The ACM ASIA Conference on Computer and Communications Security (ACM ASIACCS) is an avenue for cybersecurity research breakthroughs, techniques, and tools. At the ACM ASIACCS 2018 in Incheon, South Korea, we presented our research using DefPloreX-NG, a tool for identifying and tracking web defacement campaigns using historical and live data. “DefPloreX-NG” is a play on the phrase “defacement explorer.” The appended “NG” acronym means “Next Generation,” signifying improvements from the previous version of the tool. DefPloreX-NG is equipped with an enhanced machine learning algorithm and new visualization templates to give security analysts and other professionals a better understanding of web defacement campaigns.Read More
Using a machine learning system, we analyzed 3 million software downloads, involving hundreds of thousands of internet-connected machines, and provide insights in this three-part blog series. In the first part of this series, we took a closer look at unpopular software downloads and the risks they pose to organizations. We also briefly mentioned the problem regarding code signing abuse, which we will elaborate on in this post.
Code signing is the practice of cryptographically signing software with the intent of giving the operating system (like Windows) an efficient and precise way to discriminate between a legitimate application (like an installer for Microsoft Office) and malicious software. All modern operating systems and browsers automatically verify signatures by means of the concept of a certificate chain.
Valid certificates are issued or signed by trusted certification authorities (CAs), which are backed up by parent CAs. This mechanism relies entirely and strictly on the concept of trust. We assume that malware operators are, by definition, untrustworthy entities. Supposedly, these untrustworthy entities have no access to valid certificates. However, our analysis shows that is not the case.Read More