CVE-2020-28614 in CGAL
Summary
by MITRE • 04/18/2022
Multiple code execution vulnerabilities exists in the Nef polygon-parsing functionality of CGAL libcgal CGAL-5.1.1. A specially crafted malformed file can lead to an out-of-bounds read and type confusion, which could lead to code execution. An attacker can provide malicious input to trigger any of these vulnerabilities. An oob read vulnerability exists in Nef_S2/SNC_io_parser.h SNC_io_parser<EW>::read_vertex() vh->shalfedges_begin().
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Analysis
by VulDB Data Team • 04/18/2022
The vulnerability described represents a critical security flaw within the Computational Geometry Algorithms Library (CGAL) version 5.1.1, specifically within its Nef polygon-parsing functionality. This issue affects the libcgal component and demonstrates a severe weakness in input validation and memory management that could be exploited to achieve remote code execution. The vulnerability stems from improper handling of malformed input files during the parsing of Nef polygons, which are used for representing and manipulating planar arrangements of curves in computational geometry applications.
The technical implementation of this vulnerability manifests through multiple attack vectors including out-of-bounds read conditions and type confusion errors. The specific flaw occurs within the Nef_S2/SNC_io_parser.h file in the SNC_io_parser<EW>::read_vertex() function where the code accesses memory beyond the allocated bounds through vh->shalfedges_begin() method. This out-of-bounds read vulnerability is particularly dangerous because it can be leveraged to disclose sensitive memory contents and potentially manipulate program execution flow. The type confusion aspect further compounds the risk by allowing attackers to corrupt memory structures and execute arbitrary code with the privileges of the affected application.
The operational impact of this vulnerability extends beyond simple denial of service scenarios, as it provides attackers with a pathway to achieve full system compromise. Any application that utilizes CGAL's Nef polygon parsing functionality for processing untrusted input files becomes a potential target for exploitation. This includes CAD software, geographic information systems, computer graphics applications, and any other systems that rely on computational geometry operations. The vulnerability's exploitation requires minimal privileges to trigger, as attackers only need to provide a maliciously crafted input file that appears legitimate to the parser but contains crafted data structures designed to exploit the memory access violations.
From a cybersecurity perspective, this vulnerability aligns with CWE-125 (Out-of-bounds Read) and CWE-476 (NULL Pointer Dereference) classifications, representing a classic example of memory safety issues that have become increasingly prevalent in modern software systems. The attack surface is particularly concerning given CGAL's widespread adoption in professional and industrial applications where the consequences of arbitrary code execution can be catastrophic. The ATT&CK framework categorizes this as a code execution vulnerability that could be leveraged through initial access vectors such as malicious file uploads or network-based attacks targeting applications that process geometric data. Mitigation strategies should include immediate patching of affected CGAL versions, implementation of strict input validation for all geometric data processing, and deployment of memory safety enhancements such as address space layout randomization and stack canaries to reduce exploit reliability.
Organizations utilizing CGAL in their software stacks must prioritize immediate remediation efforts, as the vulnerability affects a core mathematical library used across multiple domains including automotive design, aerospace engineering, and digital manufacturing. The complexity of the geometric algorithms involved makes this type of vulnerability particularly challenging to detect and prevent without comprehensive memory safety measures and thorough input sanitization protocols. Security teams should also implement monitoring for suspicious file processing activities and consider sandboxing operations that involve external geometric data to limit potential damage from successful exploitation attempts.