CVE-2026-1484: Out-of-bounds Write in Red Hat Red Hat Enterprise Linux 10
A flaw was found in the GLib Base64 encoding routine when processing very large input data. Due to incorrect use of integer types during length calculation, the library may miscalculate buffer boundaries. This can cause memory writes outside the allocated buffer. Applications that process untrusted or extremely large Base64 input using GLib may crash or behave unpredictably.
AI Analysis
Technical Summary
This vulnerability involves an out-of-bounds write in the GLib Base64 encoding routine due to improper integer handling when processing very large input data. The miscalculation of buffer boundaries can cause memory corruption, potentially leading to application crashes or unpredictable behavior. It affects Red Hat Enterprise Linux 10 systems that use GLib for Base64 processing. The CVSS 3.1 score is 4.2 (medium), reflecting network attack vector with high attack complexity, no privileges required, user interaction needed, unchanged scope, no confidentiality impact, low integrity impact, and low availability impact.
Potential Impact
The vulnerability can cause applications that process untrusted or very large Base64 input to crash or behave unpredictably due to memory corruption from out-of-bounds writes. There is no direct confidentiality impact. Integrity and availability impacts are low but present. No known exploits in the wild have been reported, reducing immediate risk.
Mitigation Recommendations
Patch status is not yet confirmed — check the Red Hat advisory at https://access.redhat.com/security/cve/CVE-2026-1484 for current remediation guidance. Until an official fix is available, avoid processing untrusted or extremely large Base64 input with affected GLib versions. Monitor vendor communications for updates on patches or workarounds.
CVE-2026-1484: Out-of-bounds Write in Red Hat Red Hat Enterprise Linux 10
Description
A flaw was found in the GLib Base64 encoding routine when processing very large input data. Due to incorrect use of integer types during length calculation, the library may miscalculate buffer boundaries. This can cause memory writes outside the allocated buffer. Applications that process untrusted or extremely large Base64 input using GLib may crash or behave unpredictably.
CVSS v3.1
Score 4.2medium
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
This vulnerability involves an out-of-bounds write in the GLib Base64 encoding routine due to improper integer handling when processing very large input data. The miscalculation of buffer boundaries can cause memory corruption, potentially leading to application crashes or unpredictable behavior. It affects Red Hat Enterprise Linux 10 systems that use GLib for Base64 processing. The CVSS 3.1 score is 4.2 (medium), reflecting network attack vector with high attack complexity, no privileges required, user interaction needed, unchanged scope, no confidentiality impact, low integrity impact, and low availability impact.
Potential Impact
The vulnerability can cause applications that process untrusted or very large Base64 input to crash or behave unpredictably due to memory corruption from out-of-bounds writes. There is no direct confidentiality impact. Integrity and availability impacts are low but present. No known exploits in the wild have been reported, reducing immediate risk.
Mitigation Recommendations
Patch status is not yet confirmed — check the Red Hat advisory at https://access.redhat.com/security/cve/CVE-2026-1484 for current remediation guidance. Until an official fix is available, avoid processing untrusted or extremely large Base64 input with affected GLib versions. Monitor vendor communications for updates on patches or workarounds.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- redhat
- Date Reserved
- 2026-01-27T11:58:49.994Z
- Cvss Version
- 3.1
- State
- PUBLISHED
- Vendor Advisory Urls
- [{"url":"https://access.redhat.com/security/cve/CVE-2026-1484","vendor":"Red Hat"}]
Threat ID: 6978c6444623b1157c2c3085
Added to database: 01/27/2026, 14:05:56 UTC
Last enriched: 06/02/2026, 20:07:21 UTC
Last updated: 09/10/2026, 19:36:52 UTC
Views: 207
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