Botacin's Lab
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mlsec-comp-platform
mlsec-comp-platform PublicMLSEC 2.0 is a containerized, web-hosted platform for hosting adversarial malware competitions. MLSEC 2.0 offers a user portal where competitors can submit security artifacts to be automatically va…
Python 4
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SDhash_Python
SDhash_Python Publicjc_sdhash is a simple Python wrapper for SDHash that lets you generate, compare, and validate SDBF hashes directly from Python on Linux. Ideal for malware analysis, digital forensics, and fuzzy has…
Python 3
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malware-classification-web-ui
malware-classification-web-ui PublicImplementing a web ui similar to the paper https://www.usenix.org/conference/usenixsecurity23/presentation/aonzo
Python
Repositories
- mlsec-comp-platform Public
MLSEC 2.0 is a containerized, web-hosted platform for hosting adversarial malware competitions. MLSEC 2.0 offers a user portal where competitors can submit security artifacts to be automatically validated, evaluated, and scored against their peers.
- AutoPYaraPyPI Public
- EchoCrypt Public
The implementation of "Making Acoustic Side-Channel Attacks on Noisy Keyboards Viable with LLM-Assisted Spectrograms' ``Typo'' Correction" for WOOT'25: 19th USENIX WOOT Conference on Offensive Technologies
- auto-installer Public
When dealing with malware/benign files in MS Windows, most of them are installers and to access the actual binary someone has to install the exe files on a VM. With advance of VLMs, I believe this boring process can be automated.
- csce413_assignment2 Public
- replay_attack_demo Public
Educational demonstration of replay attacks and prevention techniques using Python/Flask. Shows vulnerable vs. secure server implementations with timestamp and nonce-based protection. For software security coursework.
- malware-classification-web-ui Public
Implementing a web ui similar to the paper https://www.usenix.org/conference/usenixsecurity23/presentation/aonzo
- Concept.Drift.Explanation Public
- SDhash_Python Public
jc_sdhash is a simple Python wrapper for SDHash that lets you generate, compare, and validate SDBF hashes directly from Python on Linux. Ideal for malware analysis, digital forensics, and fuzzy hashing workflows.
- SDHash Public
Modified SDHash for malware analysis, featuring optimized similarity hashing and scalable binary comparison for forensic and security research workflows.
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