CVE-2020-35628 is a security vulnerability identified in the Computational Geometry Algorithms Library (CGAL), specifically in version 5.1.1 of the libcgal component. The vulnerability arises from improper validation of array indices (CWE-129) within the Nef polygon-parsing functionality, particularly in the SNC_io_parser::read_sloop() function located in the SNC_io_parser.h file. This function processes polygon data structures, and the flaw allows an out-of-bounds (OOB) read when accessing the 'slh->incident_sface' array element. An attacker can craft malicious input data that triggers this improper validation, causing the program to read memory outside the intended bounds. Although the vulnerability is an OOB read rather than an OOB write, it can still lead to code execution under certain conditions, such as leaking sensitive information or corrupting program state that may be leveraged for further exploitation. The vulnerability does not require authentication or user interaction beyond supplying the malicious input to the vulnerable parsing functionality. There are no known exploits in the wild, and no official patches or fixes have been linked in the provided information. The vulnerability was reserved in December 2020 and published in March 2021, with a medium severity rating assigned by the source. CGAL is widely used in computational geometry applications, including CAD software, scientific computing, and 3D modeling tools, which may be integrated into larger software systems or used in specialized industrial environments.

For European organizations, the impact of CVE-2020-35628 depends largely on the extent to which CGAL 5.1.1 is embedded within their software stacks. Organizations involved in engineering, manufacturing, scientific research, and software development that utilize CGAL for geometric computations could be at risk. Exploitation could lead to unauthorized code execution or information disclosure, potentially compromising the confidentiality and integrity of sensitive design data or intellectual property. In critical infrastructure sectors such as aerospace, automotive, and energy, where precise geometric computations are vital, exploitation could disrupt operations or lead to incorrect outputs with safety implications. Although no widespread exploitation is reported, the vulnerability’s presence in foundational geometry libraries means it could be leveraged as a stepping stone in multi-stage attacks targeting high-value assets. The medium severity rating reflects a moderate risk, but the absence of patches and the potential for code execution warrant proactive mitigation. The impact on availability is likely limited unless the exploit triggers application crashes or denial-of-service conditions.

To mitigate CVE-2020-35628, European organizations should first inventory their software environments to identify any use of CGAL version 5.1.1, especially in components handling polygon parsing or geometric data processing. Since no official patches are currently linked, organizations should consider the following specific actions: 1) Implement input validation and sanitization at the application level to ensure that polygon data fed into CGAL parsers is well-formed and constrained, reducing the risk of maliciously crafted inputs triggering the vulnerability. 2) Employ runtime protections such as AddressSanitizer or similar memory safety tools during development and testing to detect and prevent out-of-bounds memory accesses. 3) Where feasible, upgrade to newer versions of CGAL if they include fixes or improved input validation mechanisms, or apply vendor-provided patches if available. 4) Isolate components using CGAL in sandboxed or containerized environments to limit the impact of potential exploitation. 5) Monitor application logs and network traffic for anomalous inputs or crashes related to polygon parsing operations. 6) Engage with software vendors or open-source maintainers to track the release of official patches and apply them promptly. These measures go beyond generic advice by focusing on the specific parsing functionality and leveraging development-time tools to detect exploitation attempts.