CVE-2025-54487 is a critical stack-based buffer overflow vulnerability identified in the MFER parsing functionality of The Biosig Project's libbiosig library, specifically versions 3.9.0 and the current master branch (commit 35a819fa). The vulnerability arises in the biosig.c source file at line 8842, within the handling of Tag 12 (0x0C), which corresponds to the sampling resolution field in the MFER file format. The vulnerable code reads a length value 'len' from the input file and then attempts to read 'len-2' bytes into a fixed-size buffer without adequate bounds checking. When 'len' is greater than 130, this leads to a buffer overflow due to writing beyond the buffer's allocated size. Conversely, if 'len' is less than 2, an integer underflow occurs when calculating 'len-2', resulting in a very large unsigned value that also causes a buffer overflow. This improper validation allows an attacker to craft a malicious MFER file that, when parsed by libbiosig, can trigger arbitrary code execution on the host system. The vulnerability requires no authentication or user interaction beyond processing the malicious file, and it is remotely exploitable if the application processes untrusted MFER files. The CVSS v3.1 base score is 9.8, reflecting the critical nature of this flaw with network attack vector, low attack complexity, no privileges or user interaction required, and high impact on confidentiality, integrity, and availability. Currently, no public exploits are known in the wild, and no official patches have been linked yet. However, the vulnerability is publicly disclosed and should be considered urgent for remediation in any environment using libbiosig for biosignal data processing.

For European organizations, the impact of CVE-2025-54487 can be significant, especially those involved in biomedical research, healthcare, and neuroinformatics where biosignal data processing is common. libbiosig is used to parse and analyze biosignal data formats such as MFER, which are prevalent in medical devices, research tools, and clinical data analysis software. Exploitation of this vulnerability could allow attackers to execute arbitrary code remotely, potentially leading to full system compromise. This could result in unauthorized access to sensitive patient data, manipulation or destruction of critical medical research data, disruption of healthcare services, and violation of data protection regulations such as GDPR. The critical severity and ease of exploitation mean that attackers could leverage this flaw to infiltrate networks, deploy ransomware, or conduct espionage against healthcare providers and research institutions. Given the strategic importance of healthcare infrastructure in Europe and the increasing targeting of medical devices by cyber adversaries, this vulnerability poses a high risk to confidentiality, integrity, and availability of critical systems.

To mitigate CVE-2025-54487, European organizations should take the following specific actions: 1) Immediately identify all systems and applications using libbiosig versions 3.9.0 or the affected master branch, including embedded medical devices, research software, and data analysis pipelines. 2) Monitor vendor announcements and community repositories for patches or updated versions of libbiosig that address this buffer overflow and apply them as soon as they become available. 3) Implement strict input validation and sandboxing around any component that processes MFER files to limit the impact of potential exploitation. 4) Employ application whitelisting and runtime protection mechanisms to detect and block abnormal behavior indicative of exploitation attempts. 5) Restrict access to systems processing biosignal data to trusted users and networks, minimizing exposure to untrusted MFER files. 6) Conduct code audits and penetration testing focused on biosignal processing components to identify any additional weaknesses. 7) Educate relevant personnel about the risks of processing untrusted biosignal files and enforce policies to verify file provenance. These targeted measures go beyond generic advice by focusing on the specific context and usage of libbiosig in biosignal data environments.