Search Results for "network security toolkit"
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Showing 14 open source projects for "network security toolkit"
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1
Python Outlier Detection
A Python toolbox for scalable outlier detection
...PyOD has multiple neural network-based models, e.g., AutoEncoders, which are implemented in both PyTorch and Tensorflow. PyOD contains multiple models that also exist in scikit-learn. It is possible to train and predict with a large number of detection models in PyOD by leveraging SUOD framework. A benchmark is supplied for select algorithms to provide an overview of the implemented models. -
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Impacket
A collection of Python classes for working with network protocols
Impacket is a collection of Python classes designed for working with network protocols. It was primarily created in the hopes of alleviating some of the hindrances associated with the implementation of networking protocols and stacks, and aims to speed up research and educational activities. It provides low-level programmatic access to packets, and the protocol implementation itself for some of the protocols, like SMB1-3 and MSRPC. It features several protocols, including Ethernet, IP, TCP,... -
3
Penzai
A JAX research toolkit to build, edit, & visualize neural networks
Penzai, developed by Google DeepMind, is a JAX-based library for representing, visualizing, and manipulating neural network models as functional pytree data structures. It is designed to make machine learning research more interpretable and interactive, particularly for tasks like model surgery, ablation studies, architecture debugging, and interpretability research. Unlike conventional neural network libraries, Penzai exposes the full internal structure of models, enabling fine-grained... -
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Terraform Examples and Modules for GC
End-to-end modular samples and landing zones toolkit for Terraform
Terraform Examples and Modules for GC is a comprehensive infrastructure-as-code toolkit built on Terraform that enables organizations to design, deploy, and manage enterprise-grade Google Cloud environments using modular and reusable components. It provides a collection of end-to-end blueprints and composable modules that allow teams to implement standardized cloud architectures such as landing zones, networking configurations, and security frameworks. -
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5
Stanza
Stanford NLP Python library for many human languages
...It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of speech and morphological features, to give a syntactic structure dependency parse, and to recognize named entities. The toolkit is designed to be parallel among more than 70 languages, using the Universal Dependencies formalism. Stanza is built with highly accurate neural network components that also enable efficient training and evaluation with your own annotated data. -
6
FairChem
FAIR Chemistry's library of machine learning methods for chemistry
FAIRChem is a unified library for machine learning in chemistry and materials, consolidating data, pretrained models, demos, and application code into a single, versioned toolkit. Version 2 modernizes the stack with a cleaner core package and breaking changes relative to V1, focusing on simpler installs and a stable API surface for production and research. The centerpiece models (e.g., UMA variants) plug directly into the ASE ecosystem via a FAIRChem calculator, so users can run relaxations, molecular dynamics, spin-state energetics, and surface catalysis workflows with the same pretrained network by switching a task flag. ... -
7
AIMET
AIMET is a library that provides advanced quantization and compression
Qualcomm Innovation Center (QuIC) is at the forefront of enabling low-power inference at the edge through its pioneering model-efficiency research. QuIC has a mission to help migrate the ecosystem toward fixed-point inference. With this goal, QuIC presents the AI Model Efficiency Toolkit (AIMET) - a library that provides advanced quantization and compression techniques for trained neural network models. AIMET enables neural networks to run more efficiently on fixed-point AI hardware accelerators. Quantized inference is significantly faster than floating point inference. For example, models that we’ve run on the Qualcomm® Hexagon™ DSP rather than on the Qualcomm® Kryo™ CPU have resulted in a 5x to 15x speedup. ... -
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Neural Network Intelligence
AutoML toolkit for automate machine learning lifecycle
Neural Network Intelligence is an open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate feature engineering, neural architecture search, hyperparameter tuning and model compression. -
9
flom
Free Lock Manager
...When used in a shell environment, FLoM manages process synchronization in the same way that "nice" manages process prioritization. Shell commands, scripts and custom programs can be synchronized inside a single system or in a network of IP connected systems. FLoM supports different types of abstract resources: simple, numeric, set, hierarchical and transactional sequence. libflom, the library shipped with FLoM, allows you to develop your own application using a simple C, C++, Java, Perl, PHP or Python client API. SSL/TLS security for network communication, X.509 certificates for peer to peer mutual authentication. -
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10
Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. -
11
Hack-Tools
Hack tools
hack-tools is a collection of various hacking tools and utilities. It serves as a comprehensive toolkit for penetration testers and cybersecurity enthusiasts, encompassing a wide range of functionalities. -
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vsResolver
DNS Validating Stub Resolver
The Validating Stub Resolver (vsResolver) is a DNS stub resolver that implements the Domain Name System Security Extensions (DNSSEC) specified in RFC 4033, RFC 4034 and RFC 4035. These add data origin authentication and data integrity to the Domain Name System. vsResolver extends the dnspython toolkit (http://www.dnspython.org/) and uses the pycrypto library for its underlying crypto implementation(https://www.dlitz.net/software/pycrypto/). -
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RegistryFilterExample
Registry Filter Driver SDK
The EaseFilter Registry Filter Driver SDK is a powerful, kernel-mode development toolkit designed to help developers monitor, control, and protect Windows registry operations in real time. It enables the development of robust security, compliance, and system integrity solutions by intercepting and managing registry access before it reaches the Windows registry subsystem. The SDK allows your application to receive notifications before any registry operation is processed by the Windows Configuration Manager. ... -
14
FileMonitorExample
EaseFilter File Monitor Filter Driver SDK
A file system filter driver intercepts requests directed at a file system or another filter driver. By capturing these requests before they reach their intended targets, the filter driver can extend or modify the functionality provided by the original target. Windows offers file system filtering services through the Filter Manager, which provides a framework for developing file systems and filter drivers without delving into the complexities of file I/O operations. EaseFilter Filter...
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