Despite the hype around AI-assisted coding, research shows LLMs only choose secure code 55% of the time, proving there are fundamental limitations to their use.

The private security industry has undergone significant transformations over the past five decades, with a notable shift toward employee-centered security models that prioritize workforce stability, ...

Security that slows productivity is a burden. It won’t survive. If your model assumes people will tolerate friction ...

OpenAI has drawn a rare bright line around its own technology, warning that the next wave of its artificial intelligence systems is likely to create a “high” cybersecurity risk even as it races to ...

One malicious prompt gets blocked, while ten prompts get through. That gap defines the difference between passing benchmarks and withstanding real-world attacks — and it's a gap most enterprises don't ...

What if the very tools designed to transform communication and decision-making could also be weaponized against us? Large Language Models (LLMs), celebrated for their ability to process and generate ...

Endor Labs today announced a brand new feature in the company’s signature platform enabling organizations to discover the AI models already in use across their applications and to set and enforce ...

Model-Driven Security Engineering for Data Systems represents a structured methodology that integrates security into the early stages of system and database development. This approach leverages ...

Vision language models (VLMs) have made impressive strides over the past year, but can they handle real-world enterprise challenges? All signs point to yes, with one caveat: They still need maturing ...