SpecterOps has announced Adversary Intelligence: LLM Tradecraft, a hands-on course developed with OpenAI through the OpenAI Daybreak Defense Network. SpecterOps says registration is open and course materials will be available starting October 15, 2026. The training combines LLM fundamentals with practical work on evaluating, testing, and defending AI systems and agents.
What is LLM tradecraft?
Here, “LLM tradecraft” means the practical knowledge needed to build, assess, and secure systems that use large language models (LLMs), including agentic workflows. The course is framed for people who need to understand how these systems work as well as how attackers may exploit them and how defenders can evaluate them.
Wunan Li, Global Cyber Partnerships at OpenAI, said, “Building practical experience is essential to understanding how AI can be applied effectively in cybersecurity.” SpecterOps’ Andrew Chiles, VP of Tradecraft, said, “The gap between using AI and understanding it can create security blind spots.”
What does the SpecterOps and OpenAI course teach?
SpecterOps describes the training as a modular curriculum that learners can follow in sequence or use to focus on topics relevant to their work. The September 30, 2026 announcement specifies eight hours of content; the launch blog describes ten standalone modules. These are course specifications, not measures of learning outcomes.
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Foundational subjects include machine learning and LLM concepts, tokenization, context windows, prompting, and agent architecture. This material gives learners a basis for understanding what an AI-enabled workflow is doing before they examine how it can fail.
Evaluation and security testing
Applied topics include LLM observability and evaluation, threat modeling, prompt injection, jailbreaks, and weaknesses in AI infrastructure. The course