CVE-2020-28627 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_volume() ch->shell_entry_objects().
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Analysis
by VulDB Data Team • 04/18/2022
The vulnerability under discussion involves multiple code execution flaws within the CGAL library's polygon-parsing functionality, specifically affecting version 5.1.1 of libcgal. This represents a critical security concern as it allows remote attackers to execute arbitrary code through carefully crafted malicious input files. The affected component resides in the Nef_S2/SNC_io_parser.h file where the SNC_io_parser<EW>::read_volume() function processes shell entry objects, creating multiple attack vectors for exploitation.
The technical implementation of this vulnerability manifests through out-of-bounds read conditions and type confusion errors that occur during polygon parsing operations. When processing malformed input files, the parser fails to properly validate input boundaries, leading to memory access violations that can be leveraged by attackers to manipulate program execution flow. The specific code path involves the ch->shell_entry_objects() function call which operates on improperly validated data structures, allowing attackers to craft inputs that cause the parser to read beyond allocated memory regions.
From an operational impact perspective, this vulnerability creates significant risk for any application or system utilizing CGAL's Nef polygon functionality for geometric computations. Attackers can exploit these flaws without requiring elevated privileges, making them particularly dangerous in environments where untrusted input is processed through the affected library components. The potential for remote code execution means that compromised systems could be used as launching points for further attacks within network infrastructures.
The vulnerability aligns with CWE-125 (Out-of-bounds Read) and CWE-476 (NULL Pointer Dereference) classifications, while also exhibiting characteristics consistent with ATT&CK technique T1059.007 (Command and Scripting Interpreter: Python) and T1583.001 (Resource Development: Code Signing Certificates) through the potential for privilege escalation. The attack surface expands significantly when considering that CGAL is widely used in CAD software, geographic information systems, and computational geometry applications where polygon processing is fundamental.
Mitigation strategies should prioritize immediate patching of affected CGAL versions to address the memory validation issues in the SNC_io_parser implementation. Organizations should implement input sanitization measures at application boundaries to validate all polygon data before processing, along with restricting file access permissions for parsing operations. Additionally, deploying intrusion detection systems capable of identifying suspicious patterns in geometric data processing may help detect exploitation attempts. Regular security assessments of third-party libraries and maintaining updated software inventories are essential practices to prevent similar vulnerabilities from being exploited in production environments.