Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Understanding LLM Evaluation Metrics for Better RAG Performance

In the evolving landscape of artificial intelligence, Large Language Models (LLMs) have become essential for natural language processing tasks. They power applications such as chatbots, machine translation, and content generation. One of the most impactful implementations of LLMs is in Retrieval-Augmented Generation (RAG), where the model retrieves relevant documents before generating responses.

OWASP LLM Top 10 for 2025: Securing Large Language Models

As the adoption of large language models (LLMs) continues to surge, ensuring their security has become a top priority for organizations leveraging AI-powered applications. The OWASP LLM Top 10 for 2025 serves as a critical guideline for understanding and mitigating vulnerabilities specific to LLMs. This framework, modeled after the OWASP Top 10 for web security, highlights the most pressing threats associated with LLM-based applications and provides best practices for securing AI-driven systems.

Avoid Rookie Mistakes: Tips for Managing LLM Cost

The initial excitement of deploying a first large language model application often wears off quickly when the first bill arrives. Many newcomers face sticker shock when they see how quickly LLM costs can escalate. Money matters in AI projects. Most teams discover this truth the hard way. The difference between success and failure often comes down to financial planning. Organizations rushing to implement AI solutions frequently overlook the financial aspects.

Understanding Common Issues in LLM Accuracy

Large language models transform how people interact with AI technology. Despite impressive capabilities, these systems struggle with consistent LLM accuracy. Users frequently encounter false information, logical errors, and confused responses. Many organizations deploy LLM-powered applications without understanding these limitations. The consequences range from minor inconveniences to major business disasters. Engineers need practical knowledge about accuracy challenges.

DeepSeek-V3: The AI Beast with 671 Billion Parameters - Game Changer or Privacy Nightmare?

Executive Summary DeepSeek is one of the biggest AI-based systems that originated in China, some serious cyberattacks recently disrupted its services, especially affecting new user registrations. It is not yet clear how it has been done. However, based on analysis and experience, people believe it was a Distributed Denial of Service (DDoS) attack against the system, as a DDoS attack simply sends too much traffic to any given system that causes downtime.

Is DeepSeek's Latest Open-source R1 Model Secure?

DeepSeek’s latest large language models (LLMs), DeepSeek-V3 and DeepSeek-R1, have captured global attention for their advanced capabilities, cost-efficient development, and open-source accessibility. These innovations have the potential to be transformative, empowering organizations to seamlessly integrate LLM-based solutions into their products. However, the open-source release of such powerful models also raises critical concerns about potential misuse, which must be carefully addressed.

5 Ways AI Helps Small Agencies Scale Efficiently and Affordably

There are always hurdles that should be considered before expanding an agency. Reaching a larger market is one of those, and it requires a bigger budget. Trying to grow always presented the same issue. Every time I wanted to scale up, I hit a wall because I did not have enough resources. It was quite a predicament. Does this ring a bell? There's some good news though - AI has leveled the playing field. Now, if you're a small agency wanting to step up your game, let me tell you some golden nuggets I've learned. Use these 5 tips if you're going to scale your business like I did.

OWASP Top 10 LLM Applications 2025 - Critical Vulnerabilities & Risk Mitigation

The release of the OWASP Top 10 for LLM Applications 2025 provides a comprehensive overview of the evolving security challenges in the world of Large Language Models (LLMs). With advancements in AI, the adoption of LLMs like GPT-4, LaMDA, and PaLM has grown, but so have the risks. The new 2025 list builds upon the foundational threats outlined in previous years, reflecting the changing landscape of LLM security.

Best Practices for Protecting PII: How To Secure Sensitive Data

Protecting PII has never been more crucial. In today’s digital world, where data breaches are rampant, ensuring PII data security is essential to maintain trust and compliance with regulations like GDPR and CCPA. PII protection safeguards sensitive personal information, such as names, addresses, and social security numbers, from cyber threats, identity theft, and financial fraud.