Microsoft Windows NT 4.0 DHCP Server Logging Buffer Overflow

To conclude our series on agentic AI, this article examines emerging vulnerabilities that threaten AI agents, focusing on providing proactive security recommendations on areas such as code execution, data exfiltration, and database access.

How can attackers exploit weaknesses in database-enabled AI agents? This research explores how SQL generation vulnerabilities, stored prompt injection, and vector store poisoning can be weaponized by attackers for fraudulent activities.

The adoption of large language models (LLMs) and Generative Pre-trained Transformers (GPTs), such as ChatGPT, by leading firms like Microsoft, Nuance, Mix and Google CCAI Insights, drives the industry towards a series of transformative changes. As the use of these new technologies becomes prevalent, it is important to understand their key behavior, advantages, and the risks they present.

This article discusses two O-RAN vulnerabilities that attackers can exploit. One vulnerability stems from insufficient access control, and the other arises from faulty message handling