A Step-by-Step Guide to Securing Large Language Models (LLMs)
summary
Argues that LLM risk reduces to data control and gives a concrete path: inventory LLM apps via cloud provider APIs, run a full enterprise scan with a data store scanner, apply on‑demand scanners to RAG sources and prompts, and enforce modular rules with AI policy matching at request and response points. Recommends fronting apps with a semantic firewall, warns guardrails can cost ~1,000x the response cost, and outlines quick wins: audit in a week, maps and labels in three months, firewall rollout in six.
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chapters (8)
- 0:00Securing enterprise LLMs
- 10:13LLM security differences
- 16:21OSI model and LLM threats
- 21:58LLM security framework
- 27:21Semantic layer defenses
- 33:30Semantic firewall design
- 34:33Summary
- 44:15Q&A
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