UBUNTU-CVE-2025-8713 (CVE-2025-8713)
Vulnerability from osv_ubuntu – Published: 2025-08-14 13:15 – Updated: 2026-04-22 07:53 – Source website
VLAI
Details
PostgreSQL optimizer statistics allow a user to read sampled data within a view that the user cannot access. Separately, statistics allow a user to read sampled data that a row security policy intended to hide. PostgreSQL maintains statistics for tables by sampling data available in columns; this data is consulted during the query planning process. Prior to this release, a user could craft a leaky operator that bypassed view access control lists (ACLs) and bypassed row security policies in partitioning or table inheritance hierarchies. Reachable statistics data notably included histograms and most-common-values lists. CVE-2017-7484 and CVE-2019-10130 intended to close this class of vulnerability, but this gap remained. Versions before PostgreSQL 17.6, 16.10, 15.14, 14.19, and 13.22 are affected.
Severity
N/A (UNKNOWN)
References
{
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"aliases": [],
"details": "PostgreSQL optimizer statistics allow a user to read sampled data within a view that the user cannot access. Separately, statistics allow a user to read sampled data that a row security policy intended to hide. PostgreSQL maintains statistics for tables by sampling data available in columns; this data is consulted during the query planning process. Prior to this release, a user could craft a leaky operator that bypassed view access control lists (ACLs) and bypassed row security policies in partitioning or table inheritance hierarchies. Reachable statistics data notably included histograms and most-common-values lists. CVE-2017-7484 and CVE-2019-10130 intended to close this class of vulnerability, but this gap remained. Versions before PostgreSQL 17.6, 16.10, 15.14, 14.19, and 13.22 are affected.",
"id": "UBUNTU-CVE-2025-8713",
"modified": "2026-04-22T07:53:19Z",
"published": "2025-08-14T13:15:00Z",
"references": [
{
"type": "REPORT",
"url": "https://ubuntu.com/security/CVE-2025-8713"
},
{
"type": "REPORT",
"url": "https://www.cve.org/CVERecord?id=CVE-2025-8713"
},
{
"type": "REPORT",
"url": "https://www.postgresql.org/about/news/postgresql-176-1610-1514-1419-1322-and-18-beta-3-released-3118/"
},
{
"type": "REPORT",
"url": "https://www.postgresql.org/support/security/CVE-2025-8713/"
},
{
"type": "ADVISORY",
"url": "https://ubuntu.com/security/notices/USN-7741-1"
}
],
"related": [
"USN-7741-1"
],
"schema_version": "1.7.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:N/A:N",
"type": "CVSS_V3"
},
{
"score": "medium",
"type": "Ubuntu"
}
],
"upstream": [
"CVE-2025-8713"
]
}
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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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