CVE Tools

CVE-2025-8713

PostgreSQL optimizer statistics can expose sampled data within a view, partition, or child table

No known exploitation. EPSS puts it in the 13th percentile. A vendor fix is available.

Published Updated Sources: CVE.org, NVD, BDU

What to do

The vendor has published a fix. Version details are below where the sources state them.

What it is

From the CVE record

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.

In plain language

No plain-language summary for this CVE yet.

Exploitation

Where each signal puts this CVE on the scale from published to confirmed exploited.

EPSS13th
CISA KEV

Not in the catalog. CISA has not confirmed exploitation.

Public exploits

No public exploit or proof of concept found in the sources we track.

EPSS

0.2% chance of exploitation activity in the next 30 days, which ranks it in the 13th percentile of scored CVEs.

Exploit Prediction Scoring System, FIRST.org. A probability, not a confirmation.

Lifecycle

5 events over 315 days, from the signal feeds we watch.

  1. OpenVAS check added
  2. Patch availablerecord updated
  3. Publishedweakness classified

Affected products

Technical detail

CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:N/A:N

Scored 3.1 by NVD.

How it is reached

  • Attack Vector NetworkExploitable remotely over the network without any special conditions
  • Attack Complexity HighRequires specific conditions like a race condition or non-default configuration
  • Privileges Required LowRequires basic user-level privileges
  • User Interaction NoneNo user interaction needed — fully automated exploitation

Scope

  • Scope UnchangedImpact is limited to the vulnerable component itself

Impact if exploited

  • Confidentiality LowSome restricted information is disclosed, but limited in scope
  • Integrity NoneNo integrity impact
  • Availability NoneNo availability impact

Weaknesses

Sources

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