CVE-2025-2924 is a heap-based buffer overflow vulnerability identified in the HDF5 library versions up to 1.14.6. The flaw resides specifically in the function H5HL__fl_deserialize within the source file src/H5HLcache.c. The vulnerability is triggered by improper handling of the 'free_block' argument during deserialization, which can lead to a heap overflow condition. This type of memory corruption can cause unpredictable behavior including application crashes or potentially arbitrary code execution. The attack vector is local, requiring the attacker to have at least low-level privileges on the host system to exploit the vulnerability. No user interaction or network access is required, but the attacker must be able to manipulate the input to the vulnerable function. Although the CVSS 4.0 base score is 4.8 (medium severity), the vulnerability's exploitation could lead to denial of service or escalation of privileges within the local environment. The vulnerability has been publicly disclosed, but no known exploits in the wild have been reported yet. HDF5 is a widely used data model, library, and file format for storing and managing large scientific data sets, commonly employed in research institutions, engineering, and data-intensive industries. The vulnerability's presence in multiple recent versions (1.14.0 through 1.14.6) indicates that many deployments could be affected if they use these versions without patching or mitigation.

For European organizations, the impact of this vulnerability depends largely on the extent to which HDF5 is integrated into their scientific computing, engineering, or data management workflows. Organizations in sectors such as research institutions, universities, aerospace, automotive, pharmaceuticals, and energy may rely heavily on HDF5 for handling large datasets. Exploitation could allow an attacker with local access to cause application crashes or potentially execute arbitrary code, leading to disruption of critical data processing tasks or unauthorized privilege escalation. This could result in data integrity issues, loss of availability of key scientific applications, or compromise of sensitive research data. Given that the attack requires local access and low privileges, insider threats or compromised user accounts pose the greatest risk. The absence of known exploits in the wild reduces immediate risk, but the public disclosure increases the likelihood of future exploitation attempts. The medium severity rating suggests that while the vulnerability is not trivial, it does not pose an immediate critical threat but should be addressed promptly to avoid escalation.

European organizations should prioritize updating HDF5 libraries to versions beyond 1.14.6 once patches become available from the maintainers. In the absence of an official patch, organizations can mitigate risk by restricting local access to systems running vulnerable HDF5 versions, enforcing strict user privilege separation, and monitoring for unusual local activity that could indicate exploitation attempts. Implementing application whitelisting and sandboxing for processes using HDF5 can reduce the impact of potential exploitation. Additionally, organizations should audit their software dependencies to identify all instances of HDF5 usage, including embedded or third-party applications, to ensure comprehensive coverage. Regularly reviewing and updating security policies related to local user access and privilege management will further reduce the attack surface. Finally, maintaining robust backup and recovery procedures will help mitigate the impact of any data corruption or availability issues resulting from exploitation.