We still treat account recovery like a minor inconvenience. A login fails, users click “reset password,” and move on. But in 2026, the problem isn’t about restoring access—it’s about identity.
The typical recovery scenario has little to do with forgetfulness. A device gets stolen. A SIM card is already compromised. Email account is breached. Authenticator app stops working.
At that point, a password reset starts to resemble calling security for a duplicate badge. The voice sounds legitimate. The details check out. But there’s no certainty who’s actually on the line.
That’s why account recovery today isn’t about restoring access. It’s about answering a much harder question: how do you know it’s really the account owner when the usual signals—device, SIM, email—can no longer be trusted?
Why fraudsters target account recovery flows
There’s an uncomfortable reality that often goes overlooked: account recovery is designed to be the most “human” part of the product.
It’s where support steps in, where systems become more flexible. Where user claims are more readily trusted. It’s also exactly where attackers focus.
Breaking the primary login has become increasingly difficult. Compromising the recovery process is often much easier.
The signals we once relied on—email, SMS, support interactions—felt dependable when attacks were costly. That’s no longer the case. Phishing now operates at scale. SIM swapping has become industrialized. Session hijacking is no longer rare.
The economics have shifted. What was once a protected fallback has quietly become a secondary entry point—often with weaker defenses than the main login.
Account recovery ≠ re-onboarding
It’s easy to mistake an account recovery for a second pass at onboarding. On the surface, it looks the same: a camera check, a one-time code, a few quick steps.
But that similarity is misleading.
Registration is a first encounter. The system is seeing a user for the first time and operates with limited context. As a result, it’s designed to be tolerant. Friction is minimized. Some degree of error is acceptable to avoid turning away legitimate users.
Account recovery operates under completely different conditions.
This is a post-incident. The legitimate user already exists. There’s a history of logins, linked credentials, and established patterns. And then something breaks—suddenly, every signal becomes questionable.
This isn’t the moment for flexibility.
In registration, the cost of being wrong is relatively low. In recovery, the cost asymmetry is stark.
A false rejection creates friction. A false acceptance creates risk.
Registration answers a straightforward question: Can we trust this new account?
Recovery asks something far more difficult: can we trust this specific person again—especially when an attacker may already know enough to impersonate them?
Biometric anti-fraud as a trust layer in account recovery
Against this backdrop, the shift toward face biometrics in account recovery makes sense. But not as a convenience feature, and not as a faster way to log in.
Face biometrics are becoming a mechanism to re-establish trust—precisely when every other factor is already in doubt.
But recognizing a face is no longer the hard part. Spoofing is the real challenge.
Attackers can use a photo on a screen, a replayed video from another device, a 2D or 3D mask, or a manipulated camera feed to bypass checks.
This is why liveness detection should be the first critical check, which confirms that the subject is physically present and interacting in real time.
However, liveness alone does not address newer attack vectors.
Deepfake-based attacks introduce a different kind of threat, using synthetic faces and AI-generated video that is designed to look convincingly real.
To counter this, deepfake detection should emerge as a second check, which identifies artificially generated or manipulated visual input.
And even that is no longer sufficient on its own.
Both liveness and deepfake detection evaluate what appears in front of the camera. Neither fully accounts for the context in which the interaction occurs.
This is where anti-fraud functionality should be implied.
In account recovery, trust cannot be established from a single signal. It requires evaluating the broader session context:
- Where the signal originates,
- Whether the data looks consistent with real device behavior,
- Whether there are signs of manipulation,
- Whether the interaction aligns with how the legitimate user typically behaves.
Account recovery should not depend on a single “successful” biometric check.
It should rely on a system capable of evaluating trust from multiple angles—because that’s exactly what attackers are trying to break.
How to safely re-establish trust before access reset
Put simply, account recovery should operate in a state of heightened caution.
The first step is to put the account into a safe mode. No critical changes should be allowed until verification is complete.
Next, confirm that there is a real, live person in front of the system—without signs of spoofing or manipulation.
Then, validate against what the system already knows: the baseline from onboarding, familiar login patterns, and a history of legitimate sessions.
Only after that should credentials and authentication factors be reissued.
You’re choosing: Protecting a button or a person
Recovery isn’t just a technical flow. It’s a controlled process of rebuilding trust—step by step, with each stage reducing uncertainty before moving to the next.
If your recovery flow is limited to a password reset, you are protecting a button.
If it is designed as a trust recovery system, you are protecting the user, along with their data, their money, and your organization’s reputation.
This defines whether your account recovery flow is a safeguard or an entry point for attackers.
Mikhaylo Pavlyuk is a commercial leader in AI and computer vision with hands-on expertise in face biometrics, liveness detection, deepfake protection, and the implementation of computer vision solutions for B2B markets.
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Featured image: Vadim Bogulov on Unsplash
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