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 know exists.When attackers send a single malicious request, open-weight AI models hold the line well, blocking attacks 87% of the time (on average). But when those same attackers send multiple prompts across a conversation via probing, reframing and escalating across numerous exchanges, the math inverts fast. Attack success rates climb from 13% to 92%.For CISOs evaluating open-weight models for enterprise deployment, the implications are immediate: The models powering your customer-facing chatbots, internal copilots and autonomous agents may pass single-turn safety benchmarks whil [...]
Security teams are buying AI defenses that don't work. Researchers from OpenAI, Anthropic, and Google DeepMind published findings in October 2025 that should stop every CISO mid-procurement. Thei [...]
Block today announced Managerbot, a new AI agent embedded in the Square platform that proactively monitors a seller's business, identifies emerging problems, and proposes actionable solutions — [...]
It’s 3:37 am on a Sunday in Los Angeles, and one of the leading financial services firms on the West Coast is experiencing the second week of a living-off-the-land (LOTL) attack. A nation-state cybe [...]
Hybrid cloud security was built before the current era of automated, machine-based cyberattacks that take just milliseconds to execute and minutes to deliver devastating impacts to infrastructure. The [...]