CVE-2025-12409 (GCVE-0-2025-12409)
Vulnerability from cvelistv5 – Published: 2025-11-10 08:59 – Updated: 2025-11-10 15:16
VLAI
EPSS
VEX
Title
SQL Injection in Looker Studio
Summary
A SQL injection vulnerability was discovered in Looker Studio that allowed for data exfiltration from BigQuery data sources.
By creating a malicious report with native functions enabled, and having the victim access the report, an attacker could execute injected SQL queries with the victim's permissions in BigQuery.
This vulnerability was patched on 07 July 2025, and no customer action is needed.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-11-10 15:14 UTC
CWE
- CWE-89 - Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')
Assigner
References
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Google Cloud | Looker Studio |
Affected:
0 , < 2025-07-07
(date)
|
guessed |
{
"containers": {
"adp": [
{
"metrics": [
{
"other": {
"content": {
"id": "CVE-2025-12409",
"options": [
{
"Exploitation": "none"
},
{
"Automatable": "no"
},
{
"Technical Impact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-11-10T15:14:54.971898Z",
"version": "2.0.3"
},
"type": "ssvc"
}
}
],
"providerMetadata": {
"dateUpdated": "2025-11-10T15:16:16.715Z",
"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"shortName": "CISA-ADP"
},
"title": "CISA ADP Vulnrichment"
}
],
"cna": {
"affected": [
{
"defaultStatus": "unaffected",
"product": "Looker Studio",
"vendor": "Google Cloud",
"versions": [
{
"lessThan": "2025-07-07",
"status": "affected",
"version": "0",
"versionType": "date"
}
]
}
],
"credits": [
{
"lang": "en",
"type": "finder",
"value": "Liv Matan from Tenable."
}
],
"descriptions": [
{
"lang": "en",
"supportingMedia": [
{
"base64": false,
"type": "text/html",
"value": "\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003e\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003e\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003e\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003e\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003e\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003eA SQL injection vulnerability was discovered in Looker Studio that allowed for data exfiltration from BigQuery data sources.\u003cbr\u003e \u003c/span\u003e\u003cbr\u003e\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003eBy creating a malicious report with native functions enabled, and having the victim access the report, an attacker could execute injected SQL queries with the victim\u0027s permissions in BigQuery.\u003cbr\u003e\u003c/span\u003e\u003c/span\u003e\u003cbr\u003eThis vulnerability was patched on 07 July 2025, and no customer action is needed.\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003cbr\u003e\u003c/span\u003e"
}
],
"value": "A SQL injection vulnerability was discovered in Looker Studio that allowed for data exfiltration from BigQuery data sources.\n \nBy creating a malicious report with native functions enabled, and having the victim access the report, an attacker could execute injected SQL queries with the victim\u0027s permissions in BigQuery.\n\nThis vulnerability was patched on 07 July 2025, and no customer action is needed."
}
],
"impacts": [
{
"capecId": "CAPEC-66",
"descriptions": [
{
"lang": "en",
"value": "CAPEC-66 SQL Injection"
}
]
}
],
"metrics": [
{
"cvssV4_0": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "PRESENT",
"attackVector": "NETWORK",
"baseScore": 7.3,
"baseSeverity": "HIGH",
"exploitMaturity": "NOT_DEFINED",
"privilegesRequired": "LOW",
"providerUrgency": "CLEAR",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "ACTIVE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:N/U:Clear",
"version": "4.0",
"vulnAvailabilityImpact": "LOW",
"vulnConfidentialityImpact": "HIGH",
"vulnIntegrityImpact": "HIGH",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"format": "CVSS",
"scenarios": [
{
"lang": "en",
"value": "GENERAL"
}
]
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-89",
"description": "CWE-89 Improper Neutralization of Special Elements used in an SQL Command (\u0027SQL Injection\u0027)",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2025-11-10T09:29:08.084Z",
"orgId": "f45cbf4e-4146-4068-b7e1-655ffc2c548c",
"shortName": "GoogleCloud"
},
"references": [
{
"url": "https://cloud.google.com/support/bulletins#gcp-2025-053"
},
{
"url": "https://www.tenable.com/security/research/tra-2025-27"
}
],
"source": {
"discovery": "UNKNOWN"
},
