HEAPSTER: Analyzing the Security of Dynamic Allocators for Monolithic Firmware Images

This repository contains all the code used in our S&P2022 paper “Heapster: Analyzing the Security of Dynamic Allocators for Monolithic Firmware Images”.
The system is able to identify a dynamic memory allocator used within a monolithic firmware image (ARMCortexM) and to test its security using symbolic execution and bounded model checking.
The project has been wrapped in a Docker container to facilitate the replicability of our findings, follow the instructions below to start to play with the analyses techniques and our datasets.

Additional resources related to the project:

• https://github.com/ucsb-seclab/heapster-dataset-metadata: a collection of metadata regarding the firmware images in our dataset (i.e., loading configurations and many different additional information like blob entry-point, base-address, recognized functions, etc…). If you need more, or support on how to use those, don’t hesitate to ping me.
• https://github.com/ucsb-seclab/monolithic-firmware-collection: a big collection of monolithic firmware images consolidated using previous research. Note that, Heapster dataset is a subset of that collection as the repo grew during time. You can find the exact list of tested blobs here. In this repo you can also find some utility I wrote to [1️⃣] automatically spot the IVT in a random blob, and, [2️⃣], automatically identify the entry-point/base-address of a blob using the algorithm presented in FirmXRay and reimplemented in angr.
• https://docs.google.com/spreadsheets/d/1e6GkfeSvBavg4e9e-mgUuTfPj4It9WYItkNG7xG1G2g/edit?usp=sharing: comprehensive metadata regarding our firmware clusterization and stats of the tool.

If you use HEAPSTER in a scientific publication, we would appreciate a citation using this Bibtex entry:

@inproceedings{gritti_heapster_22,
 author    = {Fabio Gritti and Fabio Pagani and Ilya Grishchenko and Lukas Dresel and Nilo Redini and Christopher Kruegel and Giovanni Vigna},
 booktitle = {In Proceedings of the IEEE Symposium on Security & Privacy (S&P)},
 month     = {May},
 title     = {HEAPSTER: Analyzing the Security of Dynamic Allocators for Monolithic Firmware Images},
 year      = {2022}
}

Happy Hacking!

SETUP ?

⚠️ For this project I had to pin the angr version, therefore, if you want to upgrade to a newer one, some work needs to be done to ensure compatibility.

1. Build the container:

   • cd ./heapster-env && docker build . -t heapster

2. Run the container:

   • docker run -ti heapster

3. Get some firmware to analyze!

   • You can either play with the ground_truth dataset included in the container at /root/fw-dataset/ground_truth, or,
     use the script /root/fw-dataset/wild/get-fw.py to download a specific firmware from the wild dataset, or, you can use /root/fw-dataset/get-all.py to download ALL the samples in the wild dataset.
     You can find a list of names of tested firmware (i.e., the 799 mentioned in the paper) in /root/fw-dataset/wild/fw-tested.txt, all these
     firmware are available at https://github.com/ucsb-seclab/monolithic-firmware-collection.

     Example to download a firmware sample: /root/fw-dataset/wild/get-fw.py https://github.com/ucsb-seclab/monolithic-firmware-collection/blob/master/ARMCortex-M/D_FIRMXRAYS/nordic/110_plc.bin@38da74c6d7a8252dc118e9fea6d02b1c?raw=true

4. Once you have a firmware image with its loading conf (i.e., conf.yaml, automatically downloaded by get-fw.py if you are using a tested firmware, otherwise, the script drops a template in the firmware folder and you are in charge of writing it) you are ready to start the HML Identification pipeline.

HML IDENTIFICATION ?

⚠️ For the following commands I assume the target firmware to be /root/fw-dataset/ground_truth/p2im_drone.bin.

⚠️ MAKE SURE you launch the following command from the absolute path /heapster/ within the container.

⚠️ The heuristics used by the different stages are tunable using the file at /heapster/heapster/heapster.ini within the container.

