CVE-2024-47063 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 a malicious CVAT user with permissions to either create a task, or edit an existing task can trick another logged-in 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 presents a critical security vulnerability that exploits user trust and session management weaknesses to enable unauthorized API access. This vulnerability specifically affects the tool's handling of user interactions and URL processing mechanisms, creating a path for privilege escalation through social engineering techniques. The flaw exists in how CVAT manages authenticated sessions when processing external URLs, allowing malicious actors to craft deceptive links that trigger unintended API operations on behalf of authenticated users.
This vulnerability represents a classic cross-site request forgery (CSRF) attack vector combined with session hijacking principles, where the malicious user leverages the victim's existing authenticated session to execute unauthorized commands. The technical flaw stems from insufficient validation of request origins and lack of proper session integrity checks when processing task-related URLs. The vulnerability affects users with either create task or edit task permissions, expanding the potential attack surface significantly within collaborative annotation environments.
The operational impact of this vulnerability extends beyond simple data theft, as it enables attackers to perform arbitrary API operations with the privileges of the compromised user. This includes accessing, modifying, or deleting annotation data, task configurations, and potentially sensitive training datasets that organizations rely on for computer vision model development. The temporary nature of the access means that attackers can operate within the system's permissions for as long as the victim remains logged in, creating a window for extensive data manipulation or exfiltration.
Organizations utilizing CVAT for computer vision projects face significant risks including intellectual property theft, data corruption, and potential compliance violations when this vulnerability exists. The attack requires minimal technical expertise to execute, making it particularly dangerous in collaborative environments where users frequently share links or collaborate on annotation tasks. The vulnerability affects the core functionality of CVAT's user management and access control systems, undermining the integrity of the entire annotation platform.
The recommended mitigation involves upgrading to CVAT version 2.19.0 or later, which implements proper CSRF protection mechanisms and enhanced session validation. Security patches typically address such issues by implementing anti-CSRF tokens, origin validation checks, and stricter URL parameter handling. Organizations should also consider implementing additional security measures including user education about suspicious link handling, network-level monitoring for unusual API access patterns, and regular security audits of collaborative tools. The fix aligns with established security practices for preventing session hijacking and CSRF attacks, as outlined in CWE-352 and ATT&CK techniques related to privilege escalation and credential access.
This vulnerability highlights the importance of proper session management in web applications, particularly those handling sensitive data in collaborative environments. The attack vector demonstrates how seemingly innocuous user interactions can be weaponized when proper security controls are absent. The fix addresses fundamental security principles that should be implemented across all web applications handling user sessions and API operations, emphasizing the need for comprehensive security testing and regular vulnerability assessments in development workflows.