Security Resilience

CVE-2024-24593

CSRF in Clearml ≤ 1.14.1

Public PoCCSRF
Published
06 February 2024
Modified
17 June 2026
CVSS Score v3.1 9.6
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H
EPSS Score 0.0038 30th percentile
Risk Priority 67 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-2024-24593 is a critical-severity CSRF (CWE-352) vulnerability in Clear Clearml. Its CVSS base score is 9.6 (Critical).

Operationally, exploitation aligns with the MITRE ATT&CK technique Security Account Manager (T1003.002); ranked at the 30th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.

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 AC-3 (Access Enforcement) and SC-23 (Session Authenticity) — see the control section below for these in your framework.

OWASP Top 10 for Web (2025)

A01:2025 Broken Access Control

EU & UK References

Vulnerability Data

A cross-site request forgery (CSRF) vulnerability in all versions up to 1.14.1 of the api server component of Allegro AI’s ClearML platform allows a remote attacker to impersonate a user by sending API requests via maliciously crafted html. Exploitation of…

more

the vulnerability allows an attacker to compromise confidential workspaces and files, leak sensitive information, and target instances of the ClearML platform within closed off networks.

CWE(s)
CWE-352

AI Security AnalysisAI

AI Category
Other AI Platforms
Risk Domain
Other ATLAS/OWASP Terms
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
ClearML is a Machine Learning Operations (MLOps) platform for managing ML projects, datasets, experiments, models, and workflows, fitting the 'Other Platforms' category as it is not a framework, library, or specialized AI tool like NLP or CV.

Related Threats

MITRE ATT&CK Enterprise Techniques

T1003.002 Security Account Manager Credential Access
Adversaries may attempt to extract credential material from the Security Account Manager (SAM) database either through in-memory techniques or through the Windows Registry where the SAM database is stored.
attack.mitre.org →
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.
attack.mitre.org →
T1003.007 Proc Filesystem Credential Access
Adversaries may gather credentials from the proc filesystem or `/proc`.
attack.mitre.org →
T1005 Data from Local System Collection
Adversaries may search local system sources, such as file systems, configuration files, local databases, virtual machine files, or process memory, to find files of interest and sensitive data prior to Exfiltration.
attack.mitre.org →
T1012 Query Registry Discovery
Adversaries may interact with the Windows Registry to gather information about the system, configuration, and installed software.
attack.mitre.org →
T1016.002 Wi-Fi Discovery Discovery
Adversaries may search for information about Wi-Fi networks, such as network names and passwords, on compromised systems.
attack.mitre.org →
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2023-24415Shared CWE-352
CVE-2023-44993Shared CWE-352
CVE-2024-2196Shared CWE-352
CVE-2023-28173Shared CWE-352
CVE-2023-51668Shared CWE-352
CVE-2023-32500Shared CWE-352
CVE-2023-30529Shared CWE-352
CVE-2025-49077Shared CWE-352
CVE-2023-45011Shared CWE-352
CVE-2023-1937Shared CWE-352

Affected Assets

clear
clearml
≤ 1.14.1

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)
  • V3.3.2
  • V3.5.1
  • V10.2.1

Mitigating Controls (NIST 800-53 r5) AI

AC-3 Access Enforcement partial match

Access enforcement requires verifying that state-changing requests originate from the authenticated user rather than a forged cross-site source.

SC-23 Session Authenticity partial match

Protecting session authenticity prevents attackers from replaying or forging authenticated requests via the victim's browser.

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 partial match
blocks

Secure SDLC practices directly require anti-CSRF controls such as tokens or SameSite attributes.

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.

A.5.14 Information transfer partial match
removes
A.5.15 Access control partial match
removes
A.5.16 Identity management partial match
removes
A.5.17 Authentication information partial match
removes
A.5.18 Access rights partial match
removes
A.8.10 Information deletion partial match
removes

References