CVE-2024-28219 identifies a buffer overflow vulnerability in the Pillow library, a widely used Python imaging library, specifically in the _imagingcms.c source file. The root cause is the use of the unsafe strcpy function, which does not limit the number of bytes copied, instead of the safer strncpy function that bounds the copy length. This programming error allows an attacker to overflow a buffer by supplying specially crafted image data, potentially leading to memory corruption. The vulnerability affects versions of Pillow prior to 10.3.0, although exact affected versions are not specified. The CVSS 3.1 base score is 6.7, indicating medium severity, with the vector string CVSS:3.1/AC:H/AV:L/A:H/C:H/I:H/PR:L/S:U/UI:R. This means the attack requires low privileges, local access, and user interaction, with high impact on availability, confidentiality, and integrity. No public exploits have been reported yet, but the vulnerability could be leveraged for denial of service or arbitrary code execution if exploited successfully. The CWE-680 classification corresponds to 'Integer Overflow to Buffer Overflow,' consistent with the strcpy misuse. The vulnerability is particularly relevant for applications that process untrusted image files using Pillow, such as web services, image processing pipelines, or desktop applications. Since Pillow is a common dependency in Python environments, the scope of affected systems is broad but limited by the need for local access and user interaction.

For European organizations, the impact of CVE-2024-28219 depends on their use of the Pillow library in processing image data. Organizations in sectors such as media, healthcare, finance, and government that handle large volumes of images or rely on Python-based applications could face risks including denial of service, data corruption, or potential privilege escalation if the vulnerability is exploited. The high impact on confidentiality, integrity, and availability means sensitive data could be exposed or altered, and critical services disrupted. The requirement for local access and user interaction reduces the likelihood of remote exploitation but does not eliminate insider threats or exploitation via social engineering. Additionally, organizations using containerized or cloud environments with Pillow dependencies should verify their images and update accordingly. Failure to patch could lead to targeted attacks exploiting this vulnerability, especially in environments where image processing is automated and exposed to untrusted inputs.

To mitigate CVE-2024-28219, organizations should immediately upgrade Pillow to version 10.3.0 or later, where the strcpy usage has been replaced with safer functions. Conduct a thorough inventory of all Python environments and applications that use Pillow, including development, testing, and production systems. Implement strict input validation and sanitization for all image files processed by applications to reduce the risk of malicious payloads triggering the overflow. Employ runtime protections such as Address Space Layout Randomization (ASLR) and Data Execution Prevention (DEP) to limit the impact of potential exploits. Monitor logs and system behavior for anomalies related to image processing components. For environments where immediate patching is not feasible, consider isolating image processing workloads in sandboxed or containerized environments to contain potential exploitation. Educate users about the risks of opening untrusted image files and enforce least privilege principles to minimize the impact of local exploitation.