Security Resilience

CVE-2024-23633

XSS in Humansignal Label Studio ≤ 1.10.1

Published
24 January 2024
Modified
17 June 2026
Patch / advisory
CVSS Score v3.1 4.7
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:N/A:N
EPSS Score 0.0059 47th percentile
Risk Priority 39 floored blend · peak EPSS

CVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.

Summary

CVE-2024-23633 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Humansignal Label Studio. Its CVSS base score is 4.7 (Medium).

Operationally, exploitation aligns with the MITRE ATT&CK technique Protocol or Service Impersonation (T1001.003); ranked at the 47th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

This vulnerability is AI-related — categorised as Other AI Platforms; in the Other ATLAS/OWASP Terms risk domain.

The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) 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

Vulnerability Data

Label Studio, an open source data labeling tool had a remote import feature allowed users to import data from a remote web source, that was downloaded and could be viewed on the website. Prior to version 1.10.1, this feature could…

more

had been abused to download a HTML file that executed malicious JavaScript code in the context of the Label Studio website. Executing arbitrary JavaScript could result in an attacker performing malicious actions on Label Studio users if they visit the crafted avatar image. For an example, an attacker can craft a JavaScript payload that adds a new Django Super Administrator user if a Django administrator visits the image. `data_import/uploader.py` lines 125C5 through 146 showed that if a URL passed the server side request forgery verification checks, the contents of the file would be downloaded using the filename in the URL. The downloaded file path could then be retrieved by sending a request to `/api/projects/{project_id}/file-uploads?ids=[{download_id}]` where `{project_id}` was the ID of the project and `{download_id}` was the ID of the downloaded file. Once the downloaded file path was retrieved by the previous API endpoint, `data_import/api.py`lines 595C1 through 616C62 demonstrated that the `Content-Type` of the response was determined by the file extension, since `mimetypes.guess_type` guesses the `Content-Type` based on the file extension. Since the `Content-Type` was determined by the file extension of the downloaded file, an attacker could import in a `.html` file that would execute JavaScript when visited. Version 1.10.1 contains a patch for this issue. Other remediation strategies are also available. For all user provided files that are downloaded by Label Studio, set the `Content-Security-Policy: sandbox;` response header when viewed on the site. The `sandbox` directive restricts a page's actions to prevent popups, execution of plugins and scripts and enforces a `same-origin` policy. Alternatively, restrict the allowed file extensions that may be downloaded.

CWE(s)

AI Security AnalysisAI

AI Category
Other AI Platforms
Risk Domain
Other ATLAS/OWASP Terms
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
Label Studio is an open-source data labeling platform used in AI/ML workflows for annotating datasets, fitting under 'Other Platforms' as it supports AI data preparation.

Related Threats

MITRE ATT&CK Enterprise Techniques

T1001.003 Protocol or Service Impersonation Command And Control
Adversaries may impersonate legitimate protocols or web service traffic to disguise command and control activity and thwart analysis efforts.
T1003.004 LSA Secrets Credential Access
Adversaries with SYSTEM access to a host may attempt to access Local Security Authority (LSA) secrets, which can contain a variety of different credential materials, such as credentials for service accounts.
T1003.005 Cached Domain Credentials Credential Access
Adversaries may attempt to access cached domain credentials used to allow authentication to occur in the event a domain controller is unavailable.
T1007 System Service Discovery Discovery
Adversaries may try to gather information about registered local system services.
T1011 Exfiltration Over Other Network Medium Exfiltration
Adversaries may attempt to exfiltrate data over a different network medium than the command and control channel.
T1012 Query Registry Discovery
Adversaries may interact with the Windows Registry to gather information about the system, configuration, and installed software.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2023-6568Shared CWE-79
CVE-2023-6778Shared CWE-79
CVE-2023-3685Shared CWE-79
CVE-2023-46492Shared CWE-79
CVE-2023-5001Shared CWE-79
CVE-2023-5705Shared CWE-79
CVE-2023-0280Shared CWE-79
CVE-2023-0309Shared CWE-79
CVE-2023-42478Shared CWE-79
CVE-2023-6075Shared CWE-79

Affected Assets

humansignal
label studio
≤ 1.10.1

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

—

Detect
Catch it (NIST detect / respond)

—

Harden
Shrink the surface (DISA STIG)

—

Validate
Prove the fix (OWASP ASVS)
  • V1.1.2
  • V1.3.2

Mitigating Controls (NIST 800-53 r5) AI

Developer testing and evaluation can discover missing or incorrect input neutralization through targeted web-application tests.

Input validation directly enforces neutralization of untrusted data before it reaches web output generation.

Output filtering can catch or sanitize unneutralized script content before it is served to users.

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.

PR.PS-06 mostly match
blocks

Secure SDLC practices directly target introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).

PR.PS-02 partial match
blocks

Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).

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.

removes
removes
removes
removes
blocks

A.5.6 only promotes membership in groups to improve knowledge, receive alerts, and share information; it performs no action that stops XSS exploitation (or even the underlying neutralization defect) and is a pure dependency for other controls per the owner's labeling rule.

References