LLM-Centric Threats: Injection and Poisoning
Abstract
In the last chapter, we made our server less vulnerable to common software problems. We built a strong fence around our playground to keep our tools from running malicious codes or getting files they shouldn't. Our code is now a lot safer. But the most intriguing and difficult part of keeping agentic systems safe isn't keeping the code safe; it's keeping the "mind" of the agent itself safe.
Fields of Study & Subjects
Adversarial Robustness in Machine Learning
Security and Verification in Computing
Web Application Security Vulnerabilities
Publication details
- Journal / source
- Apress eBooks
- Pages
- 195–205
- Publication date
- 1 January 2026
- Language
- EN
- Document type
- Book chapter