Torch
Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation. The goal of Torch is to have maximum flexibility and speed in building your scientific algorithms while making the process extremely simple. Torch comes with a large ecosystem of community-driven packages in machine learning, computer vision, signal processing, parallel processing, image, video, audio and networking among others, and builds on top of the Lua community. At the heart of Torch are the popular neural network and optimization libraries which are simple to use, while having maximum flexibility in implementing complex neural network topologies. You can build arbitrary graphs of neural networks, and parallelize them over CPUs and GPUs in an efficient manner.
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Chainer
A powerful, flexible, and intuitive framework for neural networks. Chainer supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort. Chainer supports various network architectures including feed-forward nets, convnets, recurrent nets and recursive nets. It also supports per-batch architectures. Forward computation can include any control flow statements of Python without lacking the ability of backpropagation. It makes code intuitive and easy to debug. Comes with ChainerRLA, a library that implements various state-of-the-art deep reinforcement algorithms. Also, with ChainerCVA, a collection of tools to train and run neural networks for computer vision tasks. Chainer supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort.
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DarkOwl
We are the industry’s leading provider of darknet data, offering the largest commercially available database of darknet content in the world. DarkOwl offers a suite of data products designed to meet the needs of business looking to quantify risk and understand their threat attack surface by leveraging darknet intelligence. DarkOwl Vision UI and API products make our data easy to access in your browser, native environment or customer-facing platform. Darknet data is a proven driver of business success for use cases spanning beyond threat intelligence and investigations. DarkOwl API products allow cyber insurance underwriters and third party risk assessors to utilize discrete data points from the darknet and incorporate them into scalable business models that accelerate revenue growth.
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Threat Landscape
Threat Landscape is an automated threat intelligence platform built for security analysts and SOC teams who need high-confidence, actionable intelligence — without the manual triage.
The platform continuously ingests and processes global OSINT and darknet sources, automatically extracting structured facts and filtering out noise before it reaches analysts. All intelligence is normalized into STIX 2.1 format, MITRE ATT&CK mapped, and correlated across threat actors, malware families, CVEs, TTPs, and IOCs — so teams spend time acting on intelligence, not building it.
Key capabilities include interactive dashboards, visualized STIX threat graphs, advanced search and filtering, darknet monitoring for leak-site claims and criminal chatter, automated daily and weekly digests, and a RESTful API for integration with SIEM, SOAR, and TIP platforms.
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