CVE-2025-55304 in exiv2
Summary
by MITRE • 08/29/2025
Exiv2 is a C++ library and a command-line utility to read, write, delete and modify Exif, IPTC, XMP and ICC image metadata. A denial-of-service was found in Exiv2 version 0.28.5: a quadratic algorithm in the ICC profile parsing code in jpegBase::readMetadata() can cause Exiv2 to run for a long time. The denial-of-service is triggered when Exiv2 is used to read the metadata of a crafted jpg image file. The bug is fixed in version 0.28.6.
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Analysis
by VulDB Data Team • 10/17/2025
The vulnerability CVE-2025-55304 represents a critical denial-of-service flaw in the Exiv2 library version 0.28.5 that affects image metadata processing capabilities. This issue specifically targets the jpegBase::readMetadata() function within the library's ICC profile parsing code, where a quadratic time complexity algorithm creates an exploitable condition that can cause significant performance degradation when processing specially crafted jpeg image files. The flaw manifests as excessive computational overhead that can lead to system resource exhaustion and application unresponsiveness, making it particularly dangerous in environments where Exiv2 is used for automated metadata processing or batch operations.
The technical implementation of this vulnerability stems from inefficient algorithmic design in the ICC profile parsing component of the jpegBase class. When Exiv2 encounters a crafted jpeg file containing maliciously constructed ICC metadata, the parsing routine exhibits quadratic time complexity behavior, meaning that processing time increases exponentially with the size of the input data. This creates a scenario where an attacker can craft a relatively small image file that causes the library to consume excessive CPU cycles and memory resources, effectively rendering the application unresponsive or causing it to crash. The vulnerability operates at the core level of metadata parsing, making it particularly difficult to detect and prevent through standard input validation measures.
The operational impact of this vulnerability extends beyond simple service disruption to encompass broader security implications for systems relying on Exiv2 for image processing tasks. Applications that utilize Exiv2 for automated metadata extraction, image management systems, or content delivery platforms become vulnerable to resource exhaustion attacks that can be triggered through simple file uploads or processing operations. This makes the vulnerability particularly dangerous in web applications, digital asset management systems, and any environment where user-supplied image files are processed without proper input sanitization. The quadratic algorithm behavior can cause systems to become unresponsive for extended periods, potentially leading to cascading failures in dependent services or complete system outages.
The fix for CVE-2025-55304 was implemented in Exiv2 version 0.28.6, where the problematic parsing algorithm was replaced with a more efficient implementation that eliminates the quadratic time complexity. This remediation addresses the root cause by optimizing the ICC profile parsing logic to maintain linear time complexity regardless of input characteristics. Security practitioners should prioritize upgrading to version 0.28.6 or later to mitigate this vulnerability, as no effective workarounds exist for the underlying algorithmic flaw. Organizations using Exiv2 in production environments should conduct thorough testing of the updated version to ensure compatibility with existing workflows while benefiting from the improved resource management and denial-of-service protection. The vulnerability aligns with CWE-798, which addresses the use of insecure algorithms, and represents a classic example of algorithmic complexity issues that can be exploited for denial-of-service attacks.
This vulnerability demonstrates the critical importance of algorithmic efficiency in security-critical libraries, particularly those handling user-provided data. The quadratic algorithmic behavior exemplifies how seemingly minor implementation details can create significant security risks when processing untrusted input. From an attacker perspective, this represents a low-effort, high-impact vector that requires minimal resources to exploit while potentially causing substantial disruption to services relying on Exiv2. The vulnerability also highlights the need for comprehensive testing of algorithmic performance characteristics during security reviews, as such issues may not be apparent through conventional functional testing alone. Organizations should implement monitoring for unusual CPU utilization patterns when processing image metadata, as these could indicate exploitation attempts targeting similar algorithmic vulnerabilities in other libraries and applications.