The second issue is that reverse engineering all boot records is impractical. Given the job of determining if a single system is infected with a bootkit, a malware analyst could acquire a disk image and then reverse engineer the boot bytes to determine if anything malicious is present in the boot chain. However, this process takes time and even an army of skilled reverse engineers wouldn’t scale to the size of modern enterprise networks. To put this in context, the compromised enterprise network referenced in our ROCKBOOT blog post had approximately 10,000 hosts. Assuming a minimum of two boot ..read more

Since our initial public release of capa, incident responders and reverse engineers have used the tool to automatically identify capabilities in Windows executables. With our newest code and ruleset updates, capa v3 also identifies capabilities in Executable and Linkable Format (ELF) files, such as those used on Linux and other Unix-like operating systems. This blog post describes the extended analysis and other improvements. You can download capa v3 standalone binaries from the project’s release page and checkout the source code on GitHub. ELF File Format Support capa finds capabilities ..read more

The FLARE team is once again hosting its annual Flare-On challenge, now in its eighth year. Take this opportunity to enjoy some extreme social distancing by solving fun puzzles to test your mettle and learn new tricks on your path to reverse engineering excellence. The contest will begin at 8:00 p.m. ET on Sept. 10, 2021. This is a CTF-style challenge for all active and aspiring reverse engineers, malware analysts, and security professionals. The contest runs for six full weeks and ends at 8:00 p.m. ET on Oct. 22, 2021. This year’s contest will consist of 10 challenges and feature a variety of ..read more

We are excited to announce version 2.0 of our open-source tool called capa. capa automatically identifies capabilities in programs using an extensible rule set. The tool supports both malware triage and deep dive reverse engineering. If you haven’t heard of capa before, or need a refresher, check out our first blog post. You can download capa 2.0 standalone binaries from the project’s release page and checkout the source code on GitHub. capa 2.0 enables anyone to contribute rules more easily, which makes the existing ecosystem even more vibrant. This blog post details the following major impro ..read more

Continuing our discussion of image parsing vulnerabilities in Windows, we take a look at a comparatively less popular vulnerability class: uninitialized memory. In this post, we will look at Windows’ inbuilt image parsers—specifically for vulnerabilities involving the use of uninitialized memory. The Vulnerability: Uninitialized Memory In unmanaged languages, such as C or C++, variables are not initialized by default. Using uninitialized variables causes undefined behavior and may cause a crash. There are roughly two variants of uninitialized memory: Direct uninitialized memory usage: An unin ..read more

FireEye recently encountered various phishing campaigns, mostly in the Americas and Europe, using source code obfuscation with compromised or bad domains. These domains were masquerading as authentic websites and stole personal information such as credit card data. The stolen information was then shared to cross-platform, cloud-based instant messaging applications. Coming off a busy holiday season with a massive surge in deliveries, this post highlights a phishing campaign involving a fake DHL tracking page. While phishing attacks targeting users of shipping services is not new, the techniques ..read more

Highlights        Perform a case study on using Transformer models to solve cyber security problems Train a Transformer model to detect malicious URLs under multiple training regimes Compare our model against other deep learning methods, and show it performs on-par with other top-scoring models Identify issues with applying generative pre-training to malicious URL detection, which is a cornerstone of Transformer training in natural language processing (NLP) tasks Introduce novel loss function that balances classification and generative loss to achieve improved performance ..read more

In August 2020, we released a blog post about how the Speakeasy emulation framework can be used to emulate user mode malware such as shellcode. If you haven’t had a chance, give the post a read today. In addition to user mode emulation, Speakeasy also supports emulation of kernel mode Windows binaries. When malware authors employ kernel mode malware, it will often be in the form of a device driver whose end goal is total compromise of an infected system. The malware most often doesn’t interact with hardware and instead leverages kernel mode to fully compromise the system and remain hidden. Cha ..read more

Andrew Davis recently announced the public release of his new Windows emulation framework named Speakeasy. While the introductory blog post focused on using Speakeasy as an automated malware sandbox of sorts, this entry will highlight another powerful use of the framework: automated malware unpacking. I will demonstrate, with code examples, how Speakeasy can be used programmatically to: Bypass unsupported Windows APIs to continue emulation and unpacking Save virtual addresses of dynamically allocated code using API hooks Surgically direct execution to key areas of code using code hooks Dump a ..read more

Though COVID-19 has had enormous effects on our society and economy, its effects on the cyber threat landscape remain limited. For the most part, the same actors we have always tracked are behaving in the same manner they did prior to the crisis. There are some new challenges, but they are perceptible, and we—and our customers—are prepared to continue this fight through this period of unprecedented change. The significant shifts in the threat landscape we are currently tracking include: The sudden major increase in a remote workforce has changed the nature and vulnerability of enterprise netw ..read more