CVE-2025-12741 (GCVE-0-2025-12741)
Vulnerability from cvelistv5 – Published: 2025-11-24 11:35 – Updated: 2025-11-24 13:13
VLAI
EPSS
VEX
Title
Arbitrary File Write in Denodo dialect of Looker allows Remote Code Execution
Summary
A Looker user with Developer role could create a database connection using Denodo driver and, by manipulating LookML, cause Looker to execute a malicious command.
Looker-hosted and Self-hosted were found to be vulnerable.
This issue has already been mitigated for Looker-hosted instances. No user action is required for these.
Self-hosted instances must be upgraded as soon as possible. This vulnerability has been patched in all supported versions of Self-hosted.
The versions below have all been updated to protect from this vulnerability. You can download these versions at the Looker download page https://download.looker.com/ :
* 24.12.108+
* 24.18.200+
* 25.0.78+
* 25.6.65+
* 25.8.47+
* 25.12.10+
* 25.14+
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-11-24 13:12 UTC
CWE
- CWE-20 - Improper Input Validation
Assigner
References
1 reference
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Google Cloud | Looker |
Affected:
0 , < 24.12.108
(custom)
Affected: 0 , < 24.18.200 (custom) Affected: 0 , < 25.0.78 (custom) Affected: 0 , < 25.6.65 (custom) Affected: 0 , < 25.8.47 (custom) Affected: 0 , < 25.12.10 (custom) Affected: 0 , < 25.14 (custom) |
guessed |
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"value": "A Looker user with Developer role could create a database connection using Denodo driver and, by manipulating LookML, cause Looker to execute a malicious command.\n\nLooker-hosted and Self-hosted were found to be vulnerable.\nThis issue has already been mitigated for Looker-hosted instances.\u00a0No user action is required for these.\n\n\nSelf-hosted instances must be upgraded as soon as possible. This vulnerability has been patched in all supported versions of Self-hosted.\nThe versions below have all been updated to protect from this vulnerability. You can download these versions at the Looker download page https://download.looker.com/ :\n * 24.12.108+\n * 24.18.200+\n * 25.0.78+\n * 25.6.65+\n * 25.8.47+\n * 25.12.10+\n * 25.14+"
}
],
"impacts": [
{
"capecId": "CAPEC-137",
"descriptions": [
{
"lang": "en",
"value": "CAPEC-137 Parameter Injection"
}
]
}
],
"metrics": [
{
"cvssV4_0": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "HIGH",
"attackRequirements": "PRESENT",
"attackVector": "NETWORK",
"baseScore": 7.7,
"baseSeverity": "HIGH",
"exploitMaturity": "NOT_DEFINED",
"privilegesRequired": "LOW",
"providerUrgency": "RED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "NONE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:H/AT:P/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/U:Red",
"version": "4.0",
"vulnAvailabilityImpact": "HIGH",
"vulnConfidentialityImpact": "HIGH",
"vulnIntegrityImpact": "HIGH",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"format": "CVSS",
"scenarios": [
{
"lang": "en",
"value": "GENERAL"
}
]
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-20",
"description": "CWE-20 Improper Input Validation",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2025-11-24T11:35:33.730Z",
"orgId": "f45cbf4e-4146-4068-b7e1-655ffc2c548c",
"shortName": "GoogleCloud"
},
"references": [
{
"url": "https://cloud.google.com/support/bulletins#gcp-2025-052"
}
],
"source": {
"discovery": "UNKNOWN"
},
"title": "Arbitrary File Write in Denodo dialect of Looker allows Remote Code Execution",
"x_generator": {
"engine": "Vulnogram 0.4.0"
}
}
},
"cveMetadata": {
"assignerOrgId": "f45cbf4e-4146-4068-b7e1-655ffc2c548c",
"assignerShortName": "GoogleCloud",
"cveId": "CVE-2025-12741",
"datePublished": "2025-11-24T11:35:33.730Z",
"dateReserved": "2025-11-05T10:50:34.070Z",
"dateUpdated": "2025-11-24T13:13:17.641Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2"
}
}
}
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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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