1. Load the firmware in angr:
   • python3 -m heapster.load_firmware.run --fw-conf /root/fw-dataset/ground_truth/p2im_drone.bin/conf.yaml /root/fw-dataset/ground_truth/p2im_drone.bin/p2im_drone.bin
   • The previous command is going to create an hb_analysis folder containing all the artifacts of the analysis and the metadata (hb_state.json)
2. Identify basic functions:
   • python3 -m heapster.identify_basic_functions.run --resume /root/fw-dataset/ground_truth/p2im_drone.bin/hb_analysis/hb_state.json --basic-function memcpy --basic-function memset --basic-function memcmp --basic-function strlen --basic-function strncat --basic-function strcat --basic-function strncpy
   • You can define new basic function if you wish (check the models inside the stage), or remove useless ones from the command line.
3. Identify pointer sources:
   • python3 -m heapster.identify_pointer_sources.run --resume /root/fw-dataset/ground_truth/p2im_drone.bin/hb_analysis/hb_state.json
   • Check the file ‘/heapster/fw-dataset/ground_truth/p2im_drone.bin/hb_analysis/hb_state.json’ for the results.
4. Identify allocator:
   • ⚠️ we are going to skip the execution of the ResetHandler for this example (i.e., –skip-entry-point).
   • python3 -m heapster.identify_allocator.run --resume /root/fw-dataset/ground_truth/p2im_drone.bin/hb_analysis/hb_state.json --skip-entry-point
   • Check the file ‘/heapster/fw-dataset/ground_truth/p2im_drone.bin/hb_analysis/hb_state.json’ for the results.
5. Identify deallocator:
   • python3 -m heapster.identify_deallocator.run --resume /root/fw-dataset/ground_truth/p2im_drone.bin/hb_analysis/hb_state.json
   • Check the file ‘/heapster/fw-dataset/ground_truth/p2im_drone.bin/hb_analysis/hb_state.json’ for the results.
6. Analyze HML prototype:
   • python3 -m heapster.identify_hml_prototype.run --resume /root/fw-dataset/ground_truth/p2im_drone.bin/hb_analysis/hb_state.json
   • Check the file ‘/heapster/fw-dataset/ground_truth/p2im_drone.bin/hb_analysis/hb_state.json’ for the results.
7. Identify hotspots:
   • python3 -m heapster.identify_hotspots.run --resume /root/fw-dataset/ground_truth/p2im_drone.bin/hb_analysis/hb_state.json
   • Check the file ‘/heapster/fw-dataset/ground_truth/p2im_drone.bin/hb_analysis/hb_state.json’ for the results.
8. Identify HML properties:
   • python3 -m heapster.identify_hml_properties.run --resume /root/fw-dataset/ground_truth/p2im_drone.bin/hb_analysis/hb_state.json
   • Check the file ‘/heapster/fw-dataset/ground_truth/p2im_drone.bin/hb_analysis/hb_state.json’ for the results.

HML SECURITY TESTING ?

1. Generate the configuration that is going to be used by HeapHopper
   • python3 /root/heapster/heapster/scripts/create_fw_hh_config_template.py /root/fw-dataset/ground_truth/p2im_drone.bin/p2im_drone.bin
2. Create the PoCs we are going to trace! (pocs are created in /root/heaphopper_analyses)
   • python3 /root/heapster/heapster/scripts/pocs_creator.py /root/fw-dataset/ground_truth/p2im_drone.bin/p2im_drone.bin p2im_drone.bin
3. Trace a PoC with HeapHopper
   • python3 /root/heapster/heaphopper/heaphopper_client.py trace -c /root/heapster/heaphopper_analyses/p2im_drone.bin/p2im_drone.bin_fake_free_3/analysis_bad_alloc.yaml -b /root/heapster/heaphopper_analyses/p2im_drone.bin/p2im_drone.bin_fake_free_3/zoo_dir/bin/2.bin
4. If HeapHopper found a vuln, you need to concretize it using the results of the analysis
   • python3 /root/heapster/heaphopper/heaphopper_client.py poc -c /root/heapster/heaphopper_analyses/p2im_drone.bin/p2im_drone.bin_fake_free_3/analysis_bad_alloc.yaml -r /root/heapster/heaphopper_analyses/p2im_drone.bin/p2im_drone.bin_fake_free_3/zoo_dir/bin/2.bin-result.yaml -d /root/heapster/heaphopper_analyses/p2im_drone.bin/p2im_drone.bin_fake_free_3/zoo_dir/bin/2.bin-desc.yaml -s /root/heapster/heaphopper_analyses/p2im_drone.bin/p2im_drone.bin_fake_free_3/zoo_dir/2.c -b /root/heapster/heaphopper_analyses/p2im_drone.bin/p2im_drone.bin_fake_free_3/zoo_dir/bin/2.bin
5. Compile the PoV
   • cd /root/heapster/heaphopper_analyses/p2im_drone.bin/p2im_drone.bin_fake_free_3/pocs/malloc_non_heap/2.bin && make
6. You may want to verify if a PoV is a false positive or not with the following command (step 12 of the pipeline in the overview)
   • cd /root/heapster && python3 -m heapster.verify_pov.run --resume /root/fw-dataset/ground_truth/p2im_drone.bin/hb_analysis/hb_state.json --analysis-conf /root/heapster/heaphopper_analyses/p2im_drone.bin/p2im_drone.bin_fake_free_3/analysis_bad_alloc.yaml --pov /root/heapster/heaphopper_analyses/p2im_drone.bin/p2im_drone.bin_fake_free_3/pocs/malloc_non_heap/2.bin/bin/poc_0_0.bin (this keeps the hooks possibly installed by the hotspots detection analysis)
   • cd /root/heapster && python3 -m heapster.verify_pov.run --resume /root/fw-dataset/ground_truth/p2im_drone.bin/hb_analysis/hb_state.json --no-hooks --analysis-conf /root/heapster/heaphopper_analyses/p2im_drone.bin/p2im_drone.bin_fake_free_3/analysis_bad_alloc.yaml --pov /root/heapster/heaphopper_analyses/p2im_drone.bin/p2im_drone.bin_fake_free_3/pocs/malloc_non_heap/2.bin/bin/poc_0_0.bin (this removes the hooks possibly installed by the hotspots detection analysis)

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