Raw vector
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:L/I:H/A:NSummary
CVE-2024-37164 is a high-severity SSRF (CWE-918) vulnerability in Cvat Computer Vision Annotation Tool. Its CVSS base score is 7.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 28th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to AC-4 (Information Flow Enforcement) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-36474
Vulnerability Data
Computer Vision Annotation Tool (CVAT) is an interactive video and image annotation tool for computer vision. CVAT allows users to supply custom endpoint URLs for cloud storages based on Amazon S3 and Azure Blob Storage. Starting in version 2.1.0 and…
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prior to version 2.14.3, an attacker with a CVAT account can exploit this feature by specifying URLs whose host part is an intranet IP address or an internal domain name. By doing this, the attacker may be able to probe the network that the CVAT backend runs in for HTTP(S) servers. In addition, if there is a web server on this network that is sufficiently API-compatible with an Amazon S3 or Azure Blob Storage endpoint, and either allows anonymous access, or allows authentication with credentials that are known by the attacker, then the attacker may be able to create a cloud storage linked to this server. They may then be able to list files on the server; extract files from the server, if these files are of a type that CVAT supports reading from cloud storage (media data (such as images/videos/archives), importable annotations or datasets, task/project backups); and/or overwrite files on this server with exported annotations/datasets/backups. The exact capabilities of the attacker will depend on how the internal server is configured. Users should upgrade to CVAT 2.14.3 to receive a patch. In this release, the existing SSRF mitigation measures are applied to requests to cloud providers, with access to intranet IP addresses prohibited by default. Some workarounds are also available. One may use network security solutions such as virtual networks or firewalls to prohibit network access from the CVAT backend to unrelated servers on your internal network and/or require authentication for access to internal servers.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.3.6V1.5.3V5.3.2V10.4.7
Mitigating Controls (NIST 800-53 r5) AI
Information flow enforcement can restrict which destinations the server is allowed to contact on behalf of users.
Input validation directly stops untrusted URLs from being accepted and fetched without destination checks.
Boundary protection limits the network reach of server-initiated requests even if SSRF occurs.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure development practices directly include input validation and destination allow-listing that prevent SSRF.
Runtime monitoring of web applications and services can detect anomalous outbound requests indicative of SSRF.
Vulnerability identification processes can discover and record SSRF flaws in web applications.
Network segmentation and egress controls can limit the damage from successful SSRF requests.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Operational threat data describing SSRF campaigns can be used to tighten outbound-request allow-lists and detection rules before attackers exploit them.