Topic starter
16/04/2026 7:03 pm
TL;DR: AI-assisted phishing, agentic abuse, and shadow AI are widening identity risk as organisations race to deploy more AI into security stacks, according to RSA Security and the 2026 RSA ID IQ Report. The central failure is that identity programmes still assume humans, agents, and non-human identities can be governed with the same review cadence and trust model.
Editorial analysis by NHI Mgmt Group, based on content published by RSA Security: “Claude Mythos and Capybara: Best Practices for The Next Evolution in AI-Powered Cybersecurity Risks”.
By the numbers:
- 91% of organizations planned to implement some form of AI into their cybersecurity stack this year.
- NHI outnumber human users by 45 to 1 in DevOps environments.
- 60% of enterprises expressed a lack of confidence in their ability to adequately secure NHI.
Key questions
Q: What breaks when AI agents are managed like ordinary machine identities?
A: What breaks is the assumption that access scope can be fully understood from provisioning data and quarterly review.
Q: Why does AI-driven phishing change identity security decisions?
A: It lowers the reliability of human judgment in routine trust checks, which means organisations need stronger process controls.
Q: How do security teams know whether shadow AI is creating insider risk?
A: Look for sensitive data moving into unauthorised models, browser extensions, or workflow tools that are not approved for that content.
Practitioner guidance
- Harden authentication against AI-driven impersonation Replace password-only and weak step-up patterns where AI-generated phishing can defeat user judgment.
- Inventory AI agents and related NHIs Create a governed inventory of AI agents, bots, and AI services, including ownership, credentials, permissions, and data access scope.
- Enforce explicit policy for shadow AI use Define which AI services are approved, what data they may process, and which business functions are off limits.
Bottom line: AI-powered phishing and impersonation are raising the baseline for identity attacks because defenders are no longer dealing with static social engineering.
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This topic was modified 4 days ago by NHI Mgmt Group
08/10/2026 6:06 pm
AI-powered attack tools are turning identity verification into a live control problem, not a user-behaviour problem. When attackers can generate more convincing phishing, impersonation, and help desk fraud, the old assumption that humans can reliably spot malicious intent collapses. The practical implication is that identity assurance must move from awareness-only thinking to stronger verification at the authentication edge.
A few things that frame the scale:
- 90% of IT leaders say properly managing NHIs is essential for a successful zero-trust implementation, according to the Ultimate Guide to NHIs.
A question worth separating out:
Q: How should organisations govern AI agents alongside human identity and device access?
A: Organisations should treat AI agents as a separate identity class with their own entitlement boundaries, logging expectations, and approval model. Human IAM controls often assume interactive sign-in and review cycles, which do not fit autonomous or programmatic access. The safer approach is to define actor-specific policy and verify which access paths can be delegated without expanding trust unnecessarily.
👉 Read our full editorial: AI-powered cybersecurity risks are exposing identity control gaps