FKIE_CVE-2025-27621
Vulnerability from fkie_nvd - Published: 2026-08-17 16:16 - Updated: 2026-08-17 16:16
Severity
Summary
UpTrain is an open-source platform to evaluate and improve generative AI applications. In version 0.7.1 and prior, the UpTrain backend creates a new default user with a static username, where the username is also used as the default API key. The UpTrain backend also has an open CORS policy. Using these two primitives, any website can make a authenticated cross-origin request to the UpTrain instance by providing the default API key in the header `uptrain-access-token`. This issue may allow arbitrary websites to perform privileged operations on the UpTrain instance, as if they were the default logged in user. As of time of publication, no known patches are available.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "uptrain",
"vendor": "uptrain-ai",
"versions": [
{
"status": "affected",
"version": "\u003c= 0.7.1"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "UpTrain is an open-source platform to evaluate and improve generative AI applications. In version 0.7.1 and prior, the UpTrain backend creates a new default user with a static username, where the username is also used as the default API key. The UpTrain backend also has an open CORS policy. Using these two primitives, any website can make a authenticated cross-origin request to the UpTrain instance by providing the default API key in the header `uptrain-access-token`. This issue may allow arbitrary websites to perform privileged operations on the UpTrain instance, as if they were the default logged in user. As of time of publication, no known patches are available."
}
],
"id": "CVE-2025-27621",
"lastModified": "2026-08-17T16:16:46.290",
"metrics": {
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "NONE",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 7.7,
"baseSeverity": "HIGH",
"confidentialityRequirement": "NOT_DEFINED",
"exploitMaturity": "PROOF_OF_CONCEPT",
"integrityRequirement": "NOT_DEFINED",
"modifiedAttackComplexity": "NOT_DEFINED",
"modifiedAttackRequirements": "NOT_DEFINED",
"modifiedAttackVector": "NOT_DEFINED",
"modifiedPrivilegesRequired": "NOT_DEFINED",
"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
"modifiedVulnAvailabilityImpact": "NOT_DEFINED",
"modifiedVulnConfidentialityImpact": "NOT_DEFINED",
"modifiedVulnIntegrityImpact": "NOT_DEFINED",
"privilegesRequired": "NONE",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "NONE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"version": "4.0",
"vulnAvailabilityImpact": "NONE",
"vulnConfidentialityImpact": "NONE",
"vulnIntegrityImpact": "HIGH",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "security-advisories@github.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2025-27621",
"options": [
{
"exploitation": "none"
},
{
"automatable": "yes"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-08-17T15:58:11.831525Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-08-17T16:16:46.290",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/uptrain-ai/uptrain/blob/a31cc14eddcb6c0b0b12cbed15f086d98c441c6f/uptrain/dashboard/backend/app.py#L105"
},
{
"source": "security-advisories@github.com",
"url": "https://securitylab.github.com/advisories/GHSL-2024-198_GHSL-2024-199_Uptrain/"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Received",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-287"
}
],
"source": "security-advisories@github.com",
"type": "Primary"
}
]
}
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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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