FKIE_CVE-2026-66771
Vulnerability from fkie_nvd - Published: 2026-08-11 01:17 - Updated: 2026-08-11 15:17
Severity
Summary
SAPUI5 allows a key user with content adaptation privileges to inject malicious script content into persisted application changes. When another user subsequently opens the adapted application, the injected script executes in the victim's browser session. Successful exploitation could allow the attacker to access sensitive session data and perform unauthorized actions on behalf of the victim, resulting in a high impact on confidentiality and integrity. There is no impact on availability.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "unaffected",
"product": "SAPUI5",
"vendor": "SAP_SE",
"versions": [
{
"status": "affected",
"version": "SAP_UI 750"
},
{
"status": "affected",
"version": "754"
},
{
"status": "affected",
"version": "755"
},
{
"status": "affected",
"version": "756"
},
{
"status": "affected",
"version": "757"
},
{
"status": "affected",
"version": "758"
},
{
"status": "affected",
"version": "816"
},
{
"status": "affected",
"version": "UI_700 200"
}
]
}
],
"source": "cna@sap.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "SAPUI5 allows a key user with content adaptation privileges to inject malicious script content into persisted application changes. When another user subsequently opens the adapted application, the injected script executes in the victim\u0027s browser session. Successful exploitation could allow the attacker to access sensitive session data and perform unauthorized actions on behalf of the victim, resulting in a high impact on confidentiality and integrity. There is no impact on availability."
}
],
"id": "CVE-2026-66771",
"lastModified": "2026-08-11T15:17:33.500",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 6.1,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "HIGH",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:U/C:H/I:H/A:N",
"version": "3.1"
},
"exploitabilityScore": 0.9,
"impactScore": 5.2,
"source": "cna@sap.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-66771",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-08-11T13:11:14.989435Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-08-11T01:17:23.407",
"references": [
{
"source": "cna@sap.com",
"url": "https://me.sap.com/notes/3772071"
},
{
"source": "cna@sap.com",
"url": "https://url.sap/sapsecuritypatchday"
}
],
"sourceIdentifier": "cna@sap.com",
"vulnStatus": "Received",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-79"
}
],
"source": "cna@sap.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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