BootStomp is a boot-loader bug finder. It looks for two different class of bugs: memory corruption and state storage vulnerabilities. For more info please refer to the BootStomp paper at https://seclab.cs.ucsb.edu/academic/publishing/#bootstomp-security-bootloaders-mobile-devices-2017
To run BootStomp's analyses, please read the following instructions. Note that BootStomp works with boot-loaders compiled for ARM architectures (32 and 64 bits both) and that results might slightly vary depending on angr and Z3's versions. This is because of the time angr takes to analyze basic blocks and to Z3's expression concretization results.
- analysis: Contains analysis results (Ex: IDA idbs etc) of boot images of different devices.
- tools: Contains tools that can be used to work with various images.
- angr (http://angr.io/)
$ pip install angr
- IDA PRO (https://www.hex-rays.com/products/ida/)
- IDA Decompiler (https://www.hex-rays.com/products/decompiler/)
The easiest way to use BootStomp is to run it in a docker container.
The folder docker
contains an appropriate Dockerfile
.
These are the commands to use it.
cd docker
# build the docker image
docker build -t bootstomp .
# run the docker image (if you need, use proper options to have persistent changes or shared files)
docker run -it bootstomp
# now you are inside a docker container
cd BootStomp
# run BootStomp's taint analysis on one of the examples
# this will take about 30 minutes
python taint_analysis/bootloadertaint.py config/config.huawei
# the last line of the output will be something like:
# INFO | 2017-10-14 01:54:10,617 | _CoreTaint | Results in /tmp/BootloaderTaint_fastboot.img_.out
# you can then "pretty print" the results using:
python taint_analysis/result_pretty_print.py /tmp/BootloaderTaint_fastboot.img_.out
The output should be something like this:
...
17)
===================== Start Info path =====================
Dereference address at: 0x5319cL
Reason: at location 0x5319cL a tainted variable is dereferenced and used as address.
...
Tainted Path
----------------
0x52f3cL -> 0x52f78L -> 0x52f8cL -> 0x52fb8L -> 0x52fc8L -> 0x52fecL -> 0x53000L -> 0x53014L -> 0x5301cL -> 0x53030L -> 0x53044L -> 0x53050L -> 0x5305cL -> 0x53068L
===================== End Info path =====================
# Total sinks related alerts: 5
# Total loop related alerts: 8
# Total dereference related alerts: 4
- Load the boot-loader binary in IDA (we used v6.95). Depending on the CPU architecture of the phone it has been extracted from, 32 bit or 64 bit IDA is needed.
- From the menu-bar, run File => Script file =>
find_taint.py
- Output will appear in the file
taint_source_sink.txt
under the same directory as the boot-loader itself.
Create a JSON configuration file for the boot-loader binary (see examples in config/
), where:
- bootloader: boot-loader file path
- info_path: boot-loader source/sink info file path (i.e., taint_source_sink.txt )
- arch: architecture's number of bits (available options are 32 and 64)
- enable_thumb: consider thumb mode (when needed) during the analysis
- start_with_thumb: starts the analysis with thumb mode enabled
- exit_on_dec_error: stop the analysis if some instructions cannot be decoded
- unlock_addr: unlocking function address. This field is necessary only for finding insecure state storage vulnerabilities.
Run
python bootloadertaint.py config-file-path
Results will be stored in /tmp/BootloaderTaint_[boot-loader].out
, where [boot-loader]
is the name of the analyzed boot-loader. Note that paths involving loops might appear more than once.
Run
python unlock_checker.py config-file-path
Results will be stored in /tmp/UnlockChecker_[boot-loader].out
, where [boot-loader]
is the name of the analyzed boot-loader. Note that paths involving loops might appear more than once.
To check BootStomp results, use the script result_pretty_print.py
, as follows:
python result_pretty_print.py results_file
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