CVE-2025-64505 is a heap buffer over-read vulnerability identified in the widely used libpng library, specifically in versions prior to 1.6.51. Libpng is a reference library for reading, creating, and manipulating PNG images, integral to many software applications across platforms. The vulnerability exists in the png_do_quantize function, which handles color quantization by mapping image palette indices. The flaw arises because the function does not properly validate the bounds of the palette_lookup array against externally supplied image data. An attacker can exploit this by crafting a PNG file with palette indices that exceed the valid range, causing the function to read memory beyond the allocated buffer. This out-of-bounds read can lead to application instability, crashes, or denial of service conditions. The CVSS 3.1 base score is 6.1 (medium severity), reflecting that exploitation requires local access (AV:L), low attack complexity (AC:L), no privileges (PR:N), but user interaction (UI:R) is necessary, and the impact is limited to confidentiality loss (C:L) and availability (A:H) without integrity impact. No known exploits have been reported in the wild as of publication. The vulnerability was patched in libpng version 1.6.51, which includes proper bounds checking to prevent out-of-bounds reads. Applications that embed or link against vulnerable libpng versions are at risk when processing untrusted PNG files, especially in environments where users might open images from external sources. This vulnerability highlights the importance of validating image data and promptly applying upstream library patches.

For European organizations, this vulnerability poses a risk primarily to the availability of applications that process PNG images using vulnerable libpng versions. Media companies, digital publishers, web service providers, and software vendors that handle image uploads or rendering are particularly at risk. A successful exploit could cause application crashes or denial of service, disrupting business operations and user experience. Although the confidentiality impact is low, repeated crashes could be leveraged for targeted disruption or as part of a larger attack chain. The requirement for user interaction limits remote exploitation but does not eliminate risk, especially in environments where users frequently handle untrusted image files. Organizations with automated image processing pipelines or public-facing services accepting PNG uploads should be cautious. The vulnerability could also affect embedded systems or IoT devices using libpng, potentially impacting availability in critical infrastructure. Given the widespread use of libpng, the scope of affected systems is broad, increasing the potential impact across multiple sectors in Europe.

The primary mitigation is to upgrade libpng to version 1.6.51 or later, which contains the patch that properly validates palette indices to prevent out-of-bounds reads. Organizations should audit their software dependencies to identify any usage of vulnerable libpng versions and coordinate with software vendors to ensure updates are applied promptly. For applications that cannot immediately upgrade, implement input validation to reject PNG files with suspicious or malformed palette data. Employ sandboxing or containerization for image processing components to limit the impact of potential crashes. Monitor application logs and crash reports for anomalies related to PNG handling to detect exploitation attempts early. Educate users about the risks of opening untrusted image files and enforce policies restricting the use of images from unverified sources. In environments with automated image ingestion, implement file integrity checks and malware scanning to reduce exposure. Finally, maintain an incident response plan that includes handling denial of service scenarios caused by malformed image files.