Category: Secure Coding

Software vulnerabilities typically cost organizations an average of $300,000 per security incident. Efforts aimed at eliminating software vulnerabilities must focus on secure coding, preventing the vulnerabilities from being deployed into production code. "Between 2010 and 2015, buffer overflows accounted for between 10-16% of publicly reported security vulnerabilities in the U.S. National Vulnerability Database each year," Microsoft researcher David Narditi wrote in a recent report. In March, the Secure Coding Team in the SEI's CERT Division published the 2016 edition of our SEI CERT C++ Coding Standard and made it freely available for download. In this blog post I will highlight some distinctive rules from the standard.

Federal agencies and other organizations face an overwhelming security landscape. The arsenal available to these organizations for securing software includes static analysis tools, which search code for flaws, including those that could lead to software vulnerabilities. The sheer effort required by auditors and coders to triage the large number of potential code flaws typically identified by static analysis can hijack a software project's budget and schedule. Auditors need a tool to classify alerts and to prioritize some of them for manual analysis. As described in my first post in this series, I am leading a team on a research project in the SEI's CERT Division to use classification models to help analysts and coders prioritize which vulnerabilities to address. In this second post, I will detail our collaboration with three U.S. Department of Defense (DoD) organizations to field test our approach. Two of these organizations each conduct static analysis of approximately 100 million lines of code (MLOC) annually.

By Will Klieber
CERT Secure Coding Team

This blog post is co-authored by Will Snavely.

Finding violations of secure coding guidelines in source code is daunting, but fixing them is an even greater challenge. We are creating automated tools for source code transformation. Experience in examining software bugs reveals that many security-relevant bugs follow common patterns (which can be automatically detected) and that there are corresponding patterns for repair (which can be performed by automatic program transformation). For example, integer overflow in calculations related to array bounds or indices is almost always a bug. While static analysis tools can help, they typically produce an enormous number of warnings. Once an issue has been identified, teams are only able to eliminate a small percentage of the vulnerabilities identified. As a result, code bases often contain an unknown number of security bug vulnerabilities. This blog post describes our research in automated code repair, which can eliminate security vulnerabilities much faster than the existing manual process and at a much lower cost. While this research focuses to the C programming language, it applies to other languages as well.

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.

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.

In 2015, the National Vulnerability Database (NVD) recorded 6,488 new software vulnerabilities, and the NVD documents a total of 74,885 software vulnerabilities discovered between 1988-2016. Static analysis tools examine code for flaws, including those that could lead to software security vulnerabilities, and produce diagnostic messages ("alerts") indicating the location of the purported flaw in the source code, the nature of the flaw, and often additional contextual information. A human auditor then evaluates the validity of the purported code flaws. The effort required to manually audit all alerts and repair all confirmed code flaws is often too much for a project's budget and schedule. Auditors therefore need tools that allow them to triage alerts, strategically prioritizing the alerts for examination. This blog post describes research we are conducting that uses classification models to help analysts and coders prioritize which alerts to address.

Today's computer systems often contain millions of lines of code and are constructed by integrating components, many of which are authored by various third parties. Application Programming Interfaces (APIs) are the glue that connects these software components. While the SEI and others have placed significant emphasis on developing secure coding practices, there has not been an equal emphasis placed on APIs. This blog post describes our recent research that aims to provide specific guidance to API designers to help them deal with the security issues regarding development of APIs.

In 2015, the SEI blog launched a redesigned platform to make browsing easier, and our content areas more accessible and easier to navigate. The SEI Blog audience also continued to grow with an ever-increasing number of visitors learning more about our research in technical debt, shift-left testing, graph analytics, DevOps, secure coding, and malware analysis. In 2015 (from January 1 through December 15), the SEI blog logged 159,604 visits and sessions (we also switched analytics platforms mid-year), a 26 percent increase in traffic from the previous year. This blog post highlights the top 10 posts published in 2015. As we did with our mid-year review, we will include links to additional related resources that readers might find of interest. We also will present the posts in descending order beginning with the 10th most popular post of 2015 and counting down to number one.

10. Ten Recommended Practices for Achieving Agile at Scale
9. Open System Architectures: When and Where to Be Closed
8. A Taxonomy of Testing
7. Is Java More Secure Than C?
6. Managing Software Complexity in Models
5. The Pharos Framework: Binary Static Analysis of Object Oriented Code
4. Developing a Software Library for Graph Analytics
3. Four Types of Shift-Left Testing
2. DevOps Technologies: Fabric or Ansible
1. A Field Study of Technical Debt

By David Svoboda
Senior Member of the Technical Staff
CERT Division

Whether Java is more secure than C is a simple question to ask, but a hard question to answer well. When we began writing the SEI CERT Oracle Coding Standard for Java, we thought that Java would require fewer secure coding rules than the SEI CERT C Coding Standard because Java was designed with security in mind. We naively assumed that a more secure language would need fewer rules than a less secure one. However, Java has 168 coding rules compared to just 116 for C. Why? Was our (admittedly simplistic) assumption completely spurious? Or, are there problems with our C or Java rules? Or, are Java programs, on average, just as susceptible to vulnerabilities as C programs? In this post, I attempt to analyze our CERT rules for both C and Java to determine if they indeed refute the conventional wisdom that Java is more secure than C.

