Over the past six months, we have developed new security-focused modeling tools that capture vulnerabilities and their propagation paths in an architecture. Recent reports (such as the remote attack surface analysis of automotive systems) show that security is no longer only a matter of code and is tightly related to the software architecture. These new tools are our contribution toward improving system and software analysis. We hope they will move forward other work on security modeling and analysis and be useful to security researchers and analysts. This post explains the motivation of our work, the available tools, and how to use them.
The exponential increase in cybercrime is a perfect example of how rapidly change is happening in cyberspace and why operational security is a critical need. In the 1990s, computer crime was usually nothing more than simple trespass. Twenty-five years later, computer crime has become a vast criminal enterprise with profits estimated at $1 trillion annually. One of the primary contributors to this astonishing success is the vulnerability of software to exploitation through defects. How pervasive is the problem of vulnerability? The average cost of a data breach is $4 million, up 29 percent since 2013, according to Ponemon Institute and IBM data. Ponemon also concluded that there's a 26-percent probability that an enterprise will be hit by one or more data breaches of 10,000 records over the next 2 years. Increased system complexity, pervasive interconnectivity, and widely distributed access have increased the challenges for building and acquiring operationally secure capabilities. This blog post introduces a set of seven principles that address the challenges of acquiring, building, deploying, and sustaining software systems to achieve a desired level of confidence for software assurance.
As part of an ongoing effort to keep you informed about our latest work, this blog post summarizes some recently published SEI technical reports, white papers, and webinars in resilience, effective cyber workforce development, secure coding, data science, insider threat, and scheduling. 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.
In 2011, the U.S. Government maintained a fleet of approximately 8,000 unmanned aerial systems (UAS), commonly referred to as "drones," a number that continues to grow. "No weapon system has had a more profound impact on the United States' ability to provide persistence on the battlefield than the UAVs," according to a report from the 2012 Defense Science Board. Making sure government and privately owned drones share international air space safely and effectively is a top priority for government officials. Distributed Adaptive Real-Time (DART) systems are key to many areas of Department of Defense (DoD) capability, including the safe execution of autonomous, multi-UAS missions having civilian benefits. DART systems promise to revolutionize several such areas of mutual civilian-DoD interest, such as robotics, transportation, energy, and health care. To fully realize the potential of DART systems, however, the software controlling them must be engineered for high-assurance and certified to operate safely and effectively. In short, these systems must satisfy guaranteed and highly-critical safety requirements (e.g., collision avoidance) while adapting smartly to achieve application requirements, such as protection coverage, while operating in dynamic and uncertain environments. This blog post describes our architecture and approach to engineering high-assurance software for DART systems.
Network flow plays a vital role in the future of network security and analysis. With more devices connecting to the Internet, networks are larger and faster than ever before. Therefore, capturing and analyzing packet capture data (pcap) on a large network is often prohibitively expensive. Cisco developed NetFlow 20 years ago to reduce the amount of information collected from a communication by aggregating packets with the same IP addresses, transport ports, and protocol (also known as the 5-tuple) into a compact record. This blog post explains why NetFlow is still important in an age in which the common wisdom is that more data is always better. Moreover, NetFlow will become even more important in the next few years as communications become more opaque with the development of new protocols that encrypt payloads by default.
Writing secure C++ code is hard. C++11 and C++14 have added new facilities that change the way programmers write C++ code with the introduction of features like lambdas and concurrency. Few resources exist, however, describing how these new facilities also increase the number of ways in which security vulnerabilities can be introduced into a program or how to avoid using these facilities insecurely. Previous secure coding efforts, including the SEI CERT C Coding Standard and SEI CERT Oracle Coding Standard for Java , have proved successful in helping programmers identify possible insecure code in C and Java but do not provide sufficient information to cover C++. Other efforts, such as MISRA C++:2008 and the community-led C++ Core Guidelines, create a subset of the C++ language and do not focus on security. This blog post introduces the SEI CERT C++ Coding Standard and explores some examples of areas in C++ that can result in security vulnerabilities.
By the close of 2016, "Annual global IP traffic will pass the zettabyte ([ZB]; 1000 exabytes [EB]) threshold and will reach 2.3 ZBs per year by 2020" according to Cisco's Visual Networking Index. The report further states that in the same time frame smartphone traffic will exceed PC traffic. While capturing and evaluating network traffic enables defenders of large-scale organizational networks to generate security alerts and identify intrusions, operators of networks with even comparatively modest size struggle with building a full, comprehensive view of network activity. To make wise security decisions, operators need to understand the mission activity on their network and the threats to that activity (referred to as network situational awareness). This blog post examines two different approaches for analyzing network security using and going beyond network flow data to gain situational awareness to improve security.
A 2016 study on cybersecurity and digital trust found that 69 percent of organizations surveyed experienced an attempted or successful theft or corruption of data by insiders in the last 12 months. Despite the impact of insider threat--and continued mandates that government agencies and their contractors put insider threat programs in place--a number of organizations still have not implemented them. Moreover, the programs that have been implemented often have serious deficiencies. One impediment to organizations establishing an insider threat program is the lack of a clear business case for implementing available countermeasures.
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.