VulnerabilityPublished 14 Aug 2025

CVE-2025-8713: PostgreSQL · Exposure of Sensitive Information Through Metadata

Affects PostgreSQLSource CVE Database V5

Mentioned vulnerabilities

Not known to be exploited · CVSS 3.1 Low.

Data as of 26 Oct 2026, 09:16 UTC

CVSS 3.1 base score

3.1Low

How severe the flaw is on the 0–10 CVSS scale.

EPSS: 0.2% chance of exploitation in 30 days – higher than 14% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

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

Attack Vector: Network
Attack Complexity: High
Privileges Required: Low
User Interaction: None
Scope: Unchanged
Confidentiality: Low
Integrity: None
Availability: None

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Network: The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed, up to and including the entire Internet. Such a vulnerability is often termed 'remotely exploitable' and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).
Attack Complexity: High: A successful attack depends on conditions beyond the attacker's control. That is, a successful attack cannot be accomplished at will, but requires the attacker to invest in some measurable amount of effort in preparation or execution against the vulnerable component before a successful attack can be expected. For example, a successful attack may require an attacker to: gather knowledge about the environment in which the vulnerable target/component exists; prepare the target environment to improve exploit reliability; or inject themselves into the logical network path between the target and the resource requested by the victim in order to read and/or modify network communications (e.g., a man in the middle attack).
Privileges Required: Low: The attacker is authorized with (i.e., requires) privileges that provide basic user capabilities that could normally affect only settings and files owned by a user. Alternatively, an attacker with Low privileges may have the ability to cause an impact only to non-sensitive resources.
User Interaction: None: The vulnerable system can be exploited without any interaction from any user.
Scope: Unchanged: An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.
Confidentiality: Low: There is some loss of confidentiality. Access to some restricted information is obtained, but the attacker does not have control over what information is obtained, or the amount or kind of loss is limited. The information disclosure does not cause a direct, serious loss to the impacted component.
Integrity: None: There is no loss of integrity within the impacted component.
Availability: None: There is no impact to availability within the impacted component.

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 14 Aug 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponised: Public exploit code exists in Metasploit or Exploit-DB, or CISA SSVC reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Affected software

Product	Affected	Fixed in
PostgreSQL	Affected =17 =16 =15 =14 =0	Fixed in–

AI-suggested

To mitigate this vulnerability, European organizations should promptly upgrade PostgreSQL to the fixed versions: 17.6, 16.10, 15.14, 14.19, or 13.22, depending on their current deployment. If immediate upgrading is not feasible, organizations should review and tighten database user privileges to minimize access to potentially leaky operators and restrict the ability to query optimizer statistics. Implementing strict monitoring and auditing of database queries that access statistical metadata can help detect suspicious activity. Additionally, organizations should evaluate the use of row security policies and view definitions to ensure they do not inadvertently expose sensitive data through metadata. Applying network segmentation and limiting database access to trusted users and applications will reduce the attack surface. Finally, organizations should stay informed about PostgreSQL security advisories and apply patches promptly to prevent exploitation.

Description

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.

Impact

For European organizations using PostgreSQL databases, this vulnerability could lead to unauthorized disclosure of sensitive information through metadata leakage. Although the direct data exposure is limited to statistical samples rather than full data rows, it can still reveal patterns, distributions, or common values within protected datasets, potentially compromising confidentiality. This is particularly concerning for sectors handling sensitive personal data, such as finance, healthcare, and government, where even partial data exposure can violate GDPR and other privacy regulations. The vulnerability could be exploited by internal threat actors or attackers who have gained limited database access but lack full privileges. While the impact on data integrity and availability is negligible, the confidentiality breach could facilitate further attacks or data inference. Given PostgreSQL's widespread use across European enterprises and public sector organizations, the risk is non-trivial, especially in environments relying heavily on row-level security policies and complex view-based access controls.

Summary

CVE-2025-8713 is a vulnerability in PostgreSQL that allows unauthorized users to infer sensitive information through the database's optimizer statistics. PostgreSQL collects statistics on table data by sampling column values, which are used by the query planner to optimize execution. However, this sampled data, including histograms and most-common-values lists, can inadvertently expose information about data in views or rows protected by access control lists (ACLs) and row security policies. Specifically, a user with limited privileges can craft queries using specially designed operators that bypass view ACLs and row-level security policies, thereby accessing statistical metadata that reveals information about data they should not see. This vulnerability affects PostgreSQL versions prior to 17.6, 16.10, 15.14, 14.19, and 13.22. Previous CVEs (CVE-2017-7484 and CVE-2019-10130) addressed similar issues but did not fully close this attack vector. The CVSS score is 3.1 (low severity), reflecting limited confidentiality impact and requiring network access with low privileges but high attack complexity and no user interaction. No known exploits are currently reported in the wild. The vulnerability does not impact data integrity or availability but poses a risk of sensitive data exposure through metadata leakage, which could aid attackers in reconnaissance or targeted attacks.

References

postgresql.org/support/security/CVE-2025-8713/ (opens in a new tab)

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 14 Aug 2025, 13:34 UTC

Technical details

References

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