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Products that do what Get a report on your compliance to CIS Benchmarks (Azure and AWS) does
Easy to run script that allow you to have a report on your compliance to CIS Benchmarks rules. Get the YAML rules from the repository, run the script, and get your results by SMS, Email, Teams, or simply by reading the logs. Currently available for AWS & Azure CIS Benchmarks, else you can check the rules folder in the repository to find rules you want to apply for the next report !
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Video compliance review powered by rules you control
16d ago · twelvelabs.io
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Benchi is a CLI tool for running benchmarks and collecting metrics. It's using Docker Compose to orchestrate the infrastructure and tools being benchmarked, making it repeatable and runnable on different machines. It allows you to run the same benchmark for different tools and compare the collected results. The repository contains a simple example. For a more elaborate example see how we use Benchi to compare data pipelines running on Conduit and Kafka Connect, two data streaming tools (still work in progress): https://github.com/ConduitIO/streaming-benchmarks
2025 · github.com
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Hey HN! I’m the founder of Unify, and we’ve just released our Model Hub, which provides a collection of LLM endpoints with live runtime benchmarks all plotted across time: https://unify.ai/hub A key finding is that static tabular runtime benchmarks for LLMs simply do not work. It’s necessary to take a time-series perspective, and plot the variations through time. We currently have 21 models provided by: Anyscale, Perplexity AI, Replicate, Together AI, OctoAI, Mistral AI and OpenAI, with more on the roadmap. We test across different regions (Asia, US, Europe), with varied…
2024
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I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…
2025 · llmapitest.com
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I built a tool called *Kekkai* for file integrity monitoring in production environments. It records file hashes during deployment and later verifies them to detect unauthorized modifications (e.g. from OS command injection or tampering). Why it matters: * Many web apps (PHP, Ruby, Python, etc.) on AWS EC2 need a lightweight way to confirm their code hasn’t been changed. * Traditional approaches that rely on metadata often create false positives. * Kekkai checks only file content, so it reliably detects real changes. * I’ve deployed it to an EC2 PHP application in production, and it’s working…
Sep 2025 · github.com
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We now write most of our code with agents. For a while, PRs piled up, causing review fatigue, and we had this sinking feeling that standards were slipping. Consistency is tough at this volume. I’m sharing the solution we found, which has become our main product. Continue (https://docs.continue.dev) runs AI checks on every PR. Each check is a source-controlled markdown file in `.continue/checks/` that shows up as a GitHub status check. They run as full agents, not just reading the diff, but able to read/write files, run bash commands, and use a browser. If it finds…
Feb 2026 · docs.continue.dev
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This is a small PoC Python project for web server access logs analyzing to classify and dynamically block bad bots, such as L7 (application-level) DDoS bots, web scrappers and so on. We'll be happy to gather initial feedback on usability and features, especialy from people having good or bad experience wit bots. *Requirements* The analyzer relies on 3 Tempesta FW specific features which you still can get with other HTTP servers or accelerators: 1. JA5 client fingerprinting (https://tempesta-tech.com/knowledge-base/Traffic-Filtering-b...). This is a HTTP and TLS layers…
Oct 2025 · github.com
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If you had to build a context window manager in 24h, would you stick to the existing model or come up with something better? Here's what I did: 1. Built a proxy that intercepts Codex's calls to OpenAI and rewrites them on the fly. 2. Replayed 3,807 rounds of SWE-bench Verified traces through it: avg prompt 44k → 6k tokens (-87%). 3. Posted it to HN to get the next reduction applied to my confidence interval — starting with the inevitable "How about accuracy?" npx -y pando-proxy · github.com/human-software-us/pando-proxy
Apr 2026 · npmjs.com
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Compliance shouldn't cost you your data.
Jul 2026 · locklistsecurity.com
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We've been trying to evaluate web scraping companies, but when you look at their benchmarks, you can't verify anything, and they mostly exist to prove the company is successful. They put somewhere between 98% and 100% because they pick their own urls, define success their own way, and don't publish the harness. We also saw companies like scrapfly astroturf websites like scrapeway and call them independent. So, we built an open source benchmark that we want to represent the frontier of web data. We're trying to look across all major anti-bot providers and industries, to build a comprehensive…
Jul 2026 · github.com
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2021 · beta.rocketcompute.com
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Analyses your QHSE documents, and draft new ones
Feb 2026 · questtor.com
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Hello, I'm Patrick SZYMOWIAK and I'm happy to introduce you to Kexa, a script that will optimize your operations, easily ensure compliance and save you money through your cloud providers. I've worked in cloud solutions with Azure for 8 years and came up with a few projects by now, and today I introduce you the new solution made by us for your cloud environments. The goal : Kexa is an open-source and portable software built to simplify and enhance the cloud verification process. It's designed to support various cloud providers. It operates on a set of user-defined rules, ensuring checks and…
2023 · github.com
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