CVE-2024-13047 - Ashlar-Vellum Cobalt CO File Parsing Type Confusion Remote Code Execution Vulnerability

CVE-2024-13047 - Ashlar-Vellum Cobalt CO File Parsing Type Confusion Remote Code Execution Vulnerability

https://cvefeed.io/rssfeed/latest.atom / Tue, 12/31/2024 - 00:23
CVE ID : CVE-2024-13047
Published : Dec. 30, 2024, 9:15 p.m. | 2 hours, 8 minutes ago
Description : Ashlar-Vellum Cobalt CO File Parsing Type Confusion Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Ashlar-Vellum Cobalt. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of CO files. The issue results from the lack of proper validation of user-supplied data, which can result in a type confusion condition. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-24843.
Severity: 7.8 | HIGH
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Kenya Education Network CERT(KENET-CERT) is a Cybersecurity Emergency Response Team and Co-ordination Center operated by the National Research and Education Network of Kenya. KENET-CERT coordination center promotes awareness on cybersecurity incidences as well as coordinates and assists member institutions in responding effectively to cyber security threats and incidences. KENET-CERT works closely with Kenya's National CIRT coordination center (CIRT/CC) as a sector CIRT for the academic institutions. KENET promotes use of ICT in Teaching, Learning and Research in Higher Education Institutions in Kenya. KENET aims to interconnect all the Universities, Tertiary and Research Institutions in Kenya by setting up a cost effective and sustainable private network with high speed access to the global Internet. KENET also facilitates electronic communication among students and faculties in member institutions, share learning and teaching resources by collaboration in Research and Development of Educational content.