FKIE_CVE-2026-47362
Vulnerability from fkie_nvd - Published: 2026-08-07 18:17 - Updated: 2026-08-08 02:17
Severity
Summary
In versions of the Datadog Android application prior to v554-5.9.4, two Room-backed SQLite databases store sensitive content in plaintext: LocalNotificationDatabase (notification title, message, recipient, service, tags, and on-call/incident deep links) and SearchRecentDatabase (the user's full in-app search history).
Impact: Any actor able to bypass the app sandbox can read these databases in plaintext.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "unaffected",
"product": "Android App",
"vendor": "Datadog",
"versions": [
{
"lessThan": "5.9.4",
"status": "affected",
"version": "5.9.4",
"versionType": "semver"
}
]
}
],
"source": "support@hackerone.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "In versions of the Datadog Android application prior to v554-5.9.4, two Room-backed SQLite databases store sensitive content in plaintext: LocalNotificationDatabase (notification title, message, recipient, service, tags, and on-call/incident deep links) and SearchRecentDatabase (the user\u0027s full in-app search history). \r\nImpact: Any actor able to bypass the app sandbox can read these databases in plaintext."
}
],
"id": "CVE-2026-47362",
"lastModified": "2026-08-08T02:17:17.600",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "PHYSICAL",
"availabilityImpact": "NONE",
"baseScore": 4.6,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:P/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
"version": "3.1"
},
"exploitabilityScore": 0.9,
"impactScore": 3.6,
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-47362",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-08-07T18:28:11.214660Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-08-07T18:17:15.887",
"references": [
{
"source": "support@hackerone.com",
"url": "https://cwe.mitre.org/data/definitions/922.html"
},
{
"source": "support@hackerone.com",
"url": "https://trust.datadoghq.com/?tcuUid=2e8b8fa5-39ca-43f4-9f6a-aeafafb440ef"
},
{
"source": "support@hackerone.com",
"url": "https://www.zetetic.net/sqlcipher/sqlcipher-for-android/"
}
],
"sourceIdentifier": "support@hackerone.com",
"vulnStatus": "Received",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-922"
}
],
"source": "support@hackerone.com",
"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.
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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