Researchers Prove Malware Can Be Hidden Inside AI Models

July 26, 2021

Researchers have discovered a new method of slipping malware past automated detention tools by hiding it in a neutral network.

To prove the validity of the technique, the researchers embellished 36.9 MiB of malware in a 178 MiB AlexaNet model without significantly altering the function of the model itself.

The malware-embedded model classified images with almost identical accuracy within 1% of the malware-free model.

By selecting the best layer to work with in an already trained model, and then embedding the malware in that layer, the researchers were able to break the malware in a way that allowed them to bypass detection by standard antivirus engines.

The new technique is a way to hide malware, not execute it. To actually execute the malware, it must be extracted from the poisoned model by another malicious program and then reassembled into its working form.

Researchers Zhi Wang, Chaoge Liu, and Xiang Cui made the discovery.

For more information, read the original story in Arstechnica.

Top Stories

Related Articles

December 30, 2025 A fast-moving cyberattack has compromised more than 59,000 internet-facing Next.js servers in less than two days after more...

December 29, 2025 The U.S. National Institute of Standards and Technology (NIST) has warned that several of its Internet Time more...

December 29, 2025 A critical security flaw has been found in LangChain, one of the most widely used frameworks for more...

December 23, 2025 South Korea will require facial recognition scans to open new mobile phone accounts. The new rule is more...

Jim Love

Jim is an author and podcast host with over 40 years in technology.

Share:
Facebook
Twitter
LinkedIn