In recent days, the VPNFilter malware has attracted attention, much of it in the wake of a May 25 public service announcement from the FBI, as well as a number of announcements from vendors and security companies. In this blog post, I examine the VPNFilter malware attack by analyzing the vulnerabilities at play, how they were exploited, and the impact on the Internet. I also outline recommendations for the next generation of small Internet of Things (IoT) device manufacturers, including home routers, which were the target of VPNFilter malware. Because this post also emphasizes the prioritization of vulnerabilities that have significant or large-scale impact, I will recap recommendations made in the March 2017 blog post on the Mirai botnet.
DoD programs continue to experience cost overruns; the inadequacies of cost estimation were cited by the Government Accountability Office (GAO) as one of the top problem areas. A recent SEI blog post by my fellow researcher Robert Stoddard, Why Does Software Cost So Much?, explored SEI work that is aimed at improving estimation and management of the costs of software-intensive systems. In this post, I provide an example of how causal learning might be used to identify specific causal factors that are most responsible for escalating costs.
Runtime assurance (RA) has become a promising technique for ensuring the safe behavior of autonomous systems (such as drones or self-driving vehicles) whose behavior cannot be fully determined at design time. The Department of Defense (DoD) is increasingly focusing on the use of complex, non-deterministic systems to address rising software complexity and the use of machine learning techniques. In this environment, assuring software correctness has become a major challenge, especially in uncertain and contested environments. This post highlights work by a team of SEI researchers to create tools and techniques that will ensure the safety of distributed cyber-physical systems.
Bugs and weaknesses in software are common: 84 percent of software breaches exploit vulnerabilities at the application layer. The prevalence of software-related problems is a key motivation for using application security testing (AST) tools. With a growing number of application security testing tools available, it can be confusing for information technology (IT) leaders, developers, and engineers to know which tools address which issues. This blog post, the first in a series on application security testing tools, will help to navigate the sea of offerings by categorizing the different types of AST tools available and providing guidance on how and when to use each class of tool.
See the second post in this series, Decision-Making Factors for Selecting Application Security Testing Tools.
As part of an ongoing effort to keep you informed about our latest work, this blog post summarizes some recently published SEI reports, podcasts, and presentations highlighting our work in deep learning, cyber intelligence, interruption costs, digital footprints on social networks, managing privacy and security, and network traffic analysis. These publications highlight the latest work of SEI technologists in these areas. This post includes a listing of each publication, author(s), and links where they can be accessed on the SEI website.