CVE-2025-14932 is a stack-based buffer overflow vulnerability classified under CWE-121, found in the NSF Unidata NetCDF-C library, a widely used C library for array-oriented scientific data, particularly in meteorology, climatology, and geospatial domains. The vulnerability specifically occurs during the parsing of time unit strings, where the library fails to properly validate the length of user-supplied input before copying it into a fixed-length stack buffer. This lack of bounds checking allows an attacker to overflow the buffer, potentially overwriting the stack and enabling arbitrary code execution. Exploitation requires user interaction, such as opening a maliciously crafted NetCDF file or visiting a webpage that triggers the vulnerable code path. The attack vector is local or remote with low complexity and no privileges required, but user interaction is necessary. The vulnerability impacts confidentiality, integrity, and availability by allowing execution of arbitrary code with the privileges of the current user. The affected version is identified by a specific commit hash, indicating a particular snapshot of the NetCDF-C codebase. No official patches or fixes have been linked yet, and no known exploits have been reported in the wild. The vulnerability was assigned a CVSS v3.0 score of 7.8, reflecting high severity due to its potential impact and ease of exploitation once user interaction occurs.

For European organizations, the impact of CVE-2025-14932 can be significant, particularly for research institutions, meteorological agencies, environmental monitoring centers, and any entities relying on NetCDF-C for scientific data processing. Successful exploitation could lead to remote code execution, allowing attackers to compromise sensitive scientific data, manipulate datasets, or disrupt critical data processing workflows. This could affect data confidentiality by exposing proprietary or sensitive environmental data, integrity by altering datasets, and availability by causing application crashes or system compromise. Given the widespread use of NetCDF-C in scientific communities across Europe, including in countries with advanced research infrastructure, the threat could disrupt scientific research and data-driven decision-making. Additionally, compromised systems could be leveraged as footholds for further network intrusion or espionage. The requirement for user interaction limits mass exploitation but targeted spear-phishing or malicious file distribution campaigns could be effective vectors.

1. Restrict the opening of NetCDF files from untrusted or unknown sources, especially those received via email or downloaded from unverified websites. 2. Employ application-level sandboxing or containerization for software that processes NetCDF-C files to limit the impact of potential exploitation. 3. Monitor network and endpoint logs for unusual behavior or crashes related to NetCDF-C applications. 4. Implement strict user awareness training focused on the risks of opening untrusted files or clicking unknown links, emphasizing the specific threat vector of this vulnerability. 5. Maintain an inventory of software versions using NetCDF-C and track updates from the vendor or community for patches addressing this vulnerability. 6. Consider deploying runtime application self-protection (RASP) or exploit mitigation technologies such as stack canaries, ASLR, and DEP if not already in use. 7. If feasible, perform code audits or use fuzz testing tools on internal applications that integrate NetCDF-C to identify and mitigate similar vulnerabilities proactively. 8. Isolate critical scientific data processing environments from general user workstations to reduce exposure.