Topic starter
23/10/2026 12:45 am
TL;DR: Agentic AI is turning trusted software into a new attack surface because agents can act on inboxes, payments, codebases, and internal systems with real credentials and broad privileges, according to ThreatLocker. Zero Trust, least privilege, and tighter auditability now matter as much for AI-driven workflows as they do for human users.
Editorial analysis by NHI Mgmt Group, based on content published by ThreatLocker: “Agentic AI: The new attack surface”.
By the numbers:
- 97% of the organizations that suffered an AI-related breach lacked proper AI access controls.
- Breaches involving shadow AI cost an average of $4.36 million.
- Gartner forecasts that 40% of enterprise applications will embed task-specific AI agents by 2026.
Key questions
Q: What breaks when an AI agent can turn untrusted content into privileged actions?
A: The trust boundary breaks because the agent no longer just reads external text.
Q: Why do AI agents increase non-human identity risk?
A: AI agents increase non-human identity risk because they can execute many actions quickly once they inherit a credential or tool permission.
Q: What are the signs that an autonomous agent is operating outside its intended boundary?
A: Look for agents running with approval prompts disabled, outbound connections to unfamiliar destinations, and access to production-classified systems that the workflow does not require.
Practitioner guidance
- Define each AI agent as a governed non-human identity Assign ownership, purpose, approved tools, and offboarding criteria for every agent that can authenticate or act independently.
- Scope agent permissions to single-purpose workflows Remove broad, reusable access and separate inbox, payment, code, and cloud privileges so one agent cannot pivot across functions.
- Block untrusted content from influencing high-risk actions Treat external documents, messages, and web content as untrusted inputs that cannot directly trigger sensitive changes, transfers, or approvals.
Bottom line: Agentic AI turns software into a delegated actor, which changes the security problem from content generation to action governance.
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23/10/2026 9:49 am
Agentic AI is becoming an identity governance problem, not just an AI problem. The central issue is that software is now being trusted with delegated authority inside live business workflows. That means access scope, approval boundaries, and evidence of intent matter more than model quality alone. Practitioners should treat agent governance as part of identity governance, not as a separate AI side project.
A few things that frame the scale:
- 53% of security leaders expect AI to run major portions of their infrastructure autonomously within the next three years, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: How do organisations keep AI agent access aligned with Zero Trust principles?
A: They need policies that evaluate the acting agent, the delegator, the task sensitivity, and the time of execution together. That keeps authorisation conditional and traceable rather than assuming a one-time account grant is enough for the whole workflow.
👉 Read our full editorial: Agentic AI expands the attack surface for identity and access controls