Memory Corruption in libxml2 via sch:name -> DoS
CVE-2025-49796 Published on June 16, 2025

A vulnerability was found in libxml2. Processing certain sch:name elements from the input XML file can trigger a memory corruption issue. This flaw allows an attacker to craft a malicious XML input file that can lead libxml to crash, resulting in a denial of service or other possible undefined behavior due to sensitive data being corrupted in memory.

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Vulnerability Analysis

CVE-2025-49796 is exploitable with network access, and does not require authorization privileges or user interaction. This vulnerability is considered to have a low attack complexity. The potential impact of an exploit of this vulnerability is considered to have no impact on confidentiality, a high impact on integrity and availability.

Attack Vector:
NETWORK
Attack Complexity:
LOW
Privileges Required:
NONE
User Interaction:
NONE
Scope:
UNCHANGED
Confidentiality Impact:
NONE
Integrity Impact:
HIGH
Availability Impact:
HIGH

Weakness Type

Out-of-bounds Read

The software reads data past the end, or before the beginning, of the intended buffer. Typically, this can allow attackers to read sensitive information from other memory locations or cause a crash. A crash can occur when the code reads a variable amount of data and assumes that a sentinel exists to stop the read operation, such as a NUL in a string. The expected sentinel might not be located in the out-of-bounds memory, causing excessive data to be read, leading to a segmentation fault or a buffer overflow. The software may modify an index or perform pointer arithmetic that references a memory location that is outside of the boundaries of the buffer. A subsequent read operation then produces undefined or unexpected results.


Products Associated with CVE-2025-49796

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Vulnerable Packages

The following package name and versions may be associated with CVE-2025-49796

Package Manager Vulnerable Package Versions Fixed In
rubygems nokogiri < 1.18.9 1.18.9

Exploit Probability

EPSS
0.46%
Percentile
63.31%

EPSS (Exploit Prediction Scoring System) scores estimate the probability that a vulnerability will be exploited in the wild within the next 30 days. The percentile shows you how this score compares to all other vulnerabilities.