Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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ReconAuthenticate to CVAT with low-privilege account
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DeliveryCraft multipart upload with HTML payload and Content-Type: text/html
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ExploitUpload to /api/assets for a shared annotation guide
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InstallVictim navigates to annotation guide containing malicious asset
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C2Browser fetches asset with attacker-set Content-Type header
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ExecuteBrowser executes embedded JavaScript
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ImpactExfiltrate session token or perform actions as victim
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A05:2025 - Injection
ASVS 5.0
V1 - Encoding and Sanitization Output encoding, context-aware escaping
MITRE ATT&CK
2 techniques across 2 tactics: Initial Access, Execution The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Exploitation Conditions | Exploitation requires an authenticated CVAT account with permission to upload annotation guide assets - specifically, write access to the /api/assets endpoint for at least one project or job guide (PR:L). The attacker must be able to set an arbitrary Content-Type in a multipart upload request, which is standard HTTP client behavior. A separate victim with guide-viewing permissions must access the annotation guide containing the malicious asset (UI:P), triggering their browser to fetch and render the file. Limiting factors: (1) pre-authentication exploitation is not possible; (2) the victim must actively navigate to and load the affected guide page; (3) in deployments where all users hold equivalent trust (e.g., single-organization internal tools), the threat model is reduced but not eliminated - a compromised low-privilege account can still target admins. No non-default configuration setting is required; any CVAT instance in the affected version range with annotation guide asset upload enabled is vulnerable. |
| Impact | The CVSS 4.0 score of 8.5 (AV:N/AC:L/AT:N/PR:L/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N) reflects a realistic attack profile: network-accessible, low attacker privilege (authenticated upload capability), and passive victim interaction required. High confidentiality and integrity impact in the vulnerable system context corresponds to full JavaScript execution in the victim's browser, enabling session token theft or account takeover. The PR:L requirement is a meaningful limiting factor - exploitation is not pre-authentication, so mass opportunistic exploitation is unlikely. No EPSS data was provided, and the CVE is absent from CISA KEV, meaning active exploitation is not confirmed. Real-world risk is moderate-to-high in multi-tenant or collaborative annotation platforms where annotators, reviewers, and admins share project guides, but substantially lower in single-user or air-gapped deployments. The absence of an availability impact (VA:N) and no subsequent-system scope (SC/SI/SA:N) suggests the attacker's blast radius is bounded to the victim's session rather than server-side compromise. |
| Exploit ScenarioDerived | An authenticated annotator uploads a file named 'guide-cover.gif' to a shared annotation guide project but sets the multipart Content-Type field to 'text/html' with an embedded JavaScript payload (e.g., a cookie-stealing script). When a project admin or peer annotator opens the annotation guide and the browser fetches the asset, CVAT serves it with Content-Type: text/html, causing the browser to execute the script and silently exfiltrate the victim's session token to an attacker-controlled server. No public proof-of-concept code has been identified, but the attack technique is well-understood and trivially constructable from the patch diff alone. |
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Alert meAnalysisAIv1 – Aug 04, 2026
Stored XSS in CVAT annotation guide asset handling (versions 2.5.0-2.66.0) allows an authenticated attacker to upload a file with an attacker-controlled Content-Type header; CVAT then serves the asset with that header intact, causing a victim's browser to render the file as an HTML page and execute any embedded JavaScript. The attack targets collaborative annotation workflows where guides are shared across users or teams, enabling session hijacking, credential theft, or unauthorized actions within the victim's browser context. No public exploit has been identified at time of analysis, and this CVE is not listed in CISA KEV. The vendor-released fix is version 2.67.0.
RemediationAI
Upgrade to CVAT version 2.67.0, which contains the fix confirmed by commit 44d717ad3a9d914f1cb2593ce09efd87d0b9159e. The patch introduces Content-Type validation at upload time in serializers.py using Python's mimetypes.guess_type(), rejecting any file where the declared Content-Type does not match the file extension; it also appends Content-Security-Policy: default-src 'none'; sandbox to all asset-serving responses as a defense-in-depth layer. Vendor advisory: https://github.com/cvat-ai/cvat/security/advisories/GHSA-w6mx-95ff-72cv. If an immediate upgrade is not feasible, restrict access to the /api/assets endpoint to only trusted internal users via network policy or reverse-proxy ACL rules - note this disables the annotation guide asset feature for external collaborators. Alternatively, configure a WAF rule to reject multipart uploads to /api/assets where the Content-Type field contains 'text/html', 'application/javascript', or other scriptable MIME types; this has low side-effect risk but may not catch all edge cases. Do not rely solely on the CSP header as a mitigation - it is a backup measure, not the primary control.
