Severity by source
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
Primary rating from Vendor (VulDB) · only source for this CVE.
CVSS VectorVendor: VulDB
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
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6DescriptionCVE.org
A security flaw has been discovered in FedML-AI FedML up to 0.8.9. This impacts an unknown function of the file FileUtils.java of the component MQTT Message Handler. Performing a manipulation of the argument dataSet results in path traversal. The attack is possible to be carried out remotely. The exploit has been released to the public and may be used for attacks. The vendor was contacted early about this disclosure but did not respond in any way.
AnalysisAI
Path traversal in FedML-AI FedML up to version 0.8.9 allows authenticated remote attackers to read arbitrary files via manipulation of the dataSet argument in the MQTT Message Handler (FileUtils.java component). The vulnerability has a CVSS score of 4.3 and publicly available exploit code exists; however, it requires low-privilege authentication and provides only information disclosure without modification or availability impact. The vendor did not respond to early disclosure efforts.
Technical ContextAI
The vulnerability resides in the MQTT Message Handler component of FedML, specifically in the FileUtils.java file. It is a classic path traversal flaw (CWE-22) where user-supplied input via the dataSet parameter is not properly sanitized before being used in file path operations. The MQTT protocol is used for message handling in distributed machine learning scenarios, and the lack of input validation allows attackers to traverse directory structures using path manipulation techniques (such as ../ sequences) to access files outside the intended directory scope. FedML is an open-source federated learning framework written in Java, commonly deployed in machine learning infrastructure environments.
RemediationAI
Organizations should upgrade FedML to a version later than 0.8.9 if available; however, specific patched version numbers are not confirmed in the vendor advisory data. Immediately review and restrict authentication credentials for FedML systems, especially in environments with untrusted users. As a temporary workaround pending upgrades, implement network-level access controls to restrict MQTT traffic to only trusted sources and isolate FedML systems on separate network segments. Input validation should be enforced at the application level to reject path traversal sequences in the dataSet parameter. Reference the VulDB entries (https://vuldb.com/vuln/355288) for additional technical details and monitoring guidance.
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Same weakness CWE-22 – Path Traversal
View allSame technique Path Traversal
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External POC / Exploit Code
Leaving vuln.today
EUVD-2026-19017
GHSA-x5gq-6962-7gv9