A recent study shows 74% of CISOs plan to increase their budgets for cyber crisis exercises. Why? The rise in sophisticated attacks and high-profile breaches like those affecting 23andMe, NHS, and Cencora highlight the urgent need for proactive defense strategies. At RELIANOID, we help organizations..

From check-in to takeoff, modern airports rely on a complex network of integrated IT systems to ensure efficiency, safety, and smooth operations. We’ve visualized this in a new diagram, highlighting key components like: ✅ AODB (Airport Operational Database) ✅ Passenger & baggage handling systems ✅ A..

Google's MCP servers arm SecOps teams with direct control of security tools using LLMs.Now, analysts can skip the fluff and get straight to work—no middleman needed. The system ties runbooks to live data, offeringautomated, role-specific security measures. The result? A fusion of top-tier protocols .. read more  

Anthropic's MCPmakes LLMs groove with real-world tools but leaves the backdoor wide open for mischief. Full-Schema Poisoning (FSP) waltzes across schema fields like it owns the place.ATPAsneaks in by twisting tool outputs, throwing off detection like a pro magicians’ misdirection. Keep your eye on t.. read more  

Gorules the realm of long-lived, concurrent agent tasks. Its lightning-fast goroutines and petite memory use make Node.js and Python look like clunky dinosaurs trudging through thick mud. And don't get started on itscancellation mechanism—seamless cancelation, zero drama... read more  

Cursorwrestled with flaky tests, tangled in its over-reliance onXPath. A shift todata-testidfinally tamed the chaos. Though it tackled some UI tests, expired API tokens and timestamped transactions revealed its Achilles' heel... read more  

Metawants a piece of the$10 billion pieat Scale AI, diving headfirst into the largest private AI funding circus yet.Scale AI'srevenue? Projected to rocket from last year’s $870M to$2 billionthis year, thanks to some beefy partnerships and serious AI model boot camps... read more  

Reinforcement Learningfine-tunes large language models for better performance by adapting outputs based on structured feedback. Scaling RL for LLMs faces resource challenges due to massive computation, model sizes, and engineering problems like GPU idle time. Meta's LlamaRL is a PyTorch-based asynch.. read more