CVE-2025-47814 is a medium-severity heap-based buffer overflow vulnerability identified in the GNU PSPP software, specifically in the libpspp-core.a library up to version 2.0.1. The vulnerability exists in the inflate_read function, which is indirectly invoked by spv_read_xml_member within the zip-reader.c source file. This function is responsible for decompressing data streams, and due to improper bounds checking or handling of input data, an attacker can trigger a heap-based buffer overflow. This type of overflow occurs when data is written beyond the allocated heap buffer, potentially corrupting adjacent memory. Although the CVSS score is 4.5 (medium), the vulnerability's scope is significant because it affects the integrity and availability of the PSPP application. The CVSS vector indicates that the attack requires local access (AV:L), high attack complexity (AC:H), no privileges (PR:N), and no user interaction (UI:N), with a scope change (S:C) meaning the vulnerability can affect resources beyond the vulnerable component. The impact is limited to integrity and availability, with no confidentiality loss. There are no known exploits in the wild, and no patches have been linked yet. PSPP is an open-source statistical analysis software often used as a free alternative to proprietary tools like SPSS. The vulnerability arises from processing crafted compressed data within PSPP's zip reader, which could be exploited by supplying malicious input files to the application, causing crashes or potentially enabling code execution or further memory corruption under certain conditions.

For European organizations, the impact of CVE-2025-47814 depends largely on the extent to which PSPP is used within their environments. PSPP is popular in academic, research, and statistical analysis contexts, including universities, public research institutions, and some government statistical offices. A successful exploit could lead to application crashes, denial of service, or potentially arbitrary code execution if the overflow is leveraged further, thereby disrupting critical data analysis workflows. This could affect data integrity and availability, particularly in sectors relying on statistical data processing for decision-making, such as healthcare research, economic forecasting, and social sciences. Although the attack requires local access and has high complexity, insider threats or compromised local machines could exploit this vulnerability. The lack of user interaction requirement increases risk in controlled environments where malicious files might be introduced. Given the scope change, the vulnerability could allow attackers to affect system components beyond PSPP itself, increasing potential damage. However, the medium severity and absence of known exploits reduce immediate widespread risk. Still, organizations should consider the potential for targeted attacks, especially in sensitive research or governmental contexts.

European organizations should implement several specific mitigations beyond generic patching advice: 1) Restrict PSPP usage to trusted users and environments, limiting local access to systems running PSPP to reduce attack surface. 2) Implement strict file validation and sandboxing for any input files processed by PSPP, especially those involving compressed data formats, to prevent malicious crafted files from triggering the overflow. 3) Monitor and audit local user activities on systems running PSPP to detect anomalous behavior or attempts to process suspicious files. 4) Employ memory protection mechanisms such as Address Space Layout Randomization (ASLR) and Data Execution Prevention (DEP) on endpoints to mitigate exploitation impact. 5) Until an official patch is released, consider using alternative statistical software or running PSPP in isolated virtual machines or containers to contain potential exploitation. 6) Stay updated with GNU project advisories and apply patches promptly once available. 7) Educate users about the risks of processing untrusted compressed data files and enforce policies to avoid opening files from unverified sources.