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 governing operational resilience, model-driven engineering, software quality, Android app analysis, software architecture, and emerging technologies. This post includes a listing of each report, author(s), and links where the published reports can be accessed on the SEI website.

This blog post was co-authored by Will Klieber.

Each software application installed on a mobile smartphone, whether a new app or an update, can introduce new, unintentional vulnerabilities or malicious code. These problems can lead to security challenges for organizations whose staff uses mobile phones for work. In April 2014, we published a blog post highlighting DidFail (Droid Intent Data Flow Analysis for Information Leakage), which is a static analysis tool for Android app sets that addresses data privacy and security issues faced by both individual smartphone users and organizations. This post highlights enhancements made to DidFail in late 2014 and an enterprise-level approach for using the tool.

A zero-day vulnerability refers to a software security vulnerability that has been exploited before any patch is published. In the past, vulnerabilities were widely exploited even when a patch was available, which means they were not zero-day. Today, zero-day vulnerabilities are common. Notorious examples include the recent Stuxnet and Operation Aurora exploits. Vulnerabilities may arise from a variety of sources, but most vulnerabilities are the result of simple coding errors. Consequently, developers need to understand common traps and pitfalls in the programming language, libraries, and platform to produce code that is free of vulnerabilities.

With the rise of multi-core processors, concurrency has become increasingly common. The broader use of concurrency, however, has been accompanied by new challenges for programmers, who struggle to avoid race conditions and other concurrent memory access hazards when writing multi-threaded programs. The problem with concurrency is that many programmers have been trained to think sequentially, so when multiple threads execute concurrently, they struggle to visualize those threads executing in parallel. When two threads attempt to access the same unprotected region of memory concurrently (one reading, one writing) logical inconsistencies can arise in the program, which can yield security concerns that are hard to detect.

According to a 2013 report examining 25 years of vulnerabilities (from 1998 to 2012), buffer overflow causes 14 percent of software security vulnerabilities and 35 percent of critical vulnerabilities, making it the leading cause of software security vulnerabilities overall. As of July 2014, the TIOBE index indicates that the C programming language, which is the language most commonly associated with buffer overflows, is the most popular language with 17.1 percent of the market. Embedded systems, network stacks, networked applications, and high-performance computing rely heavily upon C. Embedded systems can be especially vulnerable to buffer overflows because many of them lack hardware memory management units. This blog post describes my research on the Secure Coding Initiative in the CERT Division of the Carnegie Mellon University Software Engineering Instituteto create automated buffer overflow prevention.

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 secure coding, CERT Resilience Management Model, malicious-code reverse engineering, systems engineering, and incident management. This post includes a listing of each report, author(s), and links where the published reports can be accessed on the SEI website.

In the first half of this year, the SEI blog has experienced unprecedented growth, with visitors in record numbers learning more about our work in big data, secure coding for Android, malware analysis, Heartbleed, and V Models for Testing. In the first six months of 2014 (through June 20), the SEI blog has logged 60,240 visits, which is nearly comparable with the entire 2013 yearly total of 66,757 visits. As we reach the mid-year point, this blog posting takes a look back at our most popular areas of work (at least according to you, our readers) and highlights our most popular blog posts for the first half of 2014, as well as links to additional related resources that readers might find of interest.

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.)

This blog post describes a research initiative aimed at eliminating vulnerabilities resulting from memory management problems in C and C++. Memory problems in C and C++ can lead to serious software vulnerabilities including difficulty fixing bugs, performance impediments, program crashes (including null pointer deference and out-of-memory errors), and remote code execution.

As part of an ongoing effort to keep you informed about our latest work, I'd like to let you know about some recently published SEI technical reports and notes. These reports highlight the latest work of SEI technologists in information assurance and agile, the Team Software Process (TSP), CERT secure coding standards, resource allocation, fuzzing, cloud computing interoperability, and cloud computing at the tactical edge. This post includes a listing of each report, author(s), and links where the published reports can be accessed on the SEI website.

By analyzing vulnerability reports for the C, C++, Perl, and Java programming languages, the CERT Secure Coding Team observed that a relatively small number of programming errors leads to most vulnerabilities. Our research focuses on identifying insecure coding practices and developing secure alternatives that software programmers can use to reduce or eliminate vulnerabilities before software is deployed. In a previous post, I described our work to identify vulnerabilities that informed the revision of the International Organization for Standardization (ISO) and International Electrotechnical Commission (IEC) standard for the C programming language. The CERT Secure Coding Team has also been working on the CERT C Secure Coding Standard, which contains a set of rules and guidelines to help developers code securely. This posting describes our latest set of rules and recommendations, which aims to help developers avoid undefined and/or unexpected behavior in deployed code.

Buffer overflows--an all too common problem that occurs when a program tries to store more data in a buffer, or temporary storage area, than it was intended to hold--can cause security vulnerabilities. In fact, buffer overflows led to the creation of the CERT program, starting with the infamous 1988 "Morris Worm" incident in which a buffer overflow allowed a worm entry into a large number of UNIX systems. For the past several years, the CERT Secure Coding team has contributed to a major revision of the International Organization for Standardization (ISO) and International Electrotechnical Commission (IEC) standard for the C programming language. Our efforts have focused on introducing much-needed enhancements to C and its standard library to address security issues, such as buffer overflows.