Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Noam Cohen is a serial entrepreneur building seriously cool data and AI companies since 2018. Noam’s insights are informed by a unique combination of data, product, and AI expertise — with a background that includes winning the Israel Defense Prize for his work in leveraging data to predict terror attacks. As the Head of Artificial Intelligence at Torq, Noam is helping build truly next-gen AI capabilities into Torq’s autonomous SOC platform.

By now we’re all familiar with the capabilities of generative AI for creating images. For some tasks, like casting an existing image in a recognizable art style, it works well. Much more than that and it encounters limitations: complex prompts often don’t return exactly what you imagined and iterating on a failed prompt can quickly become time-consuming.

AI security is one of the most pressing challenges facing the world today. Artificial intelligence is extraordinarily powerful, and, especially considering the advent of Agentic AI, growing more so by the day. But it is for this reason that securing it is so important. AI handles massive amounts of data and plays an increasingly important role in operations; should cybercriminals abuse it, the consequences can be dire.

Over the past few years, enterprises have rapidly integrated GenAI into an increasing number of workflows and use cases. Amidst the rush and excitement to adopt a free tool that significantly boosts productivity, business leaders de-prioritized privacy, till it became a compliance issue. As privacy tools offering a quick patch quickly flooded the market, businesses ran into a new problem – which is the best tool?

Digital Risk Protection (DRP) helps organizations identify, monitor, and protect against threats across their digital footprint. The goal is to catch risks on the open, deep, and dark web before they can be exploited, by aggregating threat intelligence from diverse external sources (social media, underground forums, code repositories, and paste sites). Organizations scan continuously for exposed credentials, brand impersonations, data leaks, and emerging malware campaigns.

Vibe coding is an approach to AI coding where artificial intelligence generates executable code from natural language prompts, which is then reviewed and refined by human developers to ensure accuracy and security.