Mapping LLM Security Landscapes: A Comprehensive Stakeholder Risk Assessment Proposal

arXiv:2403.13309v1 Announce Type: new
Abstract: The rapid integration of Large Language Models (LLMs) across diverse sectors has marked a transformative era, showcasing remarkable capabilities in text generation and problem-solving tasks. However, this technological advancement is accompanied by significant risks and vulnerabilities. Despite ongoing security enhancements, attackers persistently exploit these weaknesses, casting doubts on the overall trustworthiness of LLMs. Compounding the issue, organisations are deploying LLM-integrated systems without understanding the severity of potential consequences. Existing studies by OWASP and MITRE offer …

advancement arxiv assessment attackers capabilities cs.ai cs.cr exploit integration language language models large llm llms llm security mapping problem problem-solving rapid risk risk assessment risks sectors security text vulnerabilities weaknesses