Sans Internet Storm Center Daily Network/cyber Security And Information Security Podcast

Leveraging CNNs and Entropy-Based Feature Selection to Identify Potential Malware Artifacts of Interest This diary explores a novel methodology for classifying malware by integrating entropy-driven feature selection with a specialized Convolutional Neural Network (CNN). Motivated by the increasing obfuscation tactics used by modern malware authors, we will focus on capturing high-entropy segments within files, regions most likely to harbor malicious functionality, and feeding these distinct byte patterns into our model. https://isc.sans.edu/diary/%5BGuest%20Diary%5D%20Leveraging%20CNNs%20and%20Entropy-Based%20Feature%20Selection%20to%20Identify%20Potential%20Malware%20Artifacts%20of%20Interest/31790 Malware found on npm infecting local package with reverse shell Researchers at Reversinglabs found two malicious NPM packages, ethers-provider2, and ethers-providerz that patch the well known (and not malicious) ethers package to add a reverse shell and downloader. https://www.reversinglabs.com/blog/