Vulnerabilities of Machine Learning Infrastructure

As presented at The Standoff online cyber-range and security conference by Sergey Gordeychik.

In this talk we will present results of hands-on vulnerability research of different components of AI infrastructure including NVIDIA DGX GPU servers, ML frameworks such as Pytorch, Keras and Tensorflow, data processing pipelines and specific applications, including Medical Imaging and face recognition powered CCTV. Updated Internet Census toolkit based on the Grinder framework will be introduced.

NVIDIA DGX machine learning servers vulnerabilities

NVIDIA has published fixes for vulnerabilities in NVIDIA Machine learning servers with CVSS up to 9.8.

NVIDIA DGX-1, DGX-2, and DGX A100 Servers are affected and can be hacked via BMC OOB interfaces. 

codeblue.jp talk

Vulnerabilities of Machine Learning Infrastructure talk to be presented at Code Blue 2020 security conference @Tokyo. 

Wind Turbines strikes again

 

Nice to see Nordex devices featured in SCADA StrangeLove "Too Smart Grid in da Cloud" talk back to 2014 available via SatCOM in 2020.

Vulnerabilities in AI Healthcare pipelines

Must see if you use/develop Artificial Intelligence in Healthcare and care about Cybersecurity and Privacy.

How to make your own Internet Census

Simple writeup on the Internet-scale census with example or Artificial Intelligence and Machine Learning infrastructure assessment by Antony Nikolaev. Sample Lab of Cybersecurity of Machine Learning and Artificial Intelligence at Harbour.Space University.

Just in case if you need spare Tensorboard in Africa or Kubeflow elsewhere.

Hacking Odyssey at HITBLockdown002

How to Hack Medical Imaging Applications via DICOM by Maria Nedyak

DATE: July 25, 2020
TIME: 04:00 PM - 05:00 PM (GMT +8)