FKIE_CVE-2025-68709
Vulnerability from fkie_nvd - Published: 2026-05-26 20:16 - Updated: 2026-07-24 11:10
Severity
Summary
SailingLab AppLock (aka com.alpha.applock) 4.3.8 for Android allows a local attacker to trigger arbitrary JavaScript execution via BrowserMainActivity, which accepts VIEW intents with javascript: URIs. This unsafe navigation path results in script execution and may allow UI spoofing or privilege escalation.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "n/a",
"vendor": "n/a",
"versions": [
{
"status": "affected",
"version": "n/a"
}
]
}
],
"source": "cve@mitre.org"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "SailingLab AppLock (aka com.alpha.applock) 4.3.8 for Android allows a local attacker to trigger arbitrary JavaScript execution via BrowserMainActivity, which accepts VIEW intents with javascript: URIs. This unsafe navigation path results in script execution and may allow UI spoofing or privilege escalation."
},
{
"lang": "es",
"value": "SailingLab AppLock (tambi\u00e9n conocido como com.alpha.applock) 4.3.8 para Android permite a un atacante local desencadenar la ejecuci\u00f3n arbitraria de JavaScript a trav\u00e9s de BrowserMainActivity, que acepta intents VIEW con URIs javascript:. Esta ruta de navegaci\u00f3n insegura resulta en la ejecuci\u00f3n de scripts y puede permitir la suplantaci\u00f3n de interfaz de usuario (UI) o la escalada de privilegios."
}
],
"id": "CVE-2025-68709",
"lastModified": "2026-07-24T11:10:00.170",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "ADJACENT_NETWORK",
"availabilityImpact": "NONE",
"baseScore": 5.2,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "CHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:A/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N",
"version": "3.1"
},
"exploitabilityScore": 2.1,
"impactScore": 2.7,
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2025-68709",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-05-27T17:25:20.982220Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-05-26T20:16:16.167",
"references": [
{
"source": "cve@mitre.org",
"url": "https://github.com/actuator/com.alpha.applock"
},
{
"source": "cve@mitre.org",
"url": "https://github.com/actuator/com.alpha.applock/blob/main/CVE-2025-68709"
},
{
"source": "cve@mitre.org",
"url": "https://play.google.com/store/apps/details?id=com.alpha.applock"
}
],
"sourceIdentifier": "cve@mitre.org",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-79"
}
],
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"type": "Secondary"
}
]
}
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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.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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