Search Results for "sec"
Sort By:
Showing 102 open source projects for "sec"
View related business solutions-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
-
1
Sec-Context
AI Code Security Anti-Patterns distilled from 150+ sources
Sec-Context is a curated security research project that distills common code anti-patterns and vulnerabilities that generative AI tends to produce, presenting them as a comprehensive set of examples and secure alternatives that can be used to train or guide AI assistants and reviewers toward safer code generation. It compiles insights from over 150 industry and academic sources into structured reference documents that outline real-world security problems such as hardcoded secrets, SQL injection, cross-site scripting, command injection, weak password storage, and other frequent issues that occur when code is auto-generated without context of best practices. ... -
2
HTML5 Security Cheatsheet
A collection of HTML5 related XSS attack vectors
H5SC, or the HTML5 Security Cheatsheet, is a public reference collection for researching browser-based cross-site scripting behavior. It catalogs HTML5-related XSS vectors so security professionals can compare how markup, browser features, and parsing behavior affect injection risks. The repository also includes supporting files intended for controlled XSS testing. A collection of lesser-known browser behaviors helps researchers investigate edge cases that ordinary checklists may miss.... -
3
Sealed Secrets for Kubernetes
A Kubernetes controller and tool for one-way encrypted Secrets
Sealed Secrets provides declarative Kubernetes Secret Management in a secure way. Since the Sealed Secrets are encrypted, they can be safely stored in a code repository. This enables an easy-to-implement GitOps flow that is very popular among the OSS community. Sealed Secrets offers a powerful CLI tool (kubeseal) to one-way encrypt your Kubernetes Secret easily. The Sealed Secrets controller will decrypt any Sealed Secret into its equivalent Kubernetes Secret. Sealed Secrets are safe to... -
4
ParrotOS 7-Cyber-Sec & ProtonCyber-Sec
TN365 Cyber‑Sec Editions - 2 Secure Linux OS Distros !
ProtonCyber-Sec & TN365 Cyber‑Sec Edition (Debian 13 Trixie KDE) very stable 2 Distros 2 Concepts , Try and Choose your Flavor . TN365 gives you 2 differents approchs with 2 professional Linux distributions focused on cybersecurity, privacy, and local AI. TN365 Cyber‑Sec Edition is built on Debian 13 KDE, offering a stable, secure, and modern environment designed for cybersecurity professionals, developers, sysadmins, and privacy‑focused users. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
5
Snappy
A fast compressor/decompressor
...For instance, compared to the fastest mode of zlib, Snappy is an order of magnitude faster for most inputs, but the resulting compressed files are anywhere from 20% to 100% bigger. Snappy is intended to be fast. On a single core of a Core i7 processor in 64-bit mode, it compresses at about 250 MB/sec or more and decompresses at about 500 MB/sec or more. (These numbers are for the slowest inputs in our benchmark suite; others are much faster.) In our tests, Snappy usually is faster than algorithms in the same class (e.g. LZO, LZF, QuickLZ, etc.) while achieving comparable compression ratios. -
6
AWS Secrets Manager Python caching
Enables in-process caching of secrets for Python applications
The AWS Secrets Manager Python caching client enables in-process caching of secrets for Python applications. To use this client you must have Python 3.6 or newer. Use of Python versions 3.5 or older are not supported. An Amazon Web Services (AWS) account to access secrets stored in AWS Secrets Manager. To create an AWS account, go to Sign In or Create an AWS Account and then choose I am a new user. Follow the instructions to create an AWS account. To create a secret in AWS Secrets Manager,... -
7
Colly
Elegant Scraper and Crawler Framework for Golang
...With Colly you can easily extract structured data from websites, which can be used for a wide range of applications, like data mining, data processing or archiving. Clean API. Fast (>1k request/sec on a single core) Manages request delays and maximum concurrency per domain. Automatic cookie and session handling. Sync/async/parallel scraping. Distributed scraping. Caching, automatic encoding of non-unicode responses. Robots.txt support. Google App Engine support. -
8
Ligolo-ng
An advanced, yet simple, tunneling/pivoting tool
...You need to download the Wintun driver (used by WireGuard) and place the wintun.dll in the same folder as Ligolo. You can listen to ports on the agent and redirect connections to your control/proxy server. You can easily hit more than 100 Mbits/sec. Here is a test using iperf from a 200Mbits/s server to a 200Mbits/s connection. -
9
AWS Secrets Manager Go Caching Client
Enables in-process caching of secrets for Go applications
The AWS Secrets Manager Go caching client enables in-process caching of secrets for Go applications. To use this client you must have a Go development environment. If you do not have one, go to Golang Getting Started on The Go Programming Language website, then download and install Go. An Amazon Web Services (AWS) account to access secrets stored in AWS Secrets Manager and use AWS SDK for Go. To create an AWS account, go to Sign In or Create an AWS Account and then choose I am a new user.... -
Build Data Resilience - Take the Assessment TodayIs your recovery strategy as strong as you think? Take this quick self-assessment to check your recovery readiness and gain tailored insights. In only 2 minutes, you'll learn where you fall on the recovery readiness scale.
