Category: Tidbits

Series Overview This article is Part 4 of a multi-part series: “Development of system configuration management.” The complete series:

Enterprise data solutions are growing across data warehouses, data lakes, data lakehouse, and hybrid platforms in cloud services. As the data grows exponentially across these services, it’s the data practitioners’ responsibility to secure the environment with secure guardrails and privacy boundaries.  In this article, we will learn a framework for implementing security protocols in AWS

Series Overview This article is Part 3 of a multi-part series: “Development of system configuration management.” The complete series:

We’ve normalized multi-factor authentication (MFA) for human users. In any secure environment, we expect login workflows to require more than just a password — something you know, something you have, and sometimes something you are. This layered approach is now foundational to protecting human identities. But today, the majority of interactions in our infrastructure aren’t

Ransomware remains one of the biggest threats to individuals and corporations, primarily because cybercriminals relentlessly look for loopholes. With traditional measures struggling to keep pace with cyber threats, the shift to artificial intelligence (AI) and machine learning (ML) can be revolutionary. With such technologies, detection is automated, damage mitigation strategies are devised, and even attacks

Large language models (LLMs) have transitioned from research labs into the everyday workflows of companies worldwide. While tools like GPT-4 and Claude often steal the spotlight, they come with restrictions such as API rate limits, opaque model behavior, and privacy concerns. This has led to the rise of open-source LLMs like Meta’s LLaMA, Mistral AI’s

Privacy-preserving techniques are keeping your data safe in the age of AI. In particular, federated learning (FL) keeps data local, while differential privacy (DP) strengthens individual privacy. In this article, we will discuss challenges associated with this, practical tools, and emerging trends like secure aggregation and personalized FL for stronger privacy in AI. Introduction

With the increasing use of Open GPTs in industries such as finance, healthcare, and software development, security concerns are growing. Unlike proprietary models, open-source GPTs allow greater customization but also expose organizations to various security vulnerabilities. This analysis explores real-world breaches, case studies, and advanced security techniques to safeguard Open GPT deployments.

Have you heard of the new OWASP Top 10 for Large Language Model (LLM) Applications? If not, you’re not alone. OWASP is famous for its “Top 10” lists addressing security pitfalls in web and mobile apps, but few realize they’ve recently released a dedicated list for LLM-based systems. With AI chatbots, text generators, and agentic

The Open Worldwide Application Security Project, OWASP, has just released its top 10 non-human identities risks for 2025. While other OWASP resources broadly address application and API security, none focus specifically on the unique challenges of NHIs. This new document fills that gap, addressing risks that are often overlooked but have critical implications for organizational