Cyber Resilience

CVE-2024-4941

HighPublic PoC

Published: 06 June 2024

Published
06 June 2024
Modified
15 October 2025
KEV Added
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Patch
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CVSS Score v3.1 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
EPSS Score 0.0069 72.2th percentile
Risk Priority 15 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2024-4941 is a high-severity Path Traversal (CWE-22) vulnerability in Gradio Project Gradio. Its CVSS base score is 7.5 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Data from Local System (T1005); ranked in the top 27.8% of CVEs by exploit likelihood; 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 Platforms; in the Privacy and Disclosure risk domain; MITRE ATLAS techniques in scope: Obtain Capabilities (AML.T0016), Exfiltration via AI Inference API (AML.T0024), External Harms (AML.T0048).

EU & UK References

Vulnerability details

A local file inclusion vulnerability exists in the JSON component of gradio-app/gradio version 4.25. The vulnerability arises from improper input validation in the `postprocess()` function within `gradio/components/json_component.py`, where a user-controlled string is parsed as JSON. If the parsed JSON object…

more

contains a `path` key, the specified file is moved to a temporary directory, making it possible to retrieve it later via the `/file=..` endpoint. This issue is due to the `processing_utils.move_files_to_cache()` function traversing any object passed to it, looking for a dictionary with a `path` key, and then copying the specified file to a temporary directory. The vulnerability can be exploited by an attacker to read files on the remote system, posing a significant security risk.

CWE(s)
CWE-22NVD-CWE-noinfo

AI Security AnalysisAI

AI Category
Other Platforms
Risk Domain
Privacy and Disclosure
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
Gradio is a Python library and platform for creating web-based user interfaces for machine learning models, commonly used in AI/ML demos and deployments, fitting under 'Other Platforms' as it enables model serving and interaction via web apps.

Related Threats

MITRE ATT&CK Enterprise TechniquesAI

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 →
T1083 File and Directory Discovery Discovery
Adversaries may enumerate files and directories or may search in specific locations of a host or network share for certain information within a file system.
attack.mitre.org →
T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
attack.mitre.org →
Why these techniques?

LFI vulnerability in public-facing Gradio web app (T1190) enables arbitrary remote file reads for data from local system (T1005) and file/directory discovery (T1083).

MITRE ATLAS TechniquesAI

MITRE ATLAS techniques

AML.T0016: Obtain CapabilitiesAML.T0024: Exfiltration via AI Inference APIAML.T0048: External Harms

Affected Assets

gradio project
gradio
≤ 4.31.4

Mitigating Controls

Likely Mitigating Controls AI

Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.

SI-10 Information Input Validation
addresses: CWE-22

Validates pathnames and filenames to prevent traversal outside intended directories.

References