Wednesday, March 16, 2022

(Air)Dropping some Knowledge: Using RLEAPP to Identify the Phone Number Used in an AirDrop Transfer

Summary: This post explains how to use RLEAPP to process sysdiagnose logs extracted from an iOS device to identify the phone number used in an AirDrop transfer. 

Long Version:

Imagine the following scenario… You are sitting in *insert place here* when you get an AirDrop request from an unknown subject containing a potential threat.

There’s nothing they can do to identify this mystery person, right? Wrong! Keep reading to find out!

First, some quick definitions to get us started…

Sysdiagnose Logs

Sysdiagnose logs are a series of logs used to help developers debug their apps. These logs collect so much information that they can be a goldmine of data for forensic examiners. 

Sysdiagnose logs are manually triggered by the user or they can also be generated by loading  specific iOS profiles. 

A lot of research on the forensic use of sysdiagnose logs has been done by Heather Mahalik, Mattia Epifani, and Adrian Leong, including a mind-blowing 73-page paper that is a mobile device forensic “must-read”, along with a series of scripts to parse them.


AirDrop is a native feature in iOS and MacOS that leverages Bluetooth and Wi-Fi and allows users that are in physically close proximity of each other to transfer files in an encrypted manner. Many brilliant examiners have done plenty of research on AirDrop forensics. Some of my favorite articles are:

The forensic paper “Analysis of Sysdiagnose in iOS 15 to Identify the Sending Phone Number of AirDrop Data”, written by Brandon Epstein, Benjamin Klein, and Derek Feuerstein. Published in Journal of Forensic Sciences (Jan 2022), the paper discusses a method for identifying the sender of an AirDrop file. Partial sha-256 hash values are located in "system_logs.logarchive" within the receiver’s sysdiagnose logs. Permutations of these partial hashes are generated using a list of possible country and area codes, allowing for identification of the sender’s phone number. 

Alexis Brignoni created an RLEAPP module based on this research, facilitating what could be a very tedious process.


I know some digital forensics “purists” will scream at the thought of some of the steps suggested here; they will claim that you are working on and “altering” live evidence. Newsflash: You can’t do mobile forensics by connecting a phone to a write blocker, so you are making changes to your evidence anyway. 

Also, when you trigger the sysdiagnose logs, you are technically not creating data, but collecting a series of logs that are already present and putting them in a container. 

The sysdiagnose logs are extremely volatile so by the time you get back to your lab and wait on a queue of phones (which is common in every forensic lab these days) your precious goldmine of data may have been overwritten. 

When you have a dangerous criminal on the run and time is not on your side, you have to make a quick choice, so just make sure to document your steps and the reasons behind them.  This is why we test and validate constantly. 

The following steps allow for the collection and processing of the "system_logs.logarchive" in order to obtain the sender’s phone number. For this testing, an iPhone 13 Pro running iOS 15.3.1 was used.

1. Generate the sysdiagnose logs 

Sysdiagnose logs can be generated by using a combination of buttons, leveraging Accessibility features, or by loading specific iOS profiles. There are several articles such as this one that explain detail how to trigger these logs, so in this post we are just going to summarize a couple of ways:

Using Accessibility: 

  1. Go to Settings > Accessibility > Touch >  Turn on Assistive Touch

    b.    Go to Single-Tap > Analytics 

        c. Press the emulated button (gray/white circular button on your screen). You will receive a notification on the top portion of the screen that says “AssistiveTouch Gathering analytics.”

Physical Button Combination

I find this way a bit more challenging, but I’m listing it here because some people prefer it, as they feel they are making less changes to the device.

    a.    Press and hold Vol. Up + Vol. Down + Sleep/Wake (Lock) buttons all at once for approximately  ~  1 second (250 milliseconds according to the blog posts). 

    b.    Wait for approximately 10 minutes for the logs to be generated. 

NOTE: ** Don’t be impatient and hold all three buttons forever unless you want a surprise visit from your local law enforcement and you want to scare your emergency contacts… “Accidentally” triggering “Emergency SOS”  always makes for a “fun” evening! 

2. Find the sysdiagnose logs

    a.    Go to Settings > General  > Privacy > Analytics & Improvement > Analytics Data.

Settings - Privacy

Analytics & Improvements

Analytics Data

    b.    Apple collects A LOT of analytics data, so just scroll down until you see a line that starts with “sysdiagnose_” followed by a timestamp. In this example, I had two, so I just chose the one I wanted.

3.   Export  the sysdiagnose logs to a Mac computer using your favorite method: iBackupBot, iTunes, AirDrop… 

I used AirDrop as an example in this post. This may not be the most forensically sound manner, but I just wanted something quick to start looking at these logs. Different methods of exporting sysdiagnose logs are beyond the scope of this post.

4. Use terminal to convert to extract AirDrop related events into an .ndjson file.

Unzip the sysdiagnoze .tar.gz file. Open Mac Terminal and use the “log show” command to filter by “AirDrop” related events (predicate ‘category = “AirDrop”’) and use the “style” switch to export into an “ndjson” format. Make sure you are running the command on the system_logs.logarchive you are trying to analyze (in other words, don’t run it on your own data… how do I know this can happen…?)

log show <path to the system_logs.logarchive> --style ndjson --predicate 'category = "AirDrop"'  >  airdrop.ndjson

For example:

If you want to learn more about the “log” command, this is a good reference or you can always use the man command. 

5. Update the “areacode.txt” file with the list of possible area codes you are looking for. 

This file is located within the RLEAPP directory,  in ‘scripts/areacode/’. While you could technically put every area code in the US, it would cause the RLEAPP module to be REALLY slow… (so use your good ol’ investigative skills to narrow this down). 

NOTE: If you truly have no idea what the area code is, I would suggest running the airdropmsisdn script to find the phone number. You will need the target hash start and ending fragments.

6.    Run RLEAPP
Select the “Airdrop Numbers” module – point it at the directory in your system that contains the “airdrop.ndjson” file. Select the output directory path, hit “Process”, and watch the magic happen!


A very clean output in under 2 minutes!

Note: This process only works if the Apple ID phone number was used to send the file. 

Stay tuned for additional research being conducted in case an Apple ID email was used! 

As usual, feel free to reach out to me  with any  questions or comments, this is how we grow as a community.


  • A huge thank you to the following people:
  • Alexis Brignoni,  of course, for sharing this idea with me
  • Brandon Epstein, Benjamin Klein, and Derek Feuerstein for writing the paper that inspired this post
  • Dan Ogden,  for always peer reviewing my work
  • Heather Mahalik, Mattia Epifani, and Adrian Leong for sharing their awesome sysdiagnose forensics paper with the community
  • Sarah Edwards for all your work related to iOS and Mac forensics, and in this case to AirDrop forensics.
  • Kinga Kięczkowska for your post related to AirDrop forensics

No comments:

Post a Comment

Peeking at User Notification Events in iOS 15

Summary iOS Notifications allow users to peek at content that could be important to them without having to access the app. For us forensic e...