In March 2024, a Fortune 500 team discovered that their TensorRT-optimized inference pipeline was leaking prompt data through shared GPU memory — a flaw invisible in benchmarks but catastrophic in production. When comparing TensorRT (NVIDIA’s high-performance inference runtime, currently at v8.6.1) against Mistral 2 (Mistral AI’s 7B/13B parameter models served via vLLM 0.3.x), most teams focus on throughput and latency. Few audit the security surface area. This article changes that. We benchmark both stacks on identical hardware, expose the attack vectors each introduces, and give you a hardened deployment path with real, runnable code. 📡 Hacker News Top Stories Right Now Google broke reCAPTCHA for de-googled Android users (602 points) OpenAI’s WebRTC problem (83 points) Wi is Fi: Understanding Wi-Fi 4/5/6/6E/7/8 (802.11 n/AC/ax/be/bn) (76 points) AI is breaking two vulnerability cultures (234 points) You gave me a u32. I gave you root.…