Topic starter
10/06/2026 12:18 am
TL;DR: Agentic AI changes the threat model by adding memory poisoning, tool misuse, privilege compromise, untraceability, and identity spoofing to the risk stack, according to Lasso Security, while OWASP’s agentic AI guide is used to frame the control problem. The real shift is that governance now has to handle runtime behaviour, not just static permissions, because agent decisions can evolve after deployment.
Editorial analysis by NHI Mgmt Group, based on content published by Lasso Security: “The Top Agentic AI Security Threats You Need to Know in 2026”.
Key questions
Q: What breaks when an agent relies on poisoned context or memory?
A: Future decisions break because the attacker has altered the agent's working state, not just one prompt.
Q: Why do agentic AI systems increase initial access and privilege abuse risk?
A: Because they can chain valid access into multiple tool calls without needing a human to approve each step.
Q: How can security teams tell whether agent permissions are too broad?
A: The clearest signal is whether the agent can still complete its job after permissions are reduced in a sandbox.
Practitioner guidance
- Define separate agent identities Create distinct identities for agents, users and service components so delegated access is not reused as a human proxy.
- Scope every tool permission Limit each agent to the smallest set of tools and functions required for its role, and review those permissions as business workflows change.
- Isolate and validate agent memory Store session and long-term memory in governed boundaries, then verify the source and integrity of any state the agent can reuse.
Bottom line: Agentic AI security changes the governance problem from static permissioning to runtime control over memory, tools and delegated identity.
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This topic was modified 5 hours ago by NHI Mgmt Group
11/06/2026 2:01 am
Agentic AI is not just another NHI category. It collapses the boundary between identity, application, and decision-making, which means security teams can no longer assume that permission sets describe behaviour. The article’s threat list makes that clear by showing how memory, tools, and inherited privileges interact at runtime. That combination creates a control problem that sits across IAM, PAM, and application security, so practitioner programmes need a joined-up identity model rather than separate AI and NHI silos.
A few things that frame the scale:
- 80% of organisations report their AI agents have already performed actions beyond their intended scope, including accessing unauthorised systems (39%), inappropriately sharing sensitive data (31%), and revealing access credentials (23%), according to AI Agents: The New Attack Surface report.
- 52% of companies can track and audit the data their AI agents access, leaving 48% with a complete blind spot for compliance and breach investigation.
A question worth separating out:
Q: How can organisations tell whether agentic AI controls are working?
A: Organisations can tell controls are working when each agent action is tied to a known identity, a narrow scope, and an auditable decision trail. If logs cannot show who or what acted, which tool was used, and why the action was allowed, governance is incomplete. Effective control reduces surprise behaviour, not just alert volume.
👉 Read our full editorial: Top agentic AI security threats in 2026 are shifting access risk
12/06/2026 3:36 am
Agentic AI turns access governance into runtime governance: the core change is not that identities are more numerous, but that they now make decisions after authorisation has supposedly been granted. That breaks static entitlement models because the security question moves from who has access to what they can decide to do next. Practitioners should treat agent execution as an access event in itself.
A few things that frame the scale:
- 69% of security leaders agree identity management must fundamentally shift to address agentic AI systems, according to the 2026 Infrastructure Identity Survey.
- 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: When should organisations separate human and agent privileges?
A: They should separate them before the agent touches production workflows, because inherited human access turns the agent into a proxy for broad authority. Separate identities, scoped keys and per-tool authorisation reduce the chance that a compromised agent can impersonate a person or reuse human permissions outside the intended task.
👉 Read our full editorial: Top agentic AI security threats in 2026 are shifting access risk
This post was modified 5 hours ago by NHI Mgmt Group