From Newsgroup: comp.ai.philosophy

Code uploaded to AI developer platform Hugging Face covertly installed backdoors and other types of malware on end-user machines, researchers
from security firm JFrog said Thursday in a report that’s a likely
harbinger of what’s to come.

In all, JFrog researchers said, they found roughly 100 submissions that performed hidden and unwanted actions when they were downloaded and loaded onto an end-user device. Most of the flagged machine learning models—all
of which went undetected by Hugging Face—appeared to be benign proofs of concept uploaded by researchers or curious users. JFrog researchers said
in an email that 10 of them were “truly malicious” in that they performed actions that actually compromised the users’ security when loaded.

Full control of user devices
One model drew particular concern because it opened a reverse shell that
gave a remote device on the Internet full control of the end user’s
device. When JFrog researchers loaded the model into a lab machine, the submission indeed loaded a reverse shell but took no further action.

That, the IP address of the remote device, and the existence of identical shells connecting elsewhere raised the possibility that the submission was also the work of researchers. An exploit that opens a device to such tampering, however, is a major breach of researcher ethics and
demonstrates that, just like code submitted to GitHub and other developer platforms, models available on AI sites can pose serious risks if not carefully vetted first.

“The model’s payload grants the attacker a shell on the compromised
machine, enabling them to gain full control over victims’ machines through what is commonly referred to as a ‘backdoor,’” JFrog Senior Researcher
David Cohen wrote. “This silent infiltration could potentially grant
access to critical internal systems and pave the way for large-scale data breaches or even corporate espionage, impacting not just individual users
but potentially entire organizations across the globe, all while leaving victims utterly unaware of their compromised state.”

https://arstechnica.com/security/2024/03/hugging-face-the-github-of-ai- hosted-code-that-backdoored-user-devices/

--- Synchronet 3.20a-Linux NewsLink 1.114