CVE-2025-57775 is a heap-based buffer overflow vulnerability identified in Digilent's DASYLab software, which is used for data acquisition and control applications. The root cause of this vulnerability lies in improper bounds checking when parsing DSB files, the proprietary file format used by DASYLab. Specifically, the software fails to correctly validate the specified index, position, or offset within the input data, leading to a heap buffer overflow condition. This flaw is classified under CWE-1285, which relates to improper validation of specified index, position, or offset in input. Exploitation requires an attacker to craft a malicious DSB file and convince a user to open it within DASYLab. Upon opening the specially crafted file, the heap overflow can be triggered, potentially allowing arbitrary code execution with the privileges of the user running the application. The vulnerability affects all versions of DASYLab, indicating a long-standing issue in the product's file parsing logic. The CVSS v3.1 base score is 7.8, reflecting high severity due to the combination of local attack vector (AV:L), low attack complexity (AC:L), no privileges required (PR:N), but requiring user interaction (UI:R). The impact includes full confidentiality, integrity, and availability compromise (C:H/I:H/A:H). No patches or mitigations have been published at the time of disclosure, and no known exploits are reported in the wild yet. Given the nature of the software, which is often used in industrial, research, and engineering environments for data acquisition and control, successful exploitation could lead to significant operational disruption or unauthorized control over critical systems.

For European organizations, the impact of this vulnerability could be substantial, especially in sectors relying on DASYLab for data acquisition, control, and automation tasks such as manufacturing, research institutions, energy, and utilities. Exploitation could lead to arbitrary code execution, enabling attackers to manipulate data acquisition processes, disrupt operational technology (OT) environments, or exfiltrate sensitive data. This could result in operational downtime, loss of data integrity, and potential safety hazards if control systems are affected. Confidentiality breaches could expose proprietary research or industrial process data. The requirement for user interaction (opening a malicious file) suggests that targeted spear-phishing or social engineering campaigns could be effective attack vectors. The lack of patches increases the risk window for European entities until mitigations or updates are released. Additionally, the high integrity and availability impact could affect compliance with European regulations such as GDPR (due to data breaches) and NIS Directive (due to operational disruptions in critical infrastructure).

Given the absence of official patches, European organizations should implement the following specific mitigations: 1) Restrict DSB file handling to trusted sources only; implement strict policies to prevent opening DSB files from unverified or external origins. 2) Employ application whitelisting and sandboxing techniques to limit the execution context of DASYLab, reducing the impact of potential code execution. 3) Enhance user awareness and training focused on recognizing phishing attempts and suspicious file attachments, emphasizing the risks of opening unsolicited DSB files. 4) Monitor network and host activity for anomalous behavior indicative of exploitation attempts, such as unexpected process spawning or memory corruption indicators. 5) Where feasible, isolate systems running DASYLab from critical networks to contain potential compromises. 6) Engage with Digilent for updates and subscribe to vulnerability advisories to apply patches promptly once available. 7) Consider implementing endpoint detection and response (EDR) solutions capable of detecting heap overflow exploitation techniques. These targeted measures go beyond generic advice by focusing on the specific attack vector (malicious DSB files) and operational context of DASYLab.