CVE-2022-31188
Published: 01 August 2022
Summary
CVE-2022-31188 is a high-severity SSRF (CWE-918) vulnerability in Cvat Computer Vision Annotation Tool. Its CVSS base score is 8.6 (High).
Operationally, ranked in the top 2.8% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
Deeper analysis
CVAT, an open source interactive video and image annotation tool for computer vision, is affected by a server-side request forgery vulnerability in all versions prior to 2.0.0. The flaw, tracked as CWE-918, resides in the handling of URLs within an affected code path and carries a CVSS 3.1 score of 8.6 reflecting network attack vector, low complexity, and no required privileges or user interaction.
An unauthenticated remote attacker can supply crafted URLs to induce the server into making arbitrary requests, resulting in high impact to confidentiality along with limited integrity and availability consequences. Public exploit code for this issue has been posted to Packet Storm.
The project’s GitHub security advisory and associated commit 6fad1764efd922d99dbcda28c4ee72d071aa5a07 state that input validation was added to the relevant URL handling in version 2.0.0; administrators are advised to upgrade, as no workarounds are known.
The current EPSS score of 0.3573 is essentially unchanged from its recorded peak of 0.3594.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-52783
Vulnerability details
CVAT is an opensource interactive video and image annotation tool for computer vision. Versions prior to 2.0.0 were found to be subject to a Server-side request forgery (SSRF) vulnerability. Validation has been added to urls used in the affected code…
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path in version 2.0.0. Users are advised to upgrade. There are no known workarounds for this issue.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Penetration testing attempts server-side requests to internal resources, identifying SSRF weaknesses for remediation.
Outbound connections to external resources can be monitored and limited at the boundary, reducing SSRF impact.
Validates server-side URLs and resource references to block SSRF attempts.
Detects server-side request forgery through monitoring of unexpected outbound connections.