearing surfaces deserve the first testing budget because they create the fastest path to impact.
Practitioner takeaway: Prioritise by the combination of reach and consequence, then test the surfaces that can change decisions or actions before the ones that only add noise or complexity.
Related resources from NHI Mgmt Group
- Should organisations prioritise external exposure or internal credential governance first?
- How do organisations decide whether to prioritise AI discovery, data governance, or broader compliance mapping first?
- What should organisations prioritise first: expanding agentic AI use or strengthening data security controls?
- Why does agentic AI driven pentesting matter for organisations with growing cloud and web attack surfaces?
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on September 30, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
