As part of our mission to advance the practice of software engineering and cybersecurity through research and technology transition, our work focuses on ensuring the development and operation of software-reliant Department of Defense (DoD) systems with predictable and improved quality, schedule, and cost. To achieve this mission, the SEI conducts research and development (R&D) activities involving the DoD, federal agencies, industry, and academia. As we look back on 2012, this blog posting highlights our many R&D accomplishments.
The majority of research in cyber security focuses on incident response or network defense, either trying to keep the bad guys out or facilitating the isolation and clean-up when a computer is compromised. It's hard to find a technology website that's not touting articles on fielding better firewalls, patching operating systems, updating anti-virus signatures, and a slew of other technologies to help detect or block malicious actors from getting on your network. What's missing from this picture is a proactive understanding of who the threats are and how they intend to use the cyber domain to get what they want. Our team of researchers--which included Andrew Mellinger, Melissa Ludwick, Jay McAllister, and Kate Ambrose Sereno--sought to help organizations bolster their cyber security posture by leveraging best practices in methodologies and technologies that provide a greater understanding of potential risks and threats in the cyber domain. This blog posting describes how we are approaching this challenge and what we have discovered thus far.
It is widely recognized today that software architecture serves as the blueprint for both the system and the project developing it, defining the work assignments that must be performed by design and implementation teams. Architecture is the primary purveyor of system quality attributes that are hard to achieve without a unifying architecture; it's also the conceptual glue that holds every phase of projects together for their many stakeholders. Last month, we presented two posting in a seriesfrom a panel at SATURN 2012 titled "Reflections on 20 Years of Software Architecture" that discussed the increased awareness of architecture as a primary means for achieving desired quality attributes and advances in software architecture practice for distributed real-time embedded systems during the past two decades.
Organizational improvement efforts should be driven by business needs, not by the content of improvement models. While improvement models, such as the Capability Maturity Model Integration (CMMI) or the Baldrige Criteria for Performance Excellence, provide excellent guidance and best practice standards, the way in which those models are implemented must be guided by the same drivers that influence any other business decision. Business drivers are the collection of people, information, and conditions that initiate and support activities that help an organization accomplish its mission.
In previous blog posts, I have written about applying similarity measures to malicious code to identify related files and reduce analysis expense. Another way to observe similarity in malicious code is to leverage analyst insights by identifying files that possess some property in common with a particular file of interest. One way to do this is by using YARA, an open-source project that helps researchers identify and classify malware. YARA has gained enormous popularity in recent years as a way for malware researchers and network defenders to communicate their knowledge about malicious files, from identifiers for specific families to signatures capturing common tools, techniques, and procedures (TTPs). This blog post provides guidelines for using YARA effectively, focusing on selection of objective criteria derived from malware, the type of criteria most useful in identifying related malware (including strings, resources, and functions), and guidelines for creating YARA signatures using these criteria.
CertStream is a free service for getting information from the Certificate Transparency Log Network. I decided to investigate the presence of domains generated by Domain Generation Algorithms (DGA) in this stream and I found some intersting phenomena.