Security Insights for Linux, macOS and Containers | macOS
Be it for macOS or my dog eating out of the trash, there is no such thing as a bullet-proof security policy. It’s all about creating a threshold of standards- something to work off of while simultaneously reducing overall risk (you know, like storing your trash can on the counter, for example).
This previous blog post explored ways to use osquery for macOS malware analysis. Using the same methodology introduced there, we analyzed five additional macOS malware variants and recorded their behavior to understand the techniques they used. Below, you’ll find the techniques used by Calisto, Dummy, HiddenLotus, LamePyre and WireLurker. Read on to explore how to translate the techniques used by these malware into queries you can run to hunt for the active presence or historical artifacts using osquery.
Osquery, at its most basic level, is an operating system instrumentation framework that exposes the OS as a SQL database. SQL queries can be run to view information about the systems similar to any SQL database, providing a unified cross platform framework (i.e. endpoints running on multiple operating systems can be queried using the industry standard database language: SQL. This structured approach for collecting and accessing data introduces great flexibility, making it useful for multiple purposes. For example, queries can be constructed to audit infrastructure for compliance, vulnerabilities, malware analysis and intrusion detection, etc. Data collected by osquery can be useful to anybody from IT support teams to CSIRTs. However, in this blog post we’ll narrow our focus and explore how to use osquery specifically for macOS malware analysis (though the methodologies discussed are the same for Windows and Linux operating systems).
Last week, Malwarebytes posted an article highlighting new malware discovered by John Lambert (Microsoft), Patrick Wardle (Objective-See and Digita Security) and Adam Thomas (Malwarebytes), and sure enough, persistence using launchd is still a common thing.