When it comes to iOS data acquisition, Elcomsoft iOS Forensic Toolkit stands head and shoulders above the competition. With its cutting-edge features and unmatched capabilities, the Toolkit has become the go-to software for forensic investigations on iOS devices. The recent update expanded the capabilities of the tool’s low-level extraction agent, adding keychain decryption support on Apple’s newest devices running iOS 16.0 through 16.4.

A while ago, we introduced an innovative mechanism that enabled access to parts of the file system for latest-generation Apple devices. The process we called “partial extraction” relied on a weak exploit that, at the time, did not allow a full sandbox escape. We’ve been working to improve the process, slowly lifting the “partial” tag from iOS 15 devices. Today, we are introducing a new, enhanced low-level extraction mechanism that enables full file system extraction for the iOS 16 through 16.3.1 on all devices based on Apple A12 Bionic and newer chips.

Intel has unveiled its latest lineup of dedicated graphics cards, driven by the powerful Intel Xe architecture. The Intel Arc series showcases impressive performance, rivaling mid-range offerings from competing brands, while maintaining an exceptional price-performance ratio that outperforms NVIDIA’s counterparts. In this article, we explore the potential of Intel Arc GPUs for forensic password recovery and delve into their performance capabilities, comparing them with both Intel’s built-in graphics and mid-range NVIDIA RTX boards.

Every three years, NVIDIA releases a new architecture used in their GeForce series graphics cards. Powered by Ada Lovelace, the new generation of GPUs delivers 80% better performance in password recovery compared to Ampere. While the new generation of NVIDIA graphics is faster and more efficient than Ampere, it also received a price hike. Is the update worth it for the forensic experts? Let’s try to find out.

As a provider of mobile forensic tools, we at Elcomsoft strongly believe in giving back to the community. Our iOS Forensic Toolkit (EIFT) is a highly complex and powerful mobile acquisition tool, consisting of almost eighty sub-projects, many of which are open source. While we have benefited from the contributions of the community, we also believe that it’s time to contribute back to the open source community by publishing our changes to those projects as required by their permissive license.

Last month, we introduced a new low-level mechanism, which enabled access to parts of the file system from many Apple devices. The partial extraction process relies on a weak exploit that did not allow full sandbox escape. Today, the limitations are gone, and we are proud to offer the full file system extraction and keychain decryption for the entire iOS 15 range up to and including iOS/iPadOS 15.7.2.

The recent update to iOS Forensic Toolkit brought two automations based on the Raspberry Pi Pico board. One of the new automations makes it possible to make long, scrollable screen shots in a semi-automatic fashion. In this article we will show how to build, program, and use a Raspberry Pi Pico board to automate scrolling screenshots.

The latest update to iOS Forensic Toolkit brings two new features, both requiring the use of a Raspberry Pi Pico board. The first feature automates the switching of iPhone 8, iPhone 8 Plus, and iPhone X devices into DFU, while the second feature adds the ability to make long, scrollable screen shots in a semi-automatic fashion. In this article we will show how to build, program, and use a Raspberry Pi Pico board to automate DFU mode.

Elcomsoft iOS Forensic Toolkit 8.20 for Mac and 7.80 for Windows now includes a new mechanism for low-level access, which enables the extraction of certain parts of the file system from the latest Apple devices. This partial extraction raises questions regarding what data can and cannot be extracted and how missing information can be accessed. Learn about the partial file system extraction, its benefits and limitations.

The first-generation HomePod is a smart speaker developed by Apple that offers high-quality audio and a range of features, including Siri integration and smart home controls. However, as with any electronic device, it can store valuable information that may be of interest in forensic investigations. In this article, we will explore how to use the forensically sound checkm8 extraction to access data stored in the HomePod, including the keychain and file system image. We will also outline the specific tools and steps required to extract this information and provide a cheat sheet for those looking to extract data from a HomePod. By the end of this article, you’ll have have a better understanding of how to extract data from the first-generation HomePod and the potential limitations of this extraction method.