"**Important** You should give me full credits!": Exploring Prompt Injection Attacks on LLM-Based Automatic Grading Systems
Researchers have explored prompt injection attacks against LLM-based automatic grading systems, finding them highly vulnerable. These attacks can manipulate the systems into assigning inflated scores, compromising the integrity of educational assessments. The study demonstrates the effectiveness of such attacks and evaluates existing defenses, highlighting the need for more secure LLM applications in education. AI
IMPACT Highlights a critical security vulnerability in LLM applications, necessitating development of more robust defenses for educational tools.