The Developer's Playbook for LLM Security (Books column)
I read this one. book by Steve Wilson, who was the director of the project.OWASP Top 10 for LLM Applications" He asked her how much the book was. 2024 The year on the safety of large language models is still relevant 2026-m. The answer is: as a basic engineering framework, yes, very much. As a complete overview of the current agenda - no longer, because the region has noticeably moved ahead in two years.
The book is valuable because it does not attempt to explain the security of LLM as a set of pro-prompt-injection scare stories, but shows a broader picture: where the limits of trust run, why an application with a language model cannot be perceived as a regular application, how data leaks appear, what to do with hallucinations, response processing, supply chain, model passports, SBOM/ML-BOM, protective restrictions, attack script checks and LLM operation.
The following highlights from the book
1LLM is not just a model, but a component of a software system. It has users, context, data, external sources, tools, runtime, logs, limits, access rights and consequences of actions. Therefore, security cannot be hung on a single query filter before the model.
2Prompt injections are important, but that’s not all. After all, the model has access to internal services, documents, knowledge base or tools, the risk is not in the text itself, but in the fact that it can move the behavior of the system beyond the permissible limit.
3The AI supply chain is becoming more complex than the usual software supply chain. In addition to libraries and containers, there are models, training data, vector representations, plug-in tools, query templates, quality assessment kits, and external providers. All this must be described, versioned, checked and observed in the work.
4It is important to build secure processes, not just respond to incidents. The book well suggests that LLM security needs to live inside development and operation: threat modeling, tests, attack scenario checks, defensive constraints, centralized logs, surveillance, incident response, and regular risk reassessment.
But 2026 The book can no longer be read as a comprehensive guide. In 2024The center of gravity was around chatbots, RAG applications and LLM as a new class of applied security. Now the agenda has shifted markedly to agents: tool calling, standalone workflows, MCP, memory, identity, abuse of rights, inter-agent interactions, visibility at work, and the ability to stop or roll back actions.
OWASP also reflects this: in addition to the LLM Top 10 Materials have already appeared on agential n and MCP Top 10. The more an agent can do in the outside world, the less security looks like a “check model response” and the more like a trust architecture: who gave the target, what tools are available, what rights are granted, what the agent remembers is being written in logs, who confirms dangerous actions and where the emergency stop is located.
Therefore, my assessment is this: the book is worth reading as a good foundation for engineers, architects, application security specialists, technicians and managers who launch LLM features into commercial operation. It helps to put your head back and stop thinking that AI security is a separate magical layer around the model.
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