In my last post, I presented how to create a YAF application label signature rule that corresponds to a text-based Snort-type rule. In this post, I discuss methods for using Analysis Pipeline to provide context to those signatures.
The context for signatures can take many forms. Some context can be derived from the individual flows that match the signatures. This information is easy to obtain from either SiLK or another traffic analysis tool--just look at the traffic that matched the signature. Analysis Pipeline lets you easily do more. I will discuss three simple options, but Analysis Pipeline can be used for more complex analyses.
Hi all, this is Jonathan Spring with my colleagues Leigh Metcalf and Rhiannon Weaver. We've been studying the dynamics of the Internet blacklist ecosystem for a few years now and the 2015 Verizon Data Breach Investigations Report has corroborated our general results. We get a lot of questions about which list is which and if we can recommend a list. We won't reveal which is which generally, but in this blog post we'll make a small exception (with permission of course) in a case study to update the results.
Ever want to use a Snort-like rule with SiLK or Analysis Pipeline to find text within packets? Timur Snoke and I were recently discussing how we could do this and realized that while neither SiLK nor Analysis Pipeline themselves do packet inspection, YAF can be used to create an application label that can be used in analyses in both SiLK and Pipeline (field 29, application). This post outlines the steps required and provides an example.
Software and acquisition professionals often have questions about recommended practices related to modern software development methods, techniques, and tools, such as how to apply agile methods in government acquisition frameworks, systematic verification and validation of safety-critical systems, and operational risk...