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@ilobe started using tool Python , 1 month, 1 week ago.
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@ek121268 shared a link, 1 month, 1 week ago
VP of Product Marketing, http://checkmarx.com

Securing the Museum of Software in an AI Coding Tsunami

In Securing the Museum of Software in an AI Coding Tsunami, Eran Kinsbruner argues that software now consists of legacy, modern, and rapidly AI-generated code, creating unprecedented complexity and risk. Traditional AppSec can’t keep up with machine-speed development. He calls for a unified, developer-first, agentic AppSec platform that embeds security into coding workflows to prevent, fix, and secure all code eras before vulnerabilities reach repositories.

ChatGPT Image Nov 21, 2025, 09_43_10 AM
Story FAUN.dev() Team Trending
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Founder, FAUN.dev

100 GitHub Projects That Defined 2025: A Community-Driven Ranking

This article ranks the 100 developer tools developers acted on most in 2025, based on real interaction data from across FAUN·dev() ecosystem.

100 GitHub Projects That Defined 2025
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@laura_garcia shared a post, 1 month, 1 week ago
Software Developer, RELIANOID

🔐🌱 Cybersecurity and industrial sustainability: a moment to reflect as the year comes to an end

We shared this article a few months ago, but year-end is the perfect time to revisit it and reflect on where the industry is heading in the year ahead. Cybersecurity and sustainability can no longer be treated as separate disciplines. They share a common goal: ensuring ethical, resilient, and respon..

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@eon01 shared a post, 1 month, 2 weeks ago
Founder, FAUN.dev

Enshittification is not a bug

Docker Helm Kubernetes

Bitnami charts are still high quality, but their public image distribution is going away. Instead of rewriting everything, many teams can keep the charts and switch the underlying images (for example, to Docker Hardened Images) to minimize disruption and maintain security.

Bitnami vs Docker Hardened Images
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@laura_garcia shared a post, 1 month, 2 weeks ago
Software Developer, RELIANOID

🚀 Deploy RELIANOID CE v7 on AWS with Terraform

Quickly deploy RELIANOID Community Edition v7 on AWS using the official Terraform module. ✔️ VPC, Subnet & Security Group ✔️ EC2 with RELIANOID AMI ✔️ SSH & Web GUI ready ✔️ Easy cleanup with terraform destroy ⚠️ AMI is region-specific (default: us-east-1) 🔐 Always secure your SSH private key #Terra..

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@viktoriiagolovtseva shared a post, 1 month, 2 weeks ago

How To Create a Jira Test Case Template To Boost Efficiency

Many agile teams prefer Jira for managing test cases. Even though it’s not a dedicated tool, it provides a straightforward way to organize the testing process, track progress, and share results with stakeholders. Additionally, it enhances collaboration between QA and development teams.

Using test case templates in Jira allows you to manage this process even more efficiently. These templates save time, promote standardization, and provide a structured foundation for test execution. In this short tutorial, I will show you how to create a Jira test case template and use it with automation to simplify your testing process.

Zrzut ekranu 2025-12-23 155342
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@laura_garcia shared a post, 1 month, 2 weeks ago
Software Developer, RELIANOID

🔐 RELIANOID & NIST Cybersecurity Framework Alignment

At RELIANOID, security is built into both our Load Balancer and our internal operations. We align our product and organizational practices with the NIST Cybersecurity Framework (CSF) across its five core functions: Identify, Protect, Detect, Respond, and Recover. ✔️ Consistent security controls acro..

NIST Cybersecurity Framework RELIANOID compliance
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FAUN.dev()

Goodbye Microservices

Twilio Segment collapsed 140+ destination-specific microservices into asingle monolith, one repo, one set of dependencies, one test harness. They leveled out version sprawl and builtTraffic Recorder, a homegrown yakbak-based HTTP playback tool. That killed off hours-long test runs, dropping them to.. read more  

GPT-5.3-Codex is OpenAI’s advanced agentic coding model, designed to go beyond writing code and operate as a general-purpose collaborator on a computer. It builds on GPT-5.2-Codex by combining stronger coding performance with improved reasoning and professional knowledge, while running about 25% faster. The model is optimized for long-running tasks that involve research, tool use, and complex execution, and it performs at the top of industry benchmarks such as SWE-Bench Pro and Terminal-Bench.

Unlike earlier Codex models that focused primarily on code generation and review, GPT-5.3-Codex can reason, plan, and act across the full software lifecycle. It supports activities such as debugging, deploying, monitoring, writing product requirement documents, creating tests, and analyzing metrics. It can also autonomously build and iterate on complex applications and better interpret underspecified prompts, producing more complete and production-ready results by default.

A defining feature of GPT-5.3-Codex is its interactive, agentic workflow. Users can steer the model while it is working, receive progress updates, and adjust direction without losing context, making it feel more like a teammate than a batch automation tool. The model was even used internally to help debug its own training and deployment processes. GPT-5.3-Codex is available through paid ChatGPT plans in the Codex app, CLI, IDE extension, and web, with API access planned for the future.