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Deepfakes can target a biometric check, but they can also get around a login by exploiting how identity is proved, recovered or supported—or by taking advantage of what an account can reach after sign-in. The important distinction is that a fake face or voice may attack the biometric process itself, while other attacks manipulate a separate route to account access. There is no established rate showing how often deepfakes defeat authentication systems overall.
How can deepfakes bypass authentication?
There are two distinct ways a deepfake can target a biometric system. In a presentation attack, an attacker shows or plays a fake to the sensor—for example, holding up an image or playing a voice recording. In an injection attack, untrusted media is fed into the authentication pipeline, such as a forged video inserted into a capture or verification process. UK government guidance identifies deepfake media as a possible injection input; it is not the same as simply presenting a fake to a camera.
Deepfakes can also be used against identity proofing, which is the process of establishing or verifying someone’s identity—for example, when opening an account or recovering access. NIST guidance recognizes that manipulated media can undermine document validation, biometric checks and a proofing agent’s visual review.
Can a deepfake get around a login without defeating the login factor?
Yes. A sign-in screen is only one part of an account’s identity boundary. If an attacker can persuade support staff to reset access, exploit a weak recovery route, or pass a separate proofing process, the attacker may regain access without defeating the normal login check. Microsoft notes that traditional helpdesk recovery is vulnerable to social engineering; after complete lockout, recovery should re-establish trust before access is restored.
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Access after sign-in matters too. If an account has broad permissions, a successful login can expose more information than necessary. New York State Department of Financial Services (DFS) guidance for covered entities recommends limiting access through least privilege and periodically reviewing elevated access, including in case MFA fails.
Which controls address which route?
| Control | What it helps protect | What it does not replace |
|---|---|---|
| Biometrics combined with a physical authenticator | Sign-in assurance: NIST says biometric characteristics are not secrets and supports their use only with a physical authenticator as part of multifactor authentication. | Recovery security, capture-pipeline integrity or limits on what an account can access after login. |
| Liveness and spoof detection | Some presentation attacks, by checking whether a live person or genuine capture is present. | Injection attacks or every way manipulated media can enter a system. Liveness should not be treated as a complete deepfake defense. |
| Capture integrity and protected channels | Injection and tampering risks, by helping establish that media came through a trusted capture path and was not altered in transit. | Social engineering of support or excessive post-login permissions. |
| Recovery and support safeguards | Account takeover through reset, escalation or identity re-verification. | A compromised biometric pipeline or broad permissions once an attacker is signed in. |
| Least-privilege access | The amount of information and functionality reachable after account access is obtained. | Whether the login or recovery check itself was trustworthy. |
What should organizations do about biometric checks?
Do not rely on a single “live or fake” decision. UK proofing guidance describes spoof detection and liveness testing, and advises evaluating systems against relevant performance and security standards. NIST’s identity-proofing guidance also points to analyzing submitted media for manipulation, protecting data channels, considering sensor authentication or device attestation, and supplementing automated decisions with manual review. The appropriate measures depend on the proofing context; the standard’s recommendations should not be presented as universal requirements.
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- Test against the attack path in scope: a presentation to a sensor and media injected into a pipeline are different scenarios.
- Document how capture devices and media channels are trusted, and where integrity can be lost.
- Measure false rejections and false acceptances, and provide a workable alternative for people who cannot or do not want to use biometrics.
- Use human review where the risk and context justify it, with clear procedures for resolving uncertain or conflicting evidence.
Why are biometrics not enough as a login secret?
A face, voice or other biometric trait is not like a password that can simply be kept secret or changed after exposure. NIST notes that biometric characteristics can often be obtained without a person’s consent. It therefore limits biometrics to use alongside a physical authenticator as part of multifactor authentication and says an alternative non-biometric option should be available.
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How should account recovery and access be secured?
Recovery should not silently become a weaker way into an account than the sign-in process it is meant to protect. Treat resets, helpdesk escalations and identity re-checks as authentication events: establish how identity is verified, who can approve an exception, and what evidence is recorded. When a person is fully locked out, Microsoft frames recovery as re-establishing trust before restoring access.
After recovery or login, constrain the damage an account can cause. Give users and service accounts only the permissions they need, review elevated access periodically, and avoid making one successful check a path to unrestricted data. These controls do not stop every account takeover; they reduce what an attacker can reach if an earlier control fails.
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How can you evaluate a deepfake defense?
Ask vendors or internal teams for evidence tied to the actual system and threat model, rather than a general claim that a tool is “deepfake-proof.” Useful evidence includes independent testing, documented attack artifacts, false-positive and false-negative behavior, coverage of both presentation and injection paths, and a defined manual-review process. Also examine usability, accessibility and biometric-data handling: stricter checks can increase friction or wrongly reject legitimate users, so the system needs a safe alternative and a clear escalation route.
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