We are excited to announce the latest update to the SANS Institute's FOR585: Smartphone Forensic Analysis In-Depth!
This update focused on research, testing, and documenting significant changes across iOS 17, Android 13 and 14, new data formats, and popular third-party applications. Chat applications, mobile browsers, system logs and cloud storage have evolved over the last year, so with this update we've re-created these artifacts in datasets and cover the details in the course material. This enables examiners to learn about the changes and apply the logic to their cases immediately after gaining hand-on experience via the course labs.
Anti-Forensics and Data Destruction
In many smartphone investigations, we find that the device has been tampered with. We have seen cases where applications are deleted, browser history is cleared, anti-forensic applications are installed to aid in cleaning up the device, and devices are simply wiped. Data destruction is becoming more common as users become savvy on how data is stored on devices, thus making our jobs as examiners more difficult. Common methods for destroying or hiding evidence on smartphones is covered in the course, as are methods of detection. ArtEx, a free iOS research tool developed by Ian Whiffin, helps identify wiping artifacts on iOS devices.
This tool and others are used in FOR585 to deep dive into smartphone data destruction artifacts. (Heather Mahalik Barnhart and Ian Whiffin wrote a blog on iOS wipe artifacts that can be read here.) As for Android, artifacts are more complex, as the hardware differs per manufacturer. A hands-on lab will help clarify reliable artifacts detecting Android evidence destruction when someone attempts to cover their tracks.
Wi-Fi Location Artifacts
Locations are prevalent on smartphone devices, but not all are reliable. We spent a lot of time researching, validating, and documenting locations that are accurate on Android and iOS devices. The location artifacts you can trust are covered in FOR585 as well as some that require additional supporting evidence. Piecing together the artifacts will often result in the examiner being able to say where a device was when an action occurred.
Trusted location artifacts on Android devices are more difficult to obtain compared to iOS. Wi-Fi traces are stored in many locations on Android devices and can be used to place a user at a location and provide key details such as device settings, times connected to a specific network, network password information, device reboots, and more. Mattia Epifani conducted research on WiFiConfigStore.xml which is covered in this course and in hand-on labs. The level of detail stored in WiFiConfigStore.xml is barely touched by the tools that simply parse the Wi-Fi connection. Some of these key artifacts include:
- SSID - Name of the network represented by a UTF-8 string or hexadecimal digits
- BSSID - String value of the MAC address
- Trusted - Is the connection trusted or not
- DisableReason - Responses could be wrong password, network not found, no internet, etc.
- HasEverConnected - Shows if a successful connection was established
- numRebootsSinceLastUse - Shows number of device reboots since last use.
Another Android file of interest is iwc_dump.txt, which stores common Wi-Fi connections and the time that the connection was lost as well as when Wi-Fi was switched on and off by the user.
The timestamps in this file alone can cause confusion, as this data is logged with the local time of the connection but it also provides a timestamp that can accurately be converted to UTC.
Dark Periods
Dark periods can be defined as periods of time where a device was in airplane mode, disconnected from cellular or Wi-Fi, or powered off. How a device was powered down may matter in an investigation. For example, if the phone battery died, that value will differ from a phone being shutdown manually by a user. Battery status is often tracked in eRR.p on Samsung devices and can hold value if the suspect claims their battery was depleted, which is why their device was powered off. But then you find that the device was at 82% power when the device was shut down and that the value shows the shutdown was "user requested."
For both Android and iOS, a lot of research was conducted by several people in the DFIR community to identify trusted artifacts that reveal the truth. This often includes recreating data to validate artifacts you find in an investigation. While time consuming, the results can make or break a case. Josh Hickman released a blog on eRR.p (formerly RR.p on older Android devices) and the value of diving into this file.
A big push of this course update was to identify these dark period artifacts on both iOS and Android, as criminals are becoming smarter and trying to minimize the data that is collected by smartphones while at the scene of a crime. Remember, sometimes the lack of evidence can be exactly what you are looking for. If someone took extra steps to isolate their device from location tracking, cellular networks, Wi-Fi, etc., the lack of data during that period could be associated to the timeline of interest. Proving patterns of behavior is important in mobile investigations, and these concepts are covered in the course and enforced in hands-on labs.
Summing Up the Update
The latest FOR585 update enhances the capabilities of examiners across a wide range of Android and iOS artifacts. Every lab in the course has been updated over the last year, allowing you to learn from the latest operating systems on the devices as well as understand key artifacts that differ per Android manufacturers that may not be supported by the popular smartphone tools. This course aims to arm you with a virtual machine built to showcase the best tools for mobile forensics, customized scripts for the course, custom SQL queries, and open-source tools.
The goal of the update was to ensure we are providing you the most up-to-date and accurate training focusing on artifacts that put a person behind a device, at a location, on an application, when a crime or situation occurs. We guide you to learn advanced analysis techniques to validate the artifacts so you can be sure how the data landed on the device.
In today's digital forensic environment, having this skillset on a team is a requirement to support the examination of computer crimes, fraud, insider threat, employee misuse, espionage, ransomware, malware attacks, and cases involving the use of AI.
You can find a flyer covering many of the latest updates here.
Heather Mahalik Barnhart has spent over twenty years conducting computer crime investigations. A majority of her career was focused on mobile devices and she has worked cases spanning from ICAC to counter-terrorism investigations. Heather has provided training to military special forces, Federal Government agencies, consulting firms, and law enforcement. She is a SANS Institute Fellow and co-author of FOR585 - Smartphone Forensic Analysis In-Depth. Heather is the Senior Director of Community Engagement at Cellebrite and a passionate mobile forensic researcher in the community. Connect with her on X @heathermahalik
Domenica Lee Crognale is a Certified Instructor with SANS and the co-author of FOR585: Smartphone Forensic Analysis In-Depth. In her role as a principal security engineer, she brings over 15 years of experience as a contractor for various federal agencies, supporting digital forensic investigations and promoting cybersecurity best practices within Law Enforcement and the Intelligence Community. Domenica has trained military special forces, the United States Coast Guard, and FBI personnel. In her personal time, she rigorously tests mobile forensics tools and conducts security assessments for mobile applications. Connect with her on X @domenicacrognale.
