Elastic Security Labs releases guidance to avoid LLM risks and abuses

Elastic Security Labs has released a comprehensive guide to secure the adoption of large language models (LLMs), addressing the increased attack surfaces and security challenges posed by the rapid implementation of generative AI technologies. The publication, titled the LLM Safety Assessment, offers detailed risk assessments, mitigation strategies, and InfoSec countermeasures to help organizations safeguard their LLM deployments. It includes insights for newcomers and seasoned security teams alike, covering common abuses and countermeasures, such as in-product controls for developers and information security measures for security operations centers. Elastic emphasizes the importance of public access to security research, aiming to democratize knowledge and enhance industry-wide safety, regardless of whether organizations are Elastic customers. The guide also introduces detection rules for mitigating risks associated with LLM prompt and response actions, showcasing Elastic's commitment to transparency and proactive security measures.