FKIE_CVE-2026-54050
Vulnerability from fkie_nvd - Published: 2026-09-15 18:17 - Updated: 2026-09-25 14:23
Severity
Summary
Sakai is a Collaboration and Learning Environment (CLE). From 23.0 until 23.5 and 25.3, the DELETE /api/users/{userId}/profile/image endpoint allows an authenticated user to delete another user's profile image because ProfileController.removeProfileImage() passes the attacker-controlled userId to ProfileServiceImpl.removeProfileImage() without verifying ownership, and profileImageUploadedRepository.deleteById(userId) removes the selected row. The related DELETE /api/users/{userId}/profile/pronunciation endpoint also omits session validation and ownership checks before ProfileServiceImpl.removePronunciationRecording() deletes the target user's recording. The upload path is not affected because it already verifies ownership, and superusers remain intentionally authorized to modify other profiles. Successful exploitation can repeatedly remove profile identity artifacts, including administrator and instructor images, and disrupt workflows that rely on those artifacts. This issue is fixed in versions 23.5, 25.3, and 26.0.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "sakai",
"vendor": "sakaiproject",
"versions": [
{
"status": "affected",
"version": "\u003e= 23.0, \u003c 23.5"
},
{
"status": "affected",
"version": "\u003e= 25.0, \u003c= 25.2"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Sakai is a Collaboration and Learning Environment (CLE). From 23.0 until 23.5 and 25.3, the DELETE /api/users/{userId}/profile/image endpoint allows an authenticated user to delete another user\u0027s profile image because ProfileController.removeProfileImage() passes the attacker-controlled userId to ProfileServiceImpl.removeProfileImage() without verifying ownership, and profileImageUploadedRepository.deleteById(userId) removes the selected row. The related DELETE /api/users/{userId}/profile/pronunciation endpoint also omits session validation and ownership checks before ProfileServiceImpl.removePronunciationRecording() deletes the target user\u0027s recording. The upload path is not affected because it already verifies ownership, and superusers remain intentionally authorized to modify other profiles. Successful exploitation can repeatedly remove profile identity artifacts, including administrator and instructor images, and disrupt workflows that rely on those artifacts. This issue is fixed in versions 23.5, 25.3, and 26.0."
}
],
"id": "CVE-2026-54050",
"lastModified": "2026-09-25T14:23:59.847",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 6.5,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:N",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 3.6,
"source": "security-advisories@github.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-54050",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-09-15T18:59:51.482620Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-09-15T18:17:22.533",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/sakaiproject/sakai/commit/a092dbf3dc6bf343131f50007c207a9abd95e852"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/sakaiproject/sakai/security/advisories/GHSA-9284-fjc3-fmmj"
},
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"url": "https://github.com/sakaiproject/sakai/security/advisories/GHSA-9284-fjc3-fmmj"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Awaiting Analysis",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-639"
}
],
"source": "security-advisories@github.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.
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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