CVE-2020-28620 is a medium-severity vulnerability affecting version 5.1.1 of the CGAL Project's libcgal library, specifically within the Nef polygon-parsing functionality. The root cause is an improper validation of array indices (CWE-129) in the code handling polygon data structures. The vulnerability manifests as multiple code execution issues triggered by specially crafted malformed input files. Specifically, the out-of-bounds (OOB) read occurs in the SNC_io_parser<EW>::read_edge() function, where the code accesses the center_vertex() of an edge handle without proper boundary checks. This OOB read can lead to type confusion, a condition where the program misinterprets data types, potentially allowing an attacker to execute arbitrary code. The attack vector involves supplying maliciously crafted polygon files to the vulnerable parser, which does not require authentication but does require the application to process attacker-controlled input files. There are no known exploits in the wild, and no patches have been linked in the provided data, indicating that remediation may require manual updates or vendor patches. The vulnerability affects the confidentiality, integrity, and availability of systems using libcgal 5.1.1, especially those that parse untrusted polygon data. Given the nature of the vulnerability, exploitation could lead to arbitrary code execution, potentially allowing attackers to take control of affected systems or cause denial of service.

For European organizations, the impact depends largely on the use of CGAL's libcgal library in their software stacks. CGAL is widely used in computational geometry, CAD, GIS, and scientific computing applications. Organizations in sectors such as manufacturing, engineering, geospatial analysis, and research institutions may be at risk if they utilize vulnerable versions of libcgal to process untrusted polygon data. Exploitation could lead to unauthorized code execution, data breaches, or disruption of critical services. This is particularly concerning for companies relying on automated processing of geometric data from external sources or third-party integrations. The vulnerability could also be leveraged in supply chain attacks if malicious polygon files are introduced into trusted workflows. While no active exploits are currently known, the potential for remote code execution without authentication elevates the risk profile. The impact on confidentiality, integrity, and availability could be significant if exploited, especially in environments where CGAL is integrated into larger systems handling sensitive or critical data.

1. Immediate mitigation involves upgrading libcgal to a version where this vulnerability is patched; if no official patch exists, consider applying custom patches or workarounds to validate array indices properly before processing polygon data. 2. Implement strict input validation and sanitization for all polygon files, especially those sourced externally or from untrusted origins. 3. Employ sandboxing or containerization techniques for applications using libcgal to limit the impact of potential code execution. 4. Monitor and restrict the processing of polygon files to trusted sources only, and implement file integrity checks to detect tampering. 5. Conduct code audits and static analysis on software components that use libcgal to identify and remediate similar unsafe array access patterns. 6. Maintain up-to-date intrusion detection systems and endpoint protection solutions capable of detecting anomalous behavior indicative of exploitation attempts. 7. Educate developers and system integrators about the risks of processing malformed polygon data and encourage secure coding practices around array indexing and memory management.