CVE-2025-14934 is a stack-based buffer overflow vulnerability classified under CWE-121, found in the NSF Unidata NetCDF-C library, which is widely used for array-oriented scientific data management, particularly in meteorology and geosciences. The vulnerability specifically exists in the parsing logic for variable names, where the software fails to properly validate the length of user-supplied input before copying it into a fixed-size stack buffer. This lack of bounds checking enables an attacker to overflow the buffer, potentially overwriting the stack and allowing arbitrary code execution in the context of the current user. Exploitation requires user interaction, such as opening a maliciously crafted NetCDF file or visiting a web page that triggers the vulnerable parsing routine. The vulnerability does not require prior authentication or elevated privileges, increasing its risk profile. The CVSS 3.0 score of 7.8 reflects high impact on confidentiality, integrity, and availability, with low attack complexity but requiring user interaction. No patches or exploits are currently publicly available, but the vulnerability was assigned ZDI-CAN-27267 and published on December 23, 2025. Given the critical role of NetCDF-C in scientific data workflows, this vulnerability poses a significant risk to environments processing such data.

For European organizations, especially those involved in scientific research, meteorology, climate modeling, and geospatial data analysis, this vulnerability could lead to severe consequences. Successful exploitation may result in remote code execution, allowing attackers to gain control over affected systems, steal sensitive research data, manipulate scientific results, or disrupt critical data processing pipelines. This could undermine research integrity, cause data loss, or lead to operational downtime. Additionally, compromised systems could be leveraged as footholds for further network intrusion or lateral movement within research institutions or government agencies. The requirement for user interaction somewhat limits mass exploitation but targeted spear-phishing or malicious file distribution campaigns could be effective. The impact on confidentiality, integrity, and availability is high, making this a significant threat to organizations relying on NetCDF-C in Europe.

Organizations should immediately inventory their use of NSF Unidata NetCDF-C libraries and identify affected versions. Although no patches are currently listed, monitoring for vendor updates or security advisories is critical. In the interim, implement strict input validation and sandboxing of applications processing NetCDF files to limit exposure. Employ application whitelisting and restrict user permissions to minimize the impact of potential code execution. Enhance user awareness training to recognize and avoid opening suspicious files or links. Network-level defenses such as email filtering and web content scanning can reduce the risk of malicious file delivery. Consider isolating systems handling NetCDF data from critical networks to contain potential breaches. Regularly update endpoint protection and intrusion detection systems to detect anomalous behavior indicative of exploitation attempts. Finally, establish incident response plans tailored to scientific data environments to quickly address any compromise.