"title": "SQL Injection in Looker Studio",
"x_generator": {
"engine": "Vulnogram 0.4.0"
}
}
},
"cveMetadata": {
"assignerOrgId": "f45cbf4e-4146-4068-b7e1-655ffc2c548c",
"assignerShortName": "GoogleCloud",
"cveId": "CVE-2025-12409",
"datePublished": "2025-11-10T08:59:15.899Z",
"dateReserved": "2025-10-28T15:17:15.305Z",
"dateUpdated": "2025-11-10T15:16:16.715Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2",
"vulnerability-lookup:meta": {
"epss": {
"cve": "CVE-2025-12409",
"date": "2026-11-04",
"epss": "0.00269",
"percentile": "0.19196"
},
"nvd": {
"cve": {
"affected": [
{
"affectedData": [
{
"defaultStatus": "unaffected",
"product": "Looker Studio",
"vendor": "Google Cloud",
"versions": [
{
"lessThan": "2025-07-07",
"status": "affected",
"version": "0",
"versionType": "date"
}
]
}
],
"source": "f45cbf4e-4146-4068-b7e1-655ffc2c548c"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "A SQL injection vulnerability was discovered in Looker Studio that allowed for data exfiltration from BigQuery data sources.\n \nBy creating a malicious report with native functions enabled, and having the victim access the report, an attacker could execute injected SQL queries with the victim\u0027s permissions in BigQuery.\n\nThis vulnerability was patched on 07 July 2025, and no customer action is needed."
},
{
"lang": "es",
"value": "Una vulnerabilidad de inyecci\u00f3n SQL fue descubierta en Looker Studio que permit\u00eda la exfiltraci\u00f3n de datos de fuentes de datos de BigQuery.\n\nAl crear un informe malicioso con funciones nativas habilitadas, y haciendo que la v\u00edctima accediera al informe, un atacante podr\u00eda ejecutar consultas SQL inyectadas con los permisos de la v\u00edctima en BigQuery.\n\nEsta vulnerabilidad fue parcheada el 07 de julio de 2025, y no se requiere ninguna acci\u00f3n por parte del cliente."
}
],
"id": "CVE-2025-12409",
"lastModified": "2026-10-07T21:10:00.200",
"metrics": {
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "PRESENT",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 7.3,
"baseSeverity": "HIGH",
"confidentialityRequirement": "NOT_DEFINED",
"exploitMaturity": "NOT_DEFINED",
"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": "LOW",
"providerUrgency": "CLEAR",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "ACTIVE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:A/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",
"version": "4.0",
"vulnAvailabilityImpact": "LOW",
"vulnConfidentialityImpact": "HIGH",
"vulnIntegrityImpact": "HIGH",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "f45cbf4e-4146-4068-b7e1-655ffc2c548c",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2025-12409",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-11-10T15:14:54.971898Z",
"version": "2.0.3"
}
}
]
},
"published": "2025-11-10T09:15:42.107",
"references": [
{
"source": "f45cbf4e-4146-4068-b7e1-655ffc2c548c",
"url": "https://cloud.google.com/support/bulletins#gcp-2025-053"
},
{
"source": "f45cbf4e-4146-4068-b7e1-655ffc2c548c",
"url": "https://www.tenable.com/security/research/tra-2025-27"
}
],
"sourceIdentifier": "f45cbf4e-4146-4068-b7e1-655ffc2c548c",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-89"
}
],
"source": "f45cbf4e-4146-4068-b7e1-655ffc2c548c",
"type": "Secondary"
}
]
}
},
"redhat_vex": {
"current_release_date": "2025-11-11T09:31:26+00:00",
"cve": "CVE-2025-12409",
"id": "CVE-2025-12409",
"initial_release_date": "2025-01-01T00:00:00+00:00",
"product_status:known_not_affected": "1",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "SQL Injection in Looker Studio",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2025/cve-2025-12409.json",
"version": "3"
},
"vulnrichment": {
"containers": {
"adp": [
{
"metrics": [
{
"other": {
"content": {
"id": "CVE-2025-12409",
"options": [
{
"Exploitation": "none"
},
{
"Automatable": "no"
},
{
"Technical Impact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-11-10T15:14:54.971898Z",
"version": "2.0.3"
},
"type": "ssvc"
}
}
],
"providerMetadata": {
"dateUpdated": "2025-11-10T15:16:12.602Z",
"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"shortName": "CISA-ADP"
},
"title": "CISA ADP Vulnrichment"
}
],
"cna": {
"affected": [
{
"defaultStatus": "unaffected",
"product": "Looker Studio",
"vendor": "Google Cloud",
"versions": [
{
"lessThan": "2025-07-07",
"status": "affected",
"version": "0",
"versionType": "date"
}
]
}
],
"credits": [
{
"lang": "en",
"type": "finder",
"value": "Liv Matan from Tenable."
