Security Threats in Agentic AI System

TL;DR

This paper examines the security and privacy vulnerabilities of autonomous agentic AI systems with database access, highlighting risks of data breaches, exploitation, and misuse due to system complexity and evolving autonomy.

Contribution

It identifies key security threats in agentic AI systems and emphasizes the need for targeted defenses to mitigate vulnerabilities as AI autonomy increases.

Findings

Agentic AI systems face significant privacy risks.

Vulnerabilities can be exploited through system vulnerabilities.

Increased autonomy heightens security concerns.

Abstract

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.