CVE-2020-28628 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::read_volume() seh->twin().
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Analysis
by VulDB Data Team • 04/21/2022
The CVE-2020-28628 vulnerability represents a critical security flaw within the Computational Geometry Algorithms Library (CGAL) version 5.1.1, specifically within its Nef polygon-parsing functionality. This vulnerability resides in the libcgal component and demonstrates a classic example of how geometric computation libraries can become attack vectors when handling malformed input data. The flaw manifests through multiple code execution pathways that stem from inadequate input validation and memory management within the polygon parsing subsystem, making it particularly dangerous for applications that process untrusted geometric data.
The technical implementation of this vulnerability involves a combination of out-of-bounds read conditions and type confusion errors that occur during the parsing of Nef_S2/SNC_io_parser.h files. Specifically, the SNC_io_parser::read_volume() function contains a critical flaw in how it handles the seh->twin() operation, where an attacker can craft a malformed input file that triggers an out-of-bounds memory access. This out-of-bounds read creates a type confusion scenario that can be exploited to execute arbitrary code, as the program's memory layout becomes corrupted and allows for control flow redirection. The vulnerability demonstrates characteristics consistent with CWE-125 (Out-of-bounds Read) and CWE-476 (NULL Pointer Dereference) while also exhibiting elements of memory corruption that align with ATT&CK technique T1059.007 (Command and Scripting Interpreter: PowerShell).
The operational impact of this vulnerability extends beyond simple code execution, as it represents a significant risk to any application or system that relies on CGAL for geometric computations and polygon processing. Attackers can exploit this vulnerability by providing maliciously crafted input files that trigger the vulnerable parsing functions, potentially leading to complete system compromise. The vulnerability is particularly concerning because it can be triggered through legitimate input processing pathways, making it difficult to detect and prevent through traditional network monitoring approaches. Systems that process CAD files, GIS data, or any geometric input from untrusted sources are at risk, as the attack can occur during normal file parsing operations without requiring special privileges or complex exploitation techniques.
Mitigation strategies for CVE-2020-28628 should focus on immediate patching of the CGAL library to version 5.1.2 or later, where the vulnerabilities have been addressed through improved input validation and memory management. Organizations should also implement strict input validation measures for any polygon or geometric data processing pipelines, including file format checking, size limitations, and content sanitization. Additionally, deployment of intrusion detection systems that monitor for unusual memory access patterns and potential exploitation attempts can provide early warning of attacks. The vulnerability highlights the importance of secure coding practices in mathematical and geometric libraries, emphasizing the need for comprehensive testing of edge cases and malformed inputs, which aligns with security standards such as those recommended in NIST SP 800-53 and ISO/IEC 27001. System administrators should also consider implementing network segmentation and access controls to limit the potential impact of successful exploitation attempts, particularly in environments where CGAL-based applications process sensitive or untrusted geometric data.