The cybersecurity industry is confronting a new reality: traditional vulnerability management is no longer enough. As enterprises rapidly deploy AI-powered applications, autonomous agents, and large language model (LLM) infrastructure, security teams are discovering that many of the most dangerous exposures cannot be identified through conventional CVE-based scanning alone. Instead, organizations are increasingly grappling with misconfigured AI services, […]<br /> This story continues at The Next Web [...]
Enterprise AI has largely been built around context engineering. Teams connect enterprise systems, generate chunks and embeddings, build retrieval pipelines, and assemble the context needed by individ [...]
Perplexity, the AI-powered search company valued at $20 billion, announced on Wednesday at its inaugural Ask 2026 developer conference that its multi-model AI agent, Computer, is now available to ente [...]
Earlier today, OpenAI launched GPT-5.6-Cyber, a specialized model designed to perform advanced vulnerability research and exploit development for approved defenders — including categories of work th [...]
AI R&D runs on a cycle of hypothesis, experiment, and analysis — each step demanding substantial manual engineering effort. A new framework from researchers at SII-GAIR aims to close that bottle [...]
The 2025 State of Pentesting Survey Report by Pentera paints a striking picture of a cybersecurity landscape under siege—and evolving fast. This isn’t just a story about defending digital borders; [...]
Run a prompt injection attack against Claude Opus 4.6 in a constrained coding environment, and it fails every time, 0% success rate across 200 attempts, no safeguards needed. Move that same attack to [...]
It’s been 18 years since the last Metroid Prime game, but I felt right at home in Metroid Prime 4: Beyond. Almost too at home. Whether fighting my way through a volcano, exploring a research base in [...]