Weak Model Provenance: Trust Without Proof A critical weakness in today’s AI model landscape is the lack of strong provenance mechanisms. While tools like Model Cards and accompanying documentation attempt to offer insight into a model’s architecture, training data, and intended use cases, they fall short of providing cryptographic or verifiable proof of the model’s …
When deploying LLMs in enterprise environments, overlooking secure configuration practices can unintentionally expose sensitive backend logic, security parameters, or operational infrastructure. These misconfigurations—often subtle—can offer attackers or misinformed users unintended access to the LLM’s internal behaviour, leading to serious data leakage and system compromise.
While theoretical risks highlight potential harm, real-world scenarios bring the dangers of LLM02:2025 into sharper focus. Below are three attack vectors illustrating how sensitive information disclosure unfolds in practical settings.
SearchGPT is a sophisticated AI-driven search engine that goes beyond traditional keyword matching. It leverages natural language processing (NLP) and machine learning to understand user intent, providing highly relevant and personalized search results.