-
10
AWS Secrets Manager Java caching client
Enables in-process caching of secrets for Java applications
The AWS Secrets Manager Java caching client enables in-process caching of secrets for Java applications. To use this client you must have a Java 8 development environment. If you do not have one, go to Java SE Downloads on the Oracle website, then download and install the Java SE Development Kit (JDK). Java 8 or higher is recommended. An Amazon Web Services (AWS) account to access secrets stored in AWS Secrets Manager and use AWS SDK for Java. To create an AWS account, go to Sign In or... -
11
AWS Secrets Manager Caching Client .NET
Enables in-process caching of secrets for C# applications
The AWS Secrets Manager .NET caching client enables in-process caching of secrets for C# applications. The AWS Secrets Manager caching client enables in-process caching of secrets for .NET applications. To use this client, you must have a .NET project with one of the following, .NET Framework 4.6.1 or higher, .NET Standard 2.0 or higher, and An Amazon Web Services (AWS) account to access secrets stored in AWS Secrets Manager and use AWS SDK for .NET. To create an AWS account, go to Sign In... -
12
-
13
OpenBB
Investment Research for Everyone, Everywhere
Customize and speed up your analysis, bring your own data, and create instant reports to gain a competitive edge. Whether it’s a CSV file, a private endpoint, an RSS feed, or even embed an SEC filing directly. Chat with financial data using large language models. Don’t waste time reading, create summaries in seconds and ask how that impacts investments. Create your dashboard with your favorite widgets. Create charts directly from raw data in seconds. Create charts directly from raw data in seconds. Customize your dashboards to build your dream terminal, integrate with your private datasets and bring your own fine-tuned AI copilots. -
14
Akka
Build concurrent, distributed, and resilient message-driven apps
...Building on the principles of The Reactive Manifesto Akka allows you to write systems that self-heal and stay responsive in the face of failures. Up to 50 million msg/sec on a single machine. Small memory footprint; ~2.5 million actors per GB of heap. Distributed systems without single points of failure. Load balancing and adaptive routing across nodes. Event Sourcing and CQRS with Cluster Sharding. Distributed Data for eventual consistency using CRDTs. Asynchronous non-blocking stream processing with backpressure. -
15
ML for Trading
Code for machine learning for algorithmic trading, 2nd edition
...Covers key aspects of data sourcing, financial feature engineering, and portfolio management. The design and evaluation of long-short strategies based on a broad range of ML algorithms, how to extract tradeable signals from financial text data like SEC filings, earnings call transcripts or financial news. Using deep learning models like CNN and RNN with financial and alternative data, and how to generate synthetic data with Generative Adversarial Networks, as well as training a trading agent using deep reinforcement learning. -
16
proxy.py
Utilize all available CPU cores for accepting new client connections
proxy.py is made with performance in mind. By default, proxy.py will try to utilize all available CPU cores to it for accepting new client connections. This is achieved by starting AcceptorPool which listens on configured server port. Then, AcceptorPool starts Acceptor processes (--num-acceptors) to accept incoming client connections. Alongside, if --threadless is enabled, ThreadlessPool is setup which starts Threadless processes (--num-workers) to handle the incoming client connections.... -
17
Kraken
P2P Docker registry capable of distributing TBs of data in seconds
...In our busiest cluster, Kraken distributes more than 1 million blobs per day, including 100k 1G+ blobs. At its peak production load, Kraken distributes 20K 100MB-1G blobs in under 30 sec. Kraken is capable of distributing Docker images at > 50% of max download the speed limit on every host. Cluster size and image size do not have a significant impact on download speed. Support uploader authentication and data integrity protection through TLS. Other than pluggable storage, Kraken only has an optional dependency on DNS. -
18
etcd
Distributed reliable key-value store for the most critical data
