CVE-2025-31178 is a vulnerability identified in the gnuplot software, specifically within the GetAnnotateString() function. This flaw results in a NULL pointer dereference, which can cause a segmentation fault leading to a system crash. The vulnerability is characterized by the software attempting to access or dereference a pointer that has not been properly initialized or has been set to NULL, resulting in an invalid memory access. This type of flaw typically causes the affected application to terminate unexpectedly, impacting availability. According to the CVSS v3.1 vector, the attack vector is local (AV:L), meaning an attacker must have local access to the system to exploit the vulnerability. The attack complexity is low (AC:L), and no privileges (PR:N) or user interaction (UI:N) are required to trigger the fault. The scope is unchanged (S:U), and the impact is limited to availability (A:H), with no confidentiality or integrity impact. The CVSS base score is 6.2, categorized as medium severity. There are no known exploits in the wild at the time of publication, and no patches or vendor advisories have been linked yet. The vulnerability does not affect confidentiality or integrity but can cause denial of service by crashing the gnuplot process or potentially the host system if gnuplot is run with elevated privileges or as part of critical workflows. Gnuplot is a widely used plotting utility in scientific, engineering, and academic environments for data visualization, often integrated into automated data processing pipelines. A crash in gnuplot could disrupt these workflows, causing operational downtime or loss of productivity. Since the attack vector is local, exploitation requires an attacker to have access to the system, which limits remote exploitation but does not eliminate risk in multi-user or shared environments.

For European organizations, the impact of CVE-2025-31178 depends largely on the deployment context of gnuplot. Organizations in research institutions, universities, engineering firms, and data analytics companies that rely on gnuplot for automated plotting and data visualization could experience service interruptions or workflow disruptions if this vulnerability is exploited. The denial of service caused by a segmentation fault could halt critical data processing tasks, potentially delaying research outputs or business decisions. While the vulnerability does not expose sensitive data or allow code execution, the availability impact could be significant in environments where gnuplot is integrated into larger automated systems or where uptime is critical. In multi-user systems or shared computing environments common in European academic and research institutions, an attacker with local access could intentionally trigger the crash to disrupt other users’ work. The lack of known exploits in the wild reduces immediate risk, but the presence of a medium severity vulnerability in a widely used tool warrants proactive mitigation to avoid potential exploitation or accidental crashes.

1. Restrict local access: Limit user permissions to only those who require access to systems running gnuplot to reduce the risk of local exploitation. 2. Monitor and audit usage: Implement monitoring to detect abnormal crashes or segmentation faults in gnuplot processes, enabling rapid response to potential exploitation attempts. 3. Isolate gnuplot usage: Run gnuplot in sandboxed or containerized environments where possible to contain the impact of crashes and prevent system-wide disruption. 4. Update and patch: Although no patches are currently linked, organizations should track vendor advisories and apply updates promptly once a fix is released. 5. Input validation: Where gnuplot is used in automated workflows, validate and sanitize input data to avoid triggering the vulnerable code path unintentionally. 6. Backup workflows and data: Maintain backups of critical data and scripts to minimize operational impact in case of crashes. 7. Educate users: Inform users about the vulnerability and encourage reporting of any unusual application behavior to IT security teams.