A refcounting issue which leads to potential memory leak was discovered in scipy commit 8627df31ab in Py_FindObjects() function. Note: This is disputed as a bug and not a vulnerability. SciPy is not designed to be exposed to untrusted users or data directly.
This vulnerability carries a MEDIUM severity rating with a CVSS v3.1 score of 5.5, requiring local system access to exploit with relatively low complexity without requiring user interaction requiring only low-level privileges . The vulnerability impacts and availability (service disruption) for affected systems. Impacting 1 product from scipy organizations running these solutions should prioritize assessment and patching.
Reported in 2023, this vulnerability emerged during an era marked by increased sophistication in supply chain attacks, cloud infrastructure vulnerabilities, and software-as-a-service (SaaS) security challenges. Security practices during this period emphasized zero-trust architectures, container security, and API protection.
2023-07-05T17:15:09.320
2026-06-17T05:41:10.900
Modified
CVSSv3.1: 5.5 (MEDIUM)
SecUtils normalizes and enriches National Vulnerability Database (NVD) records by standardizing vendor and product identifiers, aggregating vulnerability metadata from both NVD and MITRE sources, and providing structured context for security teams. For scipy's affected products, we extract Common Platform Enumeration (CPE) data, Common Weakness Enumeration (CWE) classifications, CVSS severity metrics, and reference data to enable rapid vulnerability prioritization and asset correlation. This record contains no exploit code, proof-of-concept instructions, or attack methodologies—only defensive intelligence necessary for patch management, risk assessment, and security operations.