A distributed, reliable key-value store for the most critical data of a distributed system. etcd is a strongly consistent, distributed key-value store that provides a reliable way to store data that needs to be accessed by a distributed system or cluster of machines. It gracefully handles leader elections during network partitions and can tolerate machine failure, even in the leader node. etcd is a consistent distributed key-value store. Mainly used as a separate coordination service, in... -
19
formidable
The most used, flexible, fast and streaming parser
The most used, flexible, fast and streaming parser for multipart form data. Supports uploading to serverless environments, AWS S3, Azure, GCP or the filesystem. Used in production. This project is semantically versioned and available as part of the Tidelift Subscription for professional-grade assurances, enhanced support and security. The maintainers of formidable and thousands of other packages are working with Tidelift to deliver commercial support and maintenance for the Open Source... -
20
Ring
Ring is a reasoning MoE LLM provided and open-sourced by InclusionAI
Ring is a reasoning Mixture-of-Experts (MoE) large language model (LLM) developed by inclusionAI. It is built from or derived from Ling. Its design emphasizes reasoning, efficiency, and modular expert activation. In its “flash” variant (Ring-flash-2.0), it optimizes inference by activating only a subset of experts. It applies reinforcement learning/reasoning optimization techniques. Its architectures and training approaches are tuned to enable efficient and capable reasoning performance.... -
21
HTTP Kit
Clojure HTTP server/client library with WebSocket support
...So you can use it with all your current libraries (e.g. Compojure) and middleware. Using an event-driven architecture like Nginx, HTTP-kit is very, very fast. It comfortably handles tens of thousands of requests/sec on even midrange hardware. Here is another test about how it stacks up with others. It's not only fast, but efficient! Each connection costs nothing but a few kB of memory. RAM usage grows O(n) with connections. Written from the ground-up to be lean, the entire client/server is available as a single ~90kB JAR with zero dependencies and ~3k lines of (mostly Java) code. ... -
22
inoscope
Arduino & STM32 Nucleo-based oscilloscope
Arduino & STM32 Nucleo-based dual-trace oscilloscope (200 ksamp/sec on Arduino Uno/ATmega328P and 2 Msamp/sec on Nucleo-F411RE) -
23
Prime number ( primenumbers )
Benchmark for 50 000 000 prime numbers as single and multicore
...(PS: C++ multicore 6 second). Added C files for gcc compiler in Windows 10 and for Xcode C command line project in MacOS ( tested on Mac mini M2 with single core 16 to 25 sec and multicore 2,3 to 5 second by compiler -O switch). Surprise, same code in JavaScript for M2 chip in Safari: 12,5 sec single core and 3,3 sec multi core. Python version with numba and numpy on MacOS with M2: 3,78 sec, Intel Ultra 5 225F Linux Fedora 43 GNOME(*Intel): 3,64 sec., W11Intel: 3,73; Faster style in python, MacOS M2: 1,81 sec, *Intel & W11Intel: 2,02 sec.; Ultra faster style in python, MacOS M2: 1,24 s - 1,26 s - 1,34 s, *Intel: 1,48 s - 1,50 s, W11Intel: 1,53 - 1,63. -
24
ThinkValue
Analyze stocks clearly without spending hours modeling
ThinkValue helps you analyze US stocks with clear DCF valuation models and SEC-sourced financial data. Build single or multi-stage valuations, run reverse DCFs, and test scenarios with sensitivity analysis. Use structured SEC financials via a free API, generate automated spreadsheets, and access research and KPIs on the web platform. Start free with no login or upgrade for versioned API access and integration support. -
25
BioXTAS RAW
Processing and analysis of Small Angle X-ray Scattering (SAXS) data.
...The software enables: creation of 1D scattering profiles from 2D detector images, standard data operations such as averaging and subtraction, analysis of radius of gyration (Rg) and molecular weight, and advanced analysis using GNOM and DAMMIF as well as electron density reconstructions using DENSS. It also allows easy processing of inline SEC-SAXS data and data deconvolution using the evolving factor analysis (EFA) or the regularized alternating least squares (REGALS) methods. Active source code is now maintained on github: https://github.com/jbhopkins/bioxtasraw To install: Check the instructions available at: http://bioxtas-raw.readthedocs.io/en/latest/install.html and in the Files tab. ...
