Cyber Resilience

CVE-2024-5548

HighPublic PoC

Published: 27 June 2024

Published
27 June 2024
Modified
15 July 2025
KEV Added
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Patch
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CVSS Score v3 7.5 CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
EPSS Score 0.0089 75.9th percentile
Risk Priority 16 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2024-5548 is a high-severity Path Traversal (CWE-22) vulnerability in Stitionai Devika. 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 24.1% 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 Enterprise AI Assistants; in the Privacy and Disclosure risk domain; MITRE ATLAS techniques in scope: Discover AI Model Family (AML.T0014), Evade AI Model (AML.T0015), Obtain Capabilities (AML.T0016).

EU & UK References

Vulnerability details

A directory traversal vulnerability exists in the stitionai/devika repository, specifically within the /api/download-project endpoint. Attackers can exploit this vulnerability by manipulating the 'project_name' parameter in a GET request to download arbitrary files from the system. This issue affects the latest…

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version of the repository. The vulnerability arises due to insufficient input validation in the 'download_project' function, allowing attackers to traverse the directory structure and access files outside the intended directory. This could lead to unauthorized access to sensitive files on the server.

CWE(s)
CWE-22

AI Security AnalysisAI

AI Category
Enterprise AI Assistants
Risk Domain
Privacy and Disclosure
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
The vulnerability is in stitionai/devika, an open-source AI agentic software engineer (AI coding assistant), listed on an AI/ML bug bounty platform (huntr). This fits Enterprise AI Assistants as it is an AI assistant for development tasks.

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?

Directory traversal vulnerability in public-facing /api/download-project endpoint enables exploitation of public-facing applications (T1190), facilitating file and directory discovery (T1083) and collection of data from the local system (T1005) via arbitrary file reads.

MITRE ATLAS TechniquesAI

MITRE ATLAS techniques

AML.T0014: Discover AI Model FamilyAML.T0015: Evade AI ModelAML.T0016: Obtain CapabilitiesAML.T0061: LLM Prompt Self-ReplicationAML.T0065: LLM Prompt CraftingAML.T0067: LLM Trusted Output Components ManipulationAML.T0069: Discover LLM System InformationAML.T0022AML.T0023AML.T0026AML.T0027AML.T0028

Affected Assets

stitionai
devika
1.0

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