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11/07/2026 8:44 pm
TL;DR: AI-generated phishing, deepfake logins, automated credential stuffing, and session replay are eroding assumptions built into traditional IAM, according to eMudhra. Static rules and fixed MFA increasingly fail against synthetic identity patterns, making adaptive, context-aware identity controls the practical response.
NHIMG editorial — based on content published by eMudhra: Artificial Intelligence is transforming cybercrime and identity access management
Questions worth separating out
Q: How should security teams respond to AI-generated phishing campaigns?
A: Security teams should assume the message quality will be good enough to fool users and focus on reducing what a successful click can do.
Q: Why do traditional MFA methods struggle against synthetic identity attacks?
A: Traditional MFA struggles because it confirms a moment of possession, not the legitimacy of the full session.
Q: What is the difference between login security and session security?
A: Login security verifies that the right identity completed authentication.
Practitioner guidance
- Reduce reliance on OTP-only authentication Treat OTP as a weak factor in high-risk workflows and add stronger non-replayable authentication for sensitive access paths, especially where phishing and proxy attacks are plausible.
- Add behavioural anomaly checks to privileged access Use device context, access timing, location drift, and session behaviour to flag synthetic logins before high-value actions are completed.
- Protect sessions, not just logins Instrument continuous session monitoring so stolen cookies, replayed tokens, and abnormal action sequences can trigger step-up or termination after authentication succeeds.
What's in the full article
eMudhra's full article covers the implementation detail this post intentionally leaves at the framework level:
- Behavioral intelligence signals used to build a digital identity profile for login decisions
- Certificate-backed authentication design choices for reducing replayable credential risk
- Adaptive access control logic for hybrid, multi-cloud, and remote-first environments
- Scenario walkthroughs showing how deepfake impersonation and session replay are detected and blocked
👉 Read eMudhra's analysis of AI-powered identity attacks and adaptive IAM →
AI-driven identity attacks are testing whether IAM can still keep up?
Explore further
11/07/2026 9:10 pm
Static identity controls are no longer aligned to AI-driven attack tempo. Traditional IAM assumes access can be judged at a single point in time using fixed rules, OTPs, and known-user behaviour. AI-powered attacks break that model by changing the shape of the login event itself, which means the control is evaluating the wrong thing. The practitioner conclusion is straightforward: assurance now has to follow behaviour, not just credentials.
A few things that frame the scale:
- 91.6% of secrets remain valid five days after the targeted organisation is notified, showing a critical gap in remediation procedures, according to Ultimate Guide to NHIs.
- Only 5.7% of organisations have full visibility into their service accounts, which means many identity programmes are still operating with major blind spots.
A question worth separating out:
Q: How should IAM teams reduce account takeover risk without relying on passwords?
A: Use passwordless methods that bind authentication to a secure device, cryptographic proof, or a physical approval action, then apply them first to the highest-risk journeys. The control only works if recovery, enrollment, and transaction approval are designed as part of the same assurance model, not bolted on later.
👉 Read our full editorial: AI-driven IAM is reshaping defence against deepfake identity attacks
