Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

For years, AI and machine learning workloads lived in the lab. They ran as internal experiments, batch jobs in isolated clusters, or offline data pipelines. Security focused on internal access controls and protecting the data perimeter. That model no longer holds. Today, AI models are increasingly part of production traffic, which is driving new challenges around securing AI workloads in Kubernetes.

Phishing attacks are everywhere these days. People encounter them while shopping, job hunting, reading work emails, and checking personal texts. Thanks to AI-powered scammers, phishing has become both more common and harder to spot, leading to disastrous consequences. A phishing attack on a business costs an average of $4.8 million, and attacks on individuals can drain bank accounts and wreck credit scores.

Everyone’s chasing a smarter agent. But the model was never what held the SOC back. The sharpest LLM still won’t know your environment, your team’s past calls, or where they draw the line on risk. That lives in the layer beneath the agents: context, memory, and learning. Torq’s AI research team breaks down how we build it.

Mobile security has always been complex, but LLM technology has added a whole new dimension to the field. Behind every popular generative AI (genAI) tool is a comprehensive large language model (LLM) that provides data and parses queries in natural language. When used responsibly, LLMs can be useful tools for ideation and content generation. In the wrong hands, though, LLMs can help threat actors supercharge their social engineering scams.

Security teams are entering a new phase of risk driven by the combination of AI agents and broad access to internal and external data. Agents are no longer limited to responding to prompts. They read files, pull documents from shared repositories, query external sources, and move information across systems on behalf of users. This shift brings real business value. Knowledge becomes easier to access, workflows move faster, and information that once required deliberate effort can be surfaced instantly.