The Wireless Emergency Alerts (WEA) service went online in April 2012, giving emergency management agencies such as the National Weather Service or a city's hazardous materials team a way to send messages to mobile phone users located in a geographic area in the event of an emergency. Since the launch of the WEA service, the newest addition to the Federal Emergency Management Agency (FEMA) Integrated Public Alert and Warning System (IPAWS),"trust" has emerged as a key issue for all involved. Alert originators at emergency management agencies must trust WEA to deliver alerts to the public in an accurate and timely manner. The public must also trust the WEA service before it will act on the alerts. Managing trust in WEA is a responsibility shared among many stakeholders who are engaged with WEA. This blog post, the first in a series, highlights recent research aimed at enhancing both the trust of alert originators in the WEA service and the public's trust in the alerts it receives.
To maintain a competitive edge, software organizations should be early adopters of innovation. To achieve this edge, organizations from Flickr and IBM to small tech startups are increasingly adopting an environment of deep collaboration between development and operations (DevOps) teams and technologies, which historically have been two disjointed groups responsible for information technology development. "The value of DevOps can be illustrated as an innovation and delivery lifecycle, with a continuous feedback loop to learn and respond to customer needs," Ashok Reddy writes in the technical white paper, DevOps: The IBM approach.
As part of an ongoing effort to keep you informed about our latest work, I would like to let you know about some recently published SEI technical reports and notes. These reports highlight the latest work of SEI technologists in cybersecurity risks, software assurance, advanced persistent threat, international insider threat, Wireless Emergency Alerts Service, security and survivability, and acquisition.
The Government Accountability Office (GAO) recently reported that acquisition program costs typically run 26 percent over budget, with development costs exceeding initial estimates by 40 percent. Moreover, many programs fail to deliver capabilities when promised, experiencing a 21-month delay on average. The report attributes the "optimistic assumptions about system requirements, technology, and design maturity [that] play a large part in these failures" to a lack of disciplined systems engineering analysis early in the program. What acquisition managers do not always realize is the importance of focusing on software engineering during the early systems engineeringeffort. Improving on this collaboration is difficult partly because both disciplines appear in a variety of roles and practices. This post, the first in a series, addresses the interaction between systems and software engineering by identifying the similarities and differences between the two disciplines and describing the benefits both could realize through a more collaborative approach.
The Heartbleed bug, a serious vulnerability in the Open SSL crytographic software library, enables attackers to steal information that, under normal conditions, is protected by the Secure Socket Layer/Transport Layer Security(SSL/TLS) encryption used to secure the internet. Heartbleed and its aftermath left many questions in its wake:
- Would the vulnerability have been detected by static analysis tools?
- If the vulnerability has been in the wild for two years, why did it take so long to bring this to public knowledge now?
- Who is ultimately responsible for open-source code reviews and testing?
- Is there anything we can do to work around Heartbleed to provide security for banking and email web browser applications?
Software developers produce more than 100 billion lines of code for commercial systems each year. Even with automated testing tools, errors still occur at a rate of one error for every 10,000 lines of code. While many coding standards address code style issues (i.e., style guides), CERT secure coding standards focus on identifying unsafe, unreliable, and insecure coding practices, such as those that resulted in the Heartbleed vulnerability. For more than 10 years, the CERT Secure Coding Initiative at the Carnegie Mellon University Software Engineering Institutehas been working to develop guidance--most recently, The CERT C Secure Coding Standard: Second Edition--for developers and programmers through the development of coding standards by security researchers, language experts, and software developers using a wiki-based community process. This blog post explores the importance of a well-documented and enforceable coding standard in helping programmers circumvent pitfalls and avoid vulnerabilities.
This blog post is co-authored by Lori Flynn.
Although the Android Operating System continues to dominate the mobile device market (82 percent of worldwide market share in the third quarter of 2013), applications developed for Android have faced some challenging security issues. For example, applications developed for the Android platform continue to struggle with vulnerabilities, such as activity hijacking, which occurs when a malicious app receives a message (in particular, an intent) that was intended for another app but not explicitly designated for it. The attack can result in leakage of sensitive data or loss of secure control of the affected apps. Another vulnerability is exploited when sensitive information is leaked from a sensitive source to a restricted sink. This blog post is the second in a series that details our work to develop techniques and tools for analyzing code for mobile computing platforms. (A previous blog post, Secure Coding for the Android Platform, describes our team's development of Android rules and guidelines.)
Every day, analysts at major anti-virus companies and research organizations are inundated with new malware samples. From Flame to lesser-known strains, figures indicate that the number of malware samples released each day continues to rise. In 2011, malware authors unleashed approximately 70,000 new strains per day, according to figures reported by Eugene Kaspersky. The following year, McAfee reported that 100,000 new strains of malware were unleashed each day. An article published in the October 2013 issue of IEEE Spectrum, updated that figure to approximately 150,000 new malware strains. Not enough manpower exists to manually address the sheer volume of new malware samples that arrive daily in analysts' queues. In our work here at CERT, we felt that analysts needed an approach that would allow them to identify and focus first on the most destructive binary files. This blog post is a follow up of my earlier post entitled Prioritizing Malware Analysis. In this post, we describe the results of the research I conducted with fellow researchers at the Carnegie Mellon University (CMU) Software Engineering Institute (SEI) and CMU's Robotics Institutehighlighting our analysis that demonstrated the validity (with 98 percent accuracy) of our approach, which helps analysts distinguish between the malicious and benign nature of a binary file.