Security Resilience

CVE-2024-2196

CSRF in Aimstack Aim 3.17.5

Public PoCCSRF
Published
10 April 2024
Modified
29 July 2025
CVSS Score v3 8.8
Click a component to see what it means
Raw vectorCVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
EPSS Score 0.0059 47th percentile
Risk Priority 65 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-2024-2196 is a high-severity CSRF (CWE-352) vulnerability in Aimstack Aim. Its CVSS base score is 8.8 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Security Account Manager (T1003.002); ranked at the 47th 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)

EU & UK References

Vulnerability Data

aimhubio/aim is vulnerable to Cross-Site Request Forgery (CSRF), allowing attackers to perform actions such as deleting runs, updating data, and stealing data like log records and notes without the user's consent. The vulnerability stems from the lack of CSRF and…

more

CORS protection in the aim dashboard. An attacker can exploit this by tricking a user into executing a malicious script that sends unauthorized requests to the aim server, leading to potential data loss and unauthorized data manipulation.

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
aimhubio/aim is an open-source ML experiment tracking, logging, and visualization platform used for managing AI/ML training runs, metrics, and data, fitting 'Other Platforms' as it is neither a framework, library, nor specialized in NLP/CV/etc.

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.
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.
T1003.007 Proc Filesystem Credential Access
Adversaries may gather credentials from the proc filesystem or `/proc`.
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.
T1012 Query Registry Discovery
Adversaries may interact with the Windows Registry to gather information about the system, configuration, and installed software.
T1016.002 Wi-Fi Discovery Discovery
Adversaries may search for information about Wi-Fi networks, such as network names and passwords, on compromised systems.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2024-7760Same product: Aimstack Aim
CVE-2023-24415Shared CWE-352
CVE-2024-24593Shared CWE-352
CVE-2023-44993Shared 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

Affected Assets

aimstack
aim
3.17.5

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

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

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.

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References