LLMs generated 615 vulnerable code snippets aligned with CAPEC and CWE frameworks across three languages, with 0.98 cosine similarity between model outputs.
Enhancing trust and safety in digital pay- ments: an LLM-powered approach
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CASE is a novel agentic AI system that proactively interviews scam victims using LLMs to collect detailed intelligence, which is then structured for use in scam prevention, resulting in a 21% increase in enforcements on Google Pay India.
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CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments
CASE is a novel agentic AI system that proactively interviews scam victims using LLMs to collect detailed intelligence, which is then structured for use in scam prevention, resulting in a 21% increase in enforcements on Google Pay India.