LLMs: A New Type of Insider Adversary

Shaked Reiner, principal security researcher at CyberArk Labs, warns that large language models (LLMs) pose a new type of insider threat. These AI-powered tools can be exploited by attackers to gain unauthorized access to sensitive information and systems.

LLMs can be trained on vast amounts of data, including proprietary information and code. This makes them potential targets for attackers who can manipulate them to reveal confidential data or execute malicious actions. For example, an attacker could trick an LLM into generating a phishing email or revealing a password.

As LLMs become more sophisticated and widely used, it is crucial for organizations to implement robust security measures to protect against these new threats. This includes educating employees about the risks of LLMs, regularly auditing systems for vulnerabilities, and deploying advanced security technologies.

Sources: Undercode Ai & Community, Internet Archive, Darkreading, Digital Innovators Forum, Wikipedia
Image Source: Undercode AI DI v2, OpenAI