CVE-2026-73221 (GCVE-0-2026-73221)
Vulnerability from cvelistv5 – Published: 2026-08-11 18:22 – Updated: 2026-08-11 20:04
VLAI
EPSS
VEX
Title
CVAT: Flawed authorization logic in endpoints related to lambda requests
Summary
CVAT is an open source interactive video and image annotation tool for computer vision. From 2.17.0 until 2.72.0, a user with the Worker role can use predictable task-based request IDs with the lambda request retrieve and destroy endpoints to view automatic annotation requests for tasks or jobs the user cannot access and cancel requests initiated by other users. This issue is fixed in version 2.72.0.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-11 20:04 UTC
CWE
- CWE-863 - Incorrect Authorization
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/cvat-ai/cvat/security/advisori… | x_refsource_CONFIRM |
| https://github.com/cvat-ai/cvat/pull/10964 | x_refsource_MISC |
| https://github.com/cvat-ai/cvat/commit/20a1076a0b… | x_refsource_MISC |
| https://github.com/cvat-ai/cvat/releases/tag/v2.72.0 | x_refsource_MISC |
Impacted products
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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