• Hugging Face, the GitHub of AI, hosted code that backdoored user devices

    From lol@lol@apple.com to comp.ai.neural-nets, comp.ai.philosophy, misc.phone.mobile.iphone, talk.politics.guns, talk.politics.misc on Tue Mar 5 22:27:49 2024
    From Newsgroup: comp.ai.neural-nets

    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 thatAs a likely
    harbinger of whatAs 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 modelsuall
    of which went undetected by Hugging Faceuappeared to be benign proofs of concept uploaded by researchers or curious users. JFrog researchers said
    in an email that 10 of them were otruly maliciouso in that they performed actions that actually compromised the usersA 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 userAs
    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.

    oThe modelAs payload grants the attacker a shell on the compromised
    machine, enabling them to gain full control over victimsA machines through what is commonly referred to as a abackdoor,Ao JFrog Senior Researcher
    David Cohen wrote. oThis 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.o

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

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