Security Threats in Agentic AI System
It addresses security vulnerabilities in AI systems for developers and users, but is incremental as it focuses on known risks without new solutions.
This paper tackles the problem of privacy and security threats in Agentic AI systems with direct database access, highlighting risks like unauthorized data retrieval and exploitation of vulnerabilities, but does not provide concrete results or numbers.
This research paper explores the privacy and security threats posed to an Agentic AI system with direct access to database systems. Such access introduces significant risks, including unauthorized retrieval of sensitive information, potential exploitation of system vulnerabilities, and misuse of personal or confidential data. The complexity of AI systems combined with their ability to process and analyze large volumes of data increases the chances of data leaks or breaches, which could occur unintentionally or through adversarial manipulation. Furthermore, as AI agents evolve with greater autonomy, their capacity to bypass or exploit security measures becomes a growing concern, heightening the need to address these critical vulnerabilities in agentic systems.