Data Exfiltration

Data exfiltration, the unauthorized removal of sensitive data from a system, is a critical cybersecurity concern, with research focusing on improving detection and understanding attack methods. Current studies explore vulnerabilities in large language models (LLMs) and cloud services, leveraging techniques like prompt injection and bidirectional training of neural networks to achieve exfiltration. These efforts highlight the need for robust security measures, particularly in light of the high costs associated with data breaches and the increasing sophistication of attacks, driving advancements in active learning, anomaly detection, and reinforcement learning-based approaches to identify and mitigate exfiltration pathways.