Overview
CVE-2025-13837 describes a denial-of-service (DoS) vulnerability affecting Python’s plistlib module. This vulnerability arises during the parsing of plist (Property List) files. A maliciously crafted plist file can exploit the way plistlib reads data, potentially leading to excessive memory consumption and ultimately crashing the application. This is triggered when the size of data to be read is determined by the value within the potentially malicious file.
Technical Details
The vulnerability lies in how the plistlib module handles the size of data specified within the plist file itself. When loading a plist, the module reads data according to the size indicated in the file’s structure. A malicious actor can craft a plist file that specifies an extremely large data size. Consequently, when plistlib attempts to allocate memory to accommodate this size, it can exhaust available memory resources, resulting in an Out-of-Memory (OOM) condition and a denial-of-service.
Specifically, the issue resides in the unmarshalling process, where the declared size of data elements is not properly validated against system memory limits before allocation. This lack of validation allows an attacker to control the memory allocation behavior of the plistlib module.
CVSS Analysis
As of the publication of this article, a CVSS score is not available (N/A). However, given the potential for a denial-of-service, the vulnerability likely warrants a medium to high severity rating once a CVSS score is assigned. The ease of exploitation (requiring only a specially crafted plist file) increases the potential for widespread impact.
Possible Impact
The exploitation of CVE-2025-13837 can lead to the following consequences:
- Denial of Service (DoS): The most likely outcome is a denial-of-service, where the application becomes unresponsive or crashes due to excessive memory consumption.
- Application Instability: Even if a full crash is avoided, the high memory usage can lead to significant performance degradation and application instability.
- Resource Exhaustion: On shared hosting environments or systems with limited resources, exploiting this vulnerability could impact other applications running on the same system.
Mitigation and Patch Steps
The recommended mitigation is to update to a patched version of Python that addresses this vulnerability. A fix has been implemented in CPython. The following steps are advised:
- Update Python: Upgrade to the latest stable version of Python as soon as a patched version is available. Check the Python Security Center for updates.
- Sanitize Input: While patching is crucial, consider implementing input validation to check plist files for excessively large data sizes before passing them to
plistlib.load. This provides an additional layer of protection. - Monitor Resource Usage: Implement monitoring solutions to detect unusual memory consumption patterns that might indicate an attempted exploit.
Always test updates in a non-production environment before deploying them to production systems.
References
GitHub Issue #119342: plistlib: OOM when reading plist files
GitHub Pull Request #119343: Fix plistlib OOM
