CVE-2020-28609 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 vulnerability arises due to improper validation of array indices (CWE-129) in the PM_io_parser component, particularly in the read_face() and store_iv() functions located in Nef_2/PM_io_parser.h. An attacker can craft a malformed input file that triggers out-of-bounds (OOB) reads and type confusion errors. These memory safety issues can potentially lead to arbitrary code execution if exploited successfully. The vulnerability is triggered by processing maliciously crafted polygon data, which causes the parser to access memory outside the bounds of allocated arrays, leading to undefined behavior. Although no known exploits are currently reported in the wild, the nature of the vulnerability—out-of-bounds reads combined with type confusion—makes it a candidate for exploitation in scenarios where untrusted polygon data is parsed. The vulnerability does not require authentication but does require the attacker to supply a malicious input file to the vulnerable parsing functionality. The scope is limited to applications and systems that utilize CGAL libcgal 5.1.1 for polygon parsing, particularly those that process untrusted or external polygon data files. Since CGAL is a computational geometry library widely used in scientific computing, CAD software, and other geometry-intensive applications, the impact is primarily on software that integrates this library without proper input validation or sandboxing.

For European organizations, the impact of this vulnerability depends on the extent to which CGAL libcgal 5.1.1 is integrated into their software stacks. Organizations involved in engineering, CAD design, scientific research, and manufacturing that rely on CGAL for geometric computations could be at risk if they process untrusted polygon data. Exploitation could lead to unauthorized code execution, potentially allowing attackers to compromise affected systems, exfiltrate sensitive data, or disrupt operations. Given the medium severity and the requirement for malicious input files, the risk is higher in environments where polygon data is received from external or untrusted sources, such as collaborative engineering platforms or cloud-based CAD services. The vulnerability could also be leveraged as a foothold for lateral movement within networks if exploited. However, since no known exploits are reported, the immediate threat level is moderate. The availability of patches or updates is not indicated, which may delay mitigation efforts and prolong exposure.

1. Immediate mitigation should involve auditing all software components and applications that utilize CGAL libcgal 5.1.1, especially those handling polygon data from external or untrusted sources. 2. Implement strict input validation and sanitization to reject malformed polygon files before parsing. 3. Employ sandboxing or containerization techniques to isolate the parsing process, limiting the potential impact of exploitation. 4. Monitor and restrict file upload or data ingestion channels to trusted sources only. 5. Where possible, upgrade to a later, patched version of CGAL libcgal once available or apply vendor-provided patches. 6. Conduct code reviews and static analysis on custom integrations of CGAL to identify and remediate unsafe parsing logic. 7. Enhance logging and anomaly detection around polygon data processing to detect potential exploitation attempts. 8. Educate developers and engineers about secure handling of geometric data and the risks of improper input validation.