Exploitable Weaknesses in Widely Used ML Toolsets Allows Control of Servers, Escalation of Privileges

A group of cybersecurity analysts have revealed nearly twenty security vulnerabilities across fifteen distinct open-source initiatives connected with machine learning (ML).

A group of cybersecurity analysts have revealed nearly twenty security vulnerabilities across fifteen distinct open-source initiatives connected with machine learning (ML).
These entail weaknesses identified on both the back-end and front-end, as indicated by findings from software integrity specialists JFrog provided in a report issued recently.
The vulnerabilities on the back-end “enable unauthorized individuals to seize control of critical servers in the

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