CVE-2025-48379 is a heap-based buffer overflow vulnerability identified in the python-pillow library, specifically affecting versions from 11.2.0 up to but not including 11.3.0. Pillow is a widely used Python imaging library that supports various image formats, including DDS (DirectDraw Surface). The vulnerability arises when Pillow attempts to save a DDS image that is larger than 64 kilobytes encoded with default settings. During this operation, the library writes data into a heap buffer without properly verifying that there is sufficient space available, leading to a buffer overflow condition (CWE-122). This flaw can be triggered only when untrusted or maliciously crafted image data is saved as a compressed DDS image. Exploiting this vulnerability could allow an attacker with limited privileges (local access with low privileges) to cause a denial of service or potentially execute arbitrary code by corrupting memory. The CVSS v3.1 score is 7.1 (high severity), reflecting the significant impact on integrity and availability, though confidentiality is not affected. The attack vector is local (AV:L), requiring low privileges (PR:L) but no user interaction (UI:N). The vulnerability has been patched in Pillow version 11.3.0, and users are strongly advised to upgrade to this or later versions. No known exploits are currently reported in the wild, but the nature of the vulnerability warrants proactive mitigation.

For European organizations, the impact of this vulnerability depends largely on their use of the Pillow library in processing DDS images, particularly in environments where untrusted image data might be saved or manipulated. Industries such as media, gaming, digital content creation, and any sectors relying on Python-based image processing pipelines could be affected. Successful exploitation could lead to denial of service conditions, disrupting business operations, or potentially allow attackers to execute arbitrary code, compromising system integrity. This could result in data corruption, service outages, or lateral movement within networks. Given the local attack vector and requirement for low privileges, the threat is more relevant in multi-user environments or where untrusted users have access to systems running vulnerable Pillow versions. European organizations with development or production environments using Pillow for image handling should consider this a significant risk, especially if they handle untrusted image inputs. The absence of known exploits suggests a window for preemptive patching and mitigation before active attacks emerge.

1. Immediate upgrade of the Pillow library to version 11.3.0 or later to apply the official patch addressing the buffer overflow. 2. Audit and restrict the handling of untrusted DDS image files within applications, ensuring that only trusted sources are allowed to save or process such images. 3. Implement strict input validation and sandboxing for any image processing components that use Pillow, limiting the potential impact of malformed or malicious images. 4. Employ runtime protections such as Address Space Layout Randomization (ASLR) and Data Execution Prevention (DEP) on systems running vulnerable versions to reduce exploitation likelihood. 5. Monitor systems for unusual crashes or memory corruption symptoms that could indicate attempted exploitation. 6. Review and limit user privileges to minimize the risk posed by low-privilege attackers. 7. Incorporate this vulnerability into vulnerability management and patching cycles, ensuring timely updates across all environments.