Affected VersionsENISA
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in euvd
Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
CVAT (Computer Vision Annotation Tool) is an open-source Django-based web application for image and video labeling used in machine learning pipelines, identified by CPE cpe:2.3:a:cvat-ai:cvat:*:*:*:*:*:*:*:*. The vulnerability resides in the annotation guide asset upload and serving pipeline: CVAT accepted attacker-supplied Content-Type values during multipart file upload without validating them against the actual file extension, then reflected those values verbatim in HTTP response headers when serving the asset later. This is a classic CWE-79 (Improper Neutralization of Input During Web Page Generation) instance - the application trusted user-supplied metadata instead of deriving the safe content type from file content or extension. The commit diff confirms the fix adds mimetypes.guess_type() validation in serializers.py, rejecting uploads where the declared Content-Type mismatches the extension (e.g., an HTML payload named 'logo.gif' with Content-Type 'text/html'). As a defense-in-depth measure, views.py was also patched to append Content-Security-Policy: default-src 'none'; sandbox to all asset responses, neutralizing script execution even if a malicious file is somehow served.
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Severity by source
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N
Network-accessible stored XSS, low-privilege upload required, victim interaction needed, scope changes to victim browser with full confidentiality and integrity impact.
Primary rating from Vendor (GitHub_M).
CVSS VectorVendor: GitHub_M
Lifecycle Timeline
2DescriptionCVE.org
CVAT is an open source interactive video and image annotation tool for computer vision. Versions 2.5.0 through 2.66.0 contain a XSS vulnerability that can be accessed through annotation guide assets. When CVAT serves the files attached to an annotation guide, it labels them with a media type ( Content-Type ) that the attacker can influence, so instead of treating an uploaded file as plain data, the victim's browser can be told to treat it as an HTML page and run any JavaScript inside it. This issue has been fixed in version 2.67.0.
Executive ViewAI
CVAT annotation platform versions 2.5.0 through 2.66.0 contain a stored cross-site scripting vulnerability in asset handling that compromises the security of collaborative annotation workflows. An attacker with platform access can inject malicious code through guide assets, affecting all users who view those resources and exposing their credentials and account access to theft or unauthorized actions. Organizations using CVAT for team-based annotation must urgently remediate to eliminate session hijacking and credential compromise risks.
Apply vendor patch.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Cross-Site Scripting occurs when an application accepts untrusted data and sends it to a web browser without proper validation or encoding.
CVAT is an opensource interactive video and image annotation tool for computer vision. Rated critical severity (CVSS 9.8
CVAT is an open source interactive video and image annotation tool for computer vision. [CVSS 8.8 HIGH]
Stored cross-site scripting in CVAT versions 2.68.0 through 2.69.x allows an authenticated user with annotation guide ed
Stored cross-site scripting in CVAT (Computer Vision Annotation Tool) versions 2.5.0 through 2.63.0 allows an authentica
Computer Vision Annotation Tool (CVAT) is an interactive video and image annotation tool for computer vision. Rated high
Path traversal in CVAT versions 1.6.0 through 2.64.0 enables an authenticated, low-privileged attacker with write access
Computer Vision Annotation Tool (CVAT) is an interactive video and image annotation tool for computer vision. Rated high
CVAT is an open source interactive video and image annotation tool for computer vision. Versions 2.2.0 through 2.39.0 ha
Computer Vision Annotation Tool (CVAT) is an interactive video and image annotation tool for computer vision. Rated medi
Computer Vision Annotation Tool (CVAT) is an interactive video and image annotation tool for computer vision. Rated medi
Computer Vision Annotation Tool (CVAT) is an interactive video and image annotation tool for computer vision. Rated medi
CVAT is an open source interactive video and image annotation tool for computer vision. [CVSS 5.4 MEDIUM]
EUVD-2026-52895
NVD
CVE.org
EPSS
Vulnrichment
GitHub
VulDB
Exploit-DB