CVE-2025-68711 (GCVE-0-2025-68711)
Vulnerability from cvelistv5 – Published: 2026-05-26 00:00 – Updated: 2026-05-27 20:32
VLAI
EPSS
VEX
Summary
AppLockZ App Lock and Fingerprint Lock (applock.passwordfingerprint.applockz) 4.2.11 for Android allows a local attacker with physical access to bypass the PIN lock. The lock is implemented as an overlay rather than by using Android's secure authentication APIs. By navigating cascading interface flows - insecure navigation through exposed routes facilitates app control evasion {I.N.T.E.R.F.A.C.E] via advertisement or browser intents, an attacker can evade lockscreen verification and access protected apps (e.g., Chrome). This results in information disclosure and privilege escalation.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-05-27 20:32 UTC
CWE
- n/a
- CWE-288 - Authentication Bypass Using an Alternate Path or Channel
Assigner
References
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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