Ladin Nguyen's repositories
ThinkStats2
Text and supporting code for Think Stats, 2nd Edition
binaries
A repository with binaries for angr tests and examples.
Jupyter-Notebooks
This is repository for learning Python and Data science libraries, including machine learning, deep learning
volatility
An advanced memory forensics framework
driller
Driller: augmenting AFL with symbolic execution!
Beamer-Example
This is the first beamer presentation project
rules
Repository of yara rules
paramiko
The leading native Python SSHv2 protocol library.
jna
Java Native Access
open3mod
Open 3D Model Viewer - A quick and powerful 3D model viewer
awesome-malware-analysis
A curated list of awesome malware analysis tools and resources.
burp-suite-docs
burp-suite-docs
binnavi
BinNavi is a binary analysis IDE that allows to inspect, navigate, edit and annotate control flow graphs and call graphs of disassembled code.
GeneticAlgorithmsWithPython
source code from the book Genetic Algorithms with Python by Clinton Sheppard
Awesome-Fuzzing
A curated list of fuzzing resources ( Books, courses - free and paid, videos, tools, tutorials and vulnerable applications to practice on ) for learning Fuzzing and initial phases of Exploit Development like root cause analysis.
awesome-symbolic-execution
A curated list of awesome symbolic execution resources including essential research papers, lectures, videos, and tools.
tesseract
Tesseract Open Source OCR Engine (main repository)
pyodbc
Python ODBC bridge
schedule
Python job scheduling for humans.
tensorflow-generative-model-collections
Collection of generative models in Tensorflow
scapy
Scapy: the Python-based interactive packet manipulation program & library. Supports Python 2 & Python 3.
WPForce
Wordpress Attack Suite
tesseract-1
A .Net wrapper for tesseract-ocr
featuretools
automated feature engineering
pandas-profiling
Create HTML profiling reports from pandas DataFrame objects
jinja
The Jinja2 template engine
Tensorflow-Programs-and-Tutorials
Implementations of CNNs, RNNs, GANs, etc
algorithms
Minimal examples of data structures and algorithms in Python
data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.