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.
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Prompt injection is not just a vulnerability — it’s a multi-headed threat vector. From overt attacks to inadvertent leakage, each scenario introduces unique risks, requiring tailored strategies to safeguard operational integrity, regulatory compliance, and business reputation.
DigiPIN is designed to be a technical standard for location identification, much like GPS coordinates.
The rapid adoption of Large Language Models (LLMs) such as ChatGPT, Claude, and Gemini has revolutionised enterprise operations across industries—from customer support and legal drafting to cybersecurity automation and product innovation. However, this surge in usage has opened new frontiers for cyber threats. Among the most pressing is LLM01:2025 Prompt Injection, the first and arguably the most dangerous vulnerability in OWASP’s Top 10 for LLMs.
Prompt injection attacks manipulate LLMs into executing unintended behaviours, bypassing safety protocols, generating harmful content, or leaking sensitive data—all of which hold serious business, regulatory, and reputational implications.