Cyber Resilience

CVE-2025-14010

Info Disclosure in Redhat Community.General

Published
04 December 2025
Modified
20 May 2026
Patch / advisory
CVSS Score v3.1 5.5
Click a component to see what it means
Raw vectorCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N
EPSS Score 0.0012 2th percentile
Risk Priority 35 floored blend · peak EPSS

Summary

CVE-2025-14010 is a medium-severity Insertion of Sensitive Information into Log File (CWE-532) vulnerability in Redhat Community.General. Its CVSS base score is 5.5 (Medium).

Operationally, ranked at the 2th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

The strongest mitigations our analysis identified map to AU-3 (Content of Audit Records) and SI-15 (Information Output Filtering) — see the control section below for these in your framework.

OWASP Top 10 for Web (2025)

EU & UK References

Vulnerability Data

A flaw was found in ansible-collection-community-general. This vulnerability allows for information exposure (IE) of sensitive credentials, specifically plaintext passwords, via verbose output when running Ansible with debug modes. Attackers with access to logs could retrieve these secrets and potentially compromise…

more

Keycloak accounts or administrative access.

CWE(s)

Related Threats

CVEs Like This One

CVE-2023-4380Same vendor: Redhat
CVE-2026-11819Same vendor: Redhat
CVE-2026-11820Same vendor: Redhat
CVE-2023-40694Same vendor: Redhat
CVE-2024-9453Same vendor: Redhat
CVE-2025-36187Same vendor: Redhat
CVE-2026-4740Same vendor: Redhat
CVE-2023-4958Same vendor: Redhat
CVE-2026-9793Same vendor: Redhat
CVE-2026-4628Same vendor: Redhat

Affected Assets

redhat
community.general
all versions

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)
  • AU-3 Content of Audit Records
  • SI-15 Information Output Filtering
  • SI-11 Error Handling
Detect
Catch it (NIST detect / respond)

Harden
Shrink the surface (DISA STIG)

Validate
Prove the fix (OWASP ASVS)

Mitigating Controls (NIST 800-53 r5) AI

prevent

Requires audit and log records to exclude sensitive credential values such as plaintext passwords from verbose or debug output.

prevent

Filters information in system outputs (including Ansible verbose/debug streams) to block unauthorized disclosure of secrets.

prevent

Ensures error and diagnostic handling routines do not expose sensitive data in logs or console output.

Mitigating Controls (NIST CSF 2.0) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.

PR.PS-06 mostly match
prevents

Secure SDLC practices directly prohibit writing sensitive data to logs; eliminating the weakness satisfies only one narrow slice of the control.

PR.PS-04 partial match
prevents

Log generation configuration can and should exclude sensitive data, but the control statement focuses on availability rather than content filtering.

Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.

A.8.15 Logging mostly match
prevents

Requiring de-identification and privacy controls before logs leave the organization reduces the chance that sensitive data inadvertently captured in logs becomes exposed to external parties.

mitigates

By defining what records must be kept, where, and for how long, the control discourages the inadvertent inclusion of sensitive information in logs or other externally accessible files that fall outside the formal record system.

mitigates

Mandating deletion of temporary files and logs that may contain sensitive information prevents those artifacts from remaining accessible after the data is no longer needed.

A.8.11 Data masking partial match
mitigates

When log entries are produced from masked data sets, the control prevents the inadvertent insertion of sensitive values into externally accessible log files.

mitigates

DLP inspection of logs and file transfers can detect and block the inadvertent placement of sensitive tokens or credentials into externally accessible log files before they are written or transmitted.

prevents

Requiring restrictions on free-text fields and proper error-message handling stops developers from embedding or leaking sensitive data into logs or diagnostic output.

References