AI-powered penetration testing is an advanced approach to security testing that uses artificial intelligence, machine learning, and autonomous agents to simulate real-world cyberattacks, identify ...

Businesses with a Mac-first strategy have long enjoyed the perception of inherent security from the Unix-based operating ...

Understanding how threat hunting differs from reactive security provides a deeper understanding of the role, while hinting at how it will evolve in the future.

Weekly cybersecurity recap covering emerging threats, fast-moving attacks, critical flaws, and key security developments you need to track this week.

Security in online gaming has evolved into a multi-layered discipline that blends technology, regulation, and behavioural analysis. As platforms grow more interconnected and financially integrated, ...

Real-world deployments show 40% test cycle efficiency improvement, 50% faster regression testing, and 36% infrastructure cost savings.

Open models were supposed to democratize artificial intelligence. Instead, security researchers now say they are handing cybercriminals industrial grade tools that can be downloaded, modified, and ...

Built-in functions, UDFs, materialized results, and integrations with ML and AI models make streaming SQL a compelling choice ...

The use of AI in pharmaceutical development is becoming widespread, but the rulebook is still being written.McKinsey reports that 71% of businesses across various industries now use generative AI, ...

AI agents are no longer a research concept. They book travel, execute trades, draft documents, approve purchases, and interact with ...

AI Impact examines responsible AI, creative scale, deployment friction and the leaders steering AI adoption.

As cyber threats continue to evolve and grow more persistent and sophisticated, simply applying tools and technologies to respond to previous attacks is ...