CVE-2014-3589 in Pillow
Summary
by MITRE
PIL/IcnsImagePlugin.py in Python Imaging Library (PIL) and Pillow before 2.3.2 and 2.5.x before 2.5.2 allows remote attackers to cause a denial of service via a crafted block size.
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Analysis
by VulDB Data Team • 03/28/2022
The vulnerability identified as CVE-2014-3589 represents a denial of service flaw affecting the Python Imaging Library and its fork Pillow. This issue specifically targets the IcnsImagePlugin.py module which handles icns file format processing. The vulnerability stems from inadequate input validation during the parsing of block size parameters within icns image files, creating a condition where malformed data can trigger unexpected behavior in the image processing pipeline.
The technical flaw manifests when the PIL or Pillow library encounters a crafted icns file containing an invalid block size value. During the parsing process, the library fails to properly validate the block size parameter, allowing an attacker to provide malicious data that causes the processing routine to enter an infinite loop or consume excessive system resources. This type of vulnerability falls under CWE-129, which addresses insufficient validation of length of input buffers, and specifically relates to improper input validation in image format parsers. The vulnerability is particularly concerning because it can be triggered through any application that utilizes PIL or Pillow for image processing, including web applications that accept user-uploaded images.
The operational impact of this vulnerability extends beyond simple service disruption, as it can be exploited remotely through web applications or any system that processes icns files from untrusted sources. Attackers can craft specially formatted icns files that, when processed by vulnerable versions of PIL or Pillow, cause the target system to consume excessive CPU cycles or memory resources. This can lead to significant performance degradation or complete system unavailability, particularly in environments where multiple image processing operations occur simultaneously. The vulnerability affects a wide range of applications including content management systems, web platforms, and image processing services that rely on these libraries for handling image uploads and conversions.
Mitigation strategies for CVE-2014-3589 primarily involve upgrading to patched versions of PIL or Pillow where the issue has been resolved through proper input validation and bounds checking. Organizations should prioritize updating their dependencies to versions 2.3.2 or 2.5.2 and later, which include the necessary safeguards against malformed block size values. Additionally, implementing proper input validation at application level can provide an additional layer of protection, ensuring that image files are validated before processing and that any file size parameters are strictly checked against expected ranges. Security measures should also include monitoring for unusual resource consumption patterns that might indicate exploitation attempts, and implementing rate limiting for image upload operations to prevent abuse of the vulnerability. This vulnerability demonstrates the importance of robust input validation in multimedia processing libraries and aligns with ATT&CK technique T1499.004 for avoiding detection through resource exhaustion attacks.