}
],
"descriptions": [
{
"lang": "en",
"supportingMedia": [
{
"base64": false,
"type": "text/html",
"value": "\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003e\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003e\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003e\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003e\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003e\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003eA SQL injection vulnerability was discovered in Looker Studio that allowed for data exfiltration from BigQuery data sources.\u003cbr\u003e \u003c/span\u003e\u003cbr\u003e\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003eBy creating a malicious report with native functions enabled, and having the victim access the report, an attacker could execute injected SQL queries with the victim\u0027s permissions in BigQuery.\u003cbr\u003e\u003c/span\u003e\u003c/span\u003e\u003cbr\u003eThis vulnerability was patched on 07 July 2025, and no customer action is needed.\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003cbr\u003e\u003c/span\u003e"
}
],
"value": "A SQL injection vulnerability was discovered in Looker Studio that allowed for data exfiltration from BigQuery data sources.\n \nBy creating a malicious report with native functions enabled, and having the victim access the report, an attacker could execute injected SQL queries with the victim\u0027s permissions in BigQuery.\n\nThis vulnerability was patched on 07 July 2025, and no customer action is needed."
}
],
"impacts": [
{
"capecId": "CAPEC-66",
"descriptions": [
{
"lang": "en",
"value": "CAPEC-66 SQL Injection"
}
]
}
],
"metrics": [
{
"cvssV4_0": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "PRESENT",
"attackVector": "NETWORK",
"baseScore": 7.3,
"baseSeverity": "HIGH",
"exploitMaturity": "NOT_DEFINED",
"privilegesRequired": "LOW",
"providerUrgency": "CLEAR",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "ACTIVE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:N/U:Clear",
"version": "4.0",
"vulnAvailabilityImpact": "LOW",
"vulnConfidentialityImpact": "HIGH",
"vulnIntegrityImpact": "HIGH",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"format": "CVSS",
"scenarios": [
{
"lang": "en",
"value": "GENERAL"
}
]
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-89",
"description": "CWE-89 Improper Neutralization of Special Elements used in an SQL Command (\u0027SQL Injection\u0027)",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2025-11-10T09:29:08.084Z",
"orgId": "f45cbf4e-4146-4068-b7e1-655ffc2c548c",
"shortName": "GoogleCloud"
},
"references": [
{
"url": "https://cloud.google.com/support/bulletins#gcp-2025-053"
},
{
"url": "https://www.tenable.com/security/research/tra-2025-27"
}
],
"source": {
"discovery": "UNKNOWN"
},
"title": "SQL Injection in Looker Studio",
"x_generator": {
"engine": "Vulnogram 0.4.0"
}
}
},
"cveMetadata": {
"assignerOrgId": "f45cbf4e-4146-4068-b7e1-655ffc2c548c",
"assignerShortName": "GoogleCloud",
"cveId": "CVE-2025-12409",
"datePublished": "2025-11-10T08:59:15.899Z",
"dateReserved": "2025-10-28T15:17:15.305Z",
"dateUpdated": "2025-11-10T15:16:16.715Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2"
}
}
}
Loading…
Loading…
Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.
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.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
Loading timeline…
Loading…
Loading…
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.
Loading…
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.