CVE-2024-47064 in cvat
Summary
by MITRE • 09/30/2024
Computer Vision Annotation Tool (CVAT) is an interactive video and image annotation tool for computer vision. If an attacker can trick a logged-in CVAT user into visiting a maliciously-constructed URL, they can initiate any API calls on that user's behalf. This gives the attacker temporary access to all data that the victim user has access to. Upgrade to CVAT 2.19.0 or a later version to fix this issue.
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Analysis
by VulDB Data Team • 10/31/2024
The Computer Vision Annotation Tool (CVAT) vulnerability CVE-2024-47064 represents a critical cross-site request forgery (CSRF) flaw that undermines the security posture of this widely-used computer vision annotation platform. This vulnerability specifically affects the authentication and authorization mechanisms within CVAT, creating a pathway for attackers to exploit legitimate user sessions and execute unauthorized API operations. The flaw manifests when an authenticated user visits a maliciously crafted URL, allowing the attacker to leverage the user's existing session to perform actions within the application. This type of vulnerability falls under CWE-352, which categorizes cross-site request forgery as a fundamental web application security weakness that enables attackers to perform actions on behalf of authenticated users without their knowledge or consent.
The technical exploitation of this vulnerability relies on the improper handling of API requests within CVAT's session management framework. When a user is logged into the system, their session tokens remain active and are typically validated through standard authentication mechanisms. However, the CSRF flaw allows an attacker to construct a malicious URL that, when visited by the victim user, automatically triggers API calls that the attacker controls. This means that any data or operations accessible to the victim user's account can be manipulated, accessed, or destroyed by the attacker. The vulnerability is particularly dangerous because it leverages the trust relationship between the user and the application, making it difficult for users to detect unauthorized activities. The attack vector typically involves social engineering techniques where users are tricked into clicking malicious links, often through phishing campaigns or compromised websites that redirect users to the attacker-controlled URLs.
The operational impact of CVE-2024-47064 extends beyond simple data theft, encompassing potential data corruption, unauthorized access to sensitive computer vision datasets, and the possibility of disrupting ongoing annotation projects. Since CVAT is commonly used in security-sensitive applications such as autonomous vehicle development, medical imaging analysis, and surveillance systems, the compromise of annotation data could have far-reaching consequences. Attackers could potentially modify annotation labels, delete critical datasets, or gain access to proprietary computer vision models that were previously protected by user-based access controls. The vulnerability affects all users with valid sessions, meaning that even administrative accounts could be compromised, potentially leading to complete system takeover. This aligns with ATT&CK technique T1531, which covers "Run-time Application Masking" and related tactics involving the exploitation of legitimate user privileges for unauthorized access.
Organizations utilizing CVAT must implement immediate mitigation strategies while planning for the mandatory upgrade to version 2.19.0 or later to address this vulnerability. The most effective immediate measure involves implementing Content Security Policy (CSP) headers that restrict the sources from which scripts can be loaded and prevent unauthorized cross-origin requests. Additionally, organizations should consider implementing additional authentication layers such as multi-factor authentication to reduce the impact of session hijacking. Network-level protections including web application firewalls and monitoring for suspicious API access patterns can help detect exploitation attempts. The upgrade to CVAT 2.19.0 addresses the core CSRF implementation issue by properly validating request origins and implementing anti-CSRF tokens for all API operations. Security teams should also conduct comprehensive user awareness training to prevent social engineering attacks that leverage this vulnerability, as the human factor remains the primary attack surface for such exploitation techniques. The fix demonstrates the importance of maintaining current security practices and the necessity of regular security updates in protecting against known vulnerabilities that could otherwise remain undetected for extended periods.