Vulnerability-Lookup

GHSA-QMV7-FCXW-PJ9W

Vulnerability from github – Published: 2025-11-10 09:30 – Updated: 2025-11-10 09:30

Details

A SQL injection vulnerability was found in Looker Studio.

A Looker Studio user with report view access could inject malicious SQL that would execute with the report owner's permissions. The vulnerability affected to reports with BigQuery as the data source.

This vulnerability was patched on 21 July 2025, and no customer action is needed.

Severity

7.6 (High)


                  
                    CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:H/VI:H/VA:L/SC:N/SI:N/SA:N/U:Clear

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JSON

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  "affected": [],
  "aliases": [
    "CVE-2025-12397"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-89"
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    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-11-10T09:15:41Z",
    "severity": "HIGH"
  },
  "details": "A SQL injection vulnerability was found in Looker Studio.\n\nA Looker Studio user with report view access could inject malicious SQL that would execute with the report owner\u0027s permissions. The vulnerability affected to reports with BigQuery as the data source.\n\nThis vulnerability was patched on 21 July 2025, and no customer action is needed.",
  "id": "GHSA-qmv7-fcxw-pj9w",
  "modified": "2025-11-10T09:30:27Z",
  "published": "2025-11-10T09:30:27Z",
  "references": [
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      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-12397"
    },
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      "type": "WEB",
      "url": "https://cloud.google.com/support/bulletins#gcp-2025-053"
    },
    {
      "type": "WEB",
      "url": "https://www.tenable.com/security/research/tra-2025-28"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
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      "score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:H/VI:H/VA:L/SC:N/SI:N/SA:N/E:X/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:Clear",
      "type": "CVSS_V4"
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}

CVE-2025-12397 (GCVE-0-2025-12397)

Vulnerability from cvelistv5 – Published: 2025-11-10 08:55 – Updated: 2025-11-10 15:17

Title

SQL Injection in Looker Studio

Summary

A SQL injection vulnerability was found in Looker Studio. A Looker Studio user with report view access could inject malicious SQL that would execute with the report owner's permissions. The vulnerability affected to reports with BigQuery as the data source. This vulnerability was patched on 21 July 2025, and no customer action is needed.

Severity

7.6 (High)


                        
                          CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:H/VI:H/VA:L/SC:N/SI:N/SA:N/U:Clear

SSVC

Exploitation: none Automatable: no Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-11-10 15:16 UTC

CWE

CWE-89 - Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')

Assigner

GoogleCloud CNA under the Google root

CNA scorecard B 77/100 over 30 records in the last 180 days details

References

2 references

URL	Tags
https://cloud.google.com/support/bulletins#gcp-2025-053
https://www.tenable.com/security/research/tra-2025-28

Impacted products

1 product

Vendor	Product	Version
Google Cloud	Looker Studio	Affected: 0 , < 2025-07-21 (date)

Credits

Liv Matan from Tenable.

Show details on NVD website

JSON

To clipboard

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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.
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