At its core, Unbounded Consumption refers to an LLM application’s failure to impose constraints on inference usage—resulting in an open door for resource abuse. Unlike traditional software vulnerabilities that might involve code injection or data leakage, Unbounded Consumption exploits the operational behaviour of the model itself—by coercing it into performing an excessive number of inferences.
In the digital-first world, Large Language Models (LLMs) such as OpenAI’s GPT series, Google’s Gemini, and Anthropic’s Claude are redefining how businesses operate. From automating customer service and accelerating legal research to generating strategic reports, LLMs are integrated into critical enterprise workflows.
LLM misinformation occurs when the model generates false or misleading information that appears credible. This is particularly dangerous because of the model’s inherent linguistic fluency—users often assume that well-phrased responses are factually correct.
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Upgrading Ubuntu Kernel v6.15.2 🔐 Linux Kernel v6.15 – What’s New & Security-Relevant 🗓️ Released: 26 May 2025 (With follow-up patches v6.15.1 and v6.15.2) 🗓️ Released: v16.15.2 on 10th June 2025 1. 🛡️ Security Enhancements 🔸 LSM (Linux Security Modules) Improvements 🔸 Spectre/Meltdown Updates 🔸 Kernel Address Space Layout Randomisation (KASLR) 2. 🔗 Networking Security …
In an era defined by algorithmic decision-making, synthetic content, and digital hyper-efficiency, the emergence of Agentic Artificial Intelligence (AI) represents a monumental shift for businesses worldwide. Unlike traditional AI tools, which are reactive and rely on manual input, Agentic AI operates autonomously. These systems can pursue goals, make decisions, and adapt in real time—effectively becoming intelligent agents embedded within organisational workflows.