Cyber Posture

CVE-2024-55241

HighRCE

Published: 06 February 2025

Published
06 February 2025
Modified
15 April 2026
KEV Added
Patch
CVSS Score 8.8 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
EPSS Score 0.0063 70.5th percentile
Risk Priority 18 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2024-55241 is a high-severity Code Injection (CWE-94) vulnerability in Notion (inferred from references). Its CVSS base score is 8.8 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 29.5% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.

This vulnerability is AI-related — categorised as Enterprise AI Assistants; in the LLM/Generative AI Risks risk domain.

The strongest mitigations our analysis identified are NIST 800-53 SI-10 (Information Input Validation) and SI-2 (Flaw Remediation).

Threat & Defense at a Glance

What attackers do: exploitation maps to Exploit Public-Facing Application (T1190). What defenders deploy: see the NIST 800-53 controls recommended below.
Threat & Defense Details

Mitigating Controls (NIST 800-53 r5)AI

prevent

Timely flaw remediation by updating to commit 99c2c03 or later directly eliminates the code injection vulnerability in modelsbyom.py.

prevent

Information input validation on the load_model function prevents injection of arbitrary code by remote low-privileged attackers.

detect

Vulnerability monitoring and scanning identifies the code injection flaw (CVE-2024-55241) in the LLM-As-Chatbot application for remediation.

MITRE ATT&CK Enterprise TechniquesAI

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.
Why these techniques?

The vulnerability allows remote arbitrary code execution in a chatbot application (likely public-facing), directly mapping to exploitation of public-facing applications.

NVD Description

An issue in deep-diver LLM-As-Chatbot before commit 99c2c03 allows a remote attacker to execute arbitrary code via the modelsbyom.py component.

Deeper analysisAI

CVE-2024-55241 is a code injection vulnerability (CWE-94) affecting the deep-diver LLM-As-Chatbot application prior to commit 99c2c03. The flaw resides in the modelsbyom.py component, enabling remote arbitrary code execution. It carries a CVSS v3.1 base score of 8.8 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H), indicating high severity due to its network accessibility, low complexity, and significant impacts on confidentiality, integrity, and availability.

A remote attacker with low privileges, such as an authenticated user, can exploit this vulnerability over the network without requiring user interaction. Successful exploitation allows the attacker to execute arbitrary code on the affected system, potentially leading to full compromise including data exfiltration, modification of chatbot behavior, or system takeover.

Advisories, including a detailed Notion page at https://diamond-bath-fd4.notion.site/Remote-Code-Execution-vulnerability-in-load_model-in-deep-diver-LLM-As-Chatbot-14d4a5b4bb28806795e8e5e8ef9ae27b, describe the remote code execution issue in the load_model function of deep-diver LLM-As-Chatbot. Practitioners should update to commit 99c2c03 or later to mitigate the vulnerability.

This vulnerability is particularly relevant to AI/ML deployments, as it targets an LLM-as-chatbot framework, highlighting risks in loading models within untrusted or insufficiently validated environments. No public evidence of real-world exploitation has been reported as of the CVE publication on 2025-02-06.

Details

CWE(s)

Affected Products

Notion
inferred from references and description; NVD did not file a CPE for this CVE

AI Security AnalysisAI

AI Category
Enterprise AI Assistants
Risk Domain
LLM/Generative AI Risks
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
The vulnerability is in 'deep-diver LLM-As-Chatbot', an LLM-based chatbot application, which fits the Enterprise AI Assistants category as it implements an AI assistant using large language models.

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References