Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI Adoption Is Outpacing Governance: Conversations on Managing AI Risk

Executives everywhere are under pressure to deploy AI fast — but our recent roundtable on AI risk, hosted by TEISS, revealed a growing concern: AI adoption is outpacing governance, and organisations are taking on more risk than they realise. While most enterprises have mature technical controls, many are missing visibility into how AI is being used — and by whom.

AI-Generated Attacks: What are They and How to Avoid Them?

AI-generated attacks, such as social engineering, phishing, deepfakes, malicious GPTs, data poisoning, and more, are disrupting the current security landscape speedily. But there are ways to avoid them and strengthen our defences with miniOrange IAM solutions.

How Exabeam Detects LLM Abuse for Google Cloud Model Armor

In this demo, see how the Exabeam New-Scale Security Operations Platform integrates with Google Cloud Model Armor to detect and stop abuse of large language models (LLMs). You’ll learn how Exabeam: Monitors AI activity for suspicious or malicious behavior Uses advanced analytics to spot LLM misuse in real time Helps security teams enforce responsible AI use policies Watch how Exabeam and Google Cloud work together to provide stronger visibility, detection, and protection against emerging threats targeting LLMs.

An AI/ML Deep Dive with Luke Wolcott

This week on the podcast, we bring on WatchGuard's head of MDR data science Luke Wolcott to discuss the evolution of machine learning and artificial intelligence in cybersecurity. We dive into the differences in common (and uncommon) machine learning models, the pros and cons of supervised vs unsupervised learning, and why some of the coolest things happening in AI aren't the ones you hear about in the news.

The AI Revolution: Embracing the Future of eDiscovery

The eDiscovery landscape is undergoing a profound transformation, driven by the rapid evolution of artificial intelligence (AI). What was once a labor-intensive, manual process is now being revolutionized by technologies capable of analyzing vast volumes of data with speed, precision and insight. AI is not just a buzzword; it’s a catalyst for smarter, faster and more defensible legal workflows.

Privacy Concerns with AI in Healthcare: 2025 Regulatory Insight

Healthcare has always been one of the toughest environments for maintaining privacy. Now add AI assistants, retrieval-augmented generation, and multimodal inputs like clinical images and voice notes. Sensitive information travels farther and faster than ever before, and the fallout from a single leak can be devastating, affecting clinical, legal, and reputational aspects. The question for 2025 is simple: how do we harness the advantages of AI without compromising private health data?

LLM Security in 2025: Risks, Mitigations & What's Next

Large language model (LLM) security refers to the strategies and practices that protect the confidentiality, integrity, and availability of AI systems that use large language models. These models, such as OpenAI’s GPT series, are trained on vast datasets and can generate, translate, summarize, and analyze text. However, like any complex software component, LLMs present unique attack surfaces because they can be influenced by the data they process and the prompts they receive from users.

Is This the Best Coding Model in the World? Claude Sonnet 4.5

In this episode of our AI Coding Tools series, we test Claude Sonnet 4.5 to see if it can build a secure note-taking app. The model claims to be the best in the world — but does it live up to the hype? We’ll cover how it codes, where it shines (or struggles), and how it stacks up against other AI coding assistants.