Recently, Microsoft published a blog post called Moving Beyond EMET that appears to make two main points: (1) Microsoft EMET will no longer support EMET after July 31, 2018, and (2) Windows 10 provides protections that make EMET unnecessary. In this blog post, I explain why Windows 10 does not provide the additional protections that EMET does and why EMET is still an important tool to help prevent exploitation of vulnerabilities.
Today we are announcing the release of the CERT Basic Fuzzing Framework Version 2.8 (BFF 2.8). It's been about three years since we released BFF 2.7. In this post, I highlight some of the changes we've made.
Users of Google Sign-In find that it integrates well with the Android platform, but iOS users (iPhone, iPad, etc.) do not have the same experience. The user experience when logging in to a Google account on an iOS application is not only more tedious than the Android experience, but it also conditions users to engage in behaviors that put their Google accounts at risk!
Application whitelisting is a useful defense against users running unapproved applications. Whether you're dealing with a malicious executable file that slips through email defenses, or you have a user that is attempting to run an application that your organization has not approved for use, application whitelisting can help prevent those activities from succeeding.
Some enterprises may deploy application whitelisting with the idea that it prevents malicious code from executing. But not all malicious code arrives in the form of a single executable application file. Many configurations of application whitelisting do not prevent malicious code from executing, though. In this blog post I explain how this is possible.
I've been working on a presentation called CERT BFF - From Start to PoC. In the process of preparing my material, I realized that a visualization could help people understand what happens during the BFF string minimization process.
What does it mean to say that an indicator is exhibiting persistent behavior? This is a question that Timur, Angela, and I have been asking each other for the past couple of months. In this blog post, we show you the analytics that we believe identify persistent behavior and how that identification can be used to identify potential threats as well as help with network profiling.
As you may have read in a previous post, the CERT/CC has been actively researching vulnerabilities in the connected vehicles. When we began our research, it became clear that in the realm of cyber-physical systems, safety is king. For regulators, manufacturers, and the consumer, we all want (and expect!) the same thing: a safe vehicle to drive. But what does safety mean in the context of security? This is the precisely the question that the National Highway Transit Safety Administration (NHTSA) asked the public in its federal register notice.
In this blog post, I describe sentiment analysis and discuss its use in the area of insider threat. Sentiment analysis, often referred to as opinion mining, refers to the application of natural language processing (NLP), computational linguistics, and text analytics to identify and extract subjective information in source materials (Wikipedia).