CVE-2025-54462 is a critical heap-based buffer overflow vulnerability identified in the Nex parsing functionality of The Biosig Project's libbiosig library, specifically affecting versions 3.9.0 and the Master Branch (commit 35a819fa). Libbiosig is an open-source library used for biosignal processing, including EEG, EMG, and other physiological data formats. The vulnerability arises when the library processes specially crafted .nex files, which are used to store neural data. An attacker can exploit this flaw by supplying a maliciously crafted .nex file that triggers a heap overflow during parsing. This overflow can corrupt memory, potentially allowing arbitrary code execution without requiring any privileges or user interaction. The CVSS v3.1 base score of 9.8 reflects the high severity, with network attack vector, low attack complexity, no privileges required, and no user interaction needed. The impact includes full compromise of the host system running vulnerable versions of libbiosig, as the attacker can execute arbitrary code with the privileges of the application using the library. No known public exploits have been reported yet, and no patches are currently linked, indicating that mitigation may require manual code updates or vendor patches once available. This vulnerability is classified under CWE-122, which relates to heap-based buffer overflows, a common and dangerous class of memory corruption bugs that can lead to remote code execution and system compromise.

For European organizations, the impact of this vulnerability can be significant, particularly for research institutions, medical facilities, and companies involved in biosignal analysis and neurotechnology that rely on libbiosig for processing neural data. Exploitation could lead to unauthorized system access, data theft, or disruption of critical research and healthcare operations. Given the criticality and ease of exploitation, attackers could leverage this flaw to implant malware, exfiltrate sensitive patient or research data, or disrupt services. The lack of required privileges and user interaction means that automated attacks could be launched remotely, increasing the risk of widespread compromise. Additionally, organizations involved in neuroscience research or medical device development in Europe could face regulatory and compliance repercussions if patient data confidentiality or system integrity is breached due to this vulnerability.

Immediate mitigation should focus on restricting exposure to untrusted .nex files by implementing strict input validation and sandboxing of applications using libbiosig. Organizations should monitor for updates from The Biosig Project and apply patches as soon as they become available. In the interim, consider disabling or limiting the use of the Nex parsing functionality if feasible. Employ application-level protections such as Address Space Layout Randomization (ASLR), Data Execution Prevention (DEP), and Control Flow Integrity (CFI) to reduce exploitation success. Network-level defenses like intrusion detection systems (IDS) and file scanning for malformed .nex files can help detect and block attempts to exploit this vulnerability. Additionally, organizations should audit their environments to identify all instances of libbiosig usage and ensure that only trusted personnel handle .nex files. Incorporating strict file handling policies and user training on the risks of opening untrusted biosignal files will further reduce exposure.