This is a repository that is meant to hold detections for various process injection techniques.
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Data analytics written within Jupyter Notebooks can be found within the
Detection_Notebooks
folder. -
Datasets of each technique can be found within the respective folders.
- DLL Injection (CreateRemoteThread & RtlCreateUserThread)
- Reflective DLL Injection
- Process Hollowing
- Process Reimaging (not necessarily injection, but still useful)
- Hook Injection via SetWindowsHookEx
POC's:
- https://github.com/theevilbit/injection
- https://github.com/secrary/InjectProc
- https://github.com/djhohnstein/ProcessReimaging
- psinject empire dataset
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You can read from the json file directly from within the notebooks (see Raw notebooks for an example).
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You can ingest the datasets into your ELK stack by utilziing
kafkacat
. Follow these steps:-
Untar the dataset of choice:
tar -xzvf dataset.tar.gz
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Use kafkacat to send dataset to Kafka broker:
kafkacat -b <HELK IP>:9092 -t winlogbeat -P -l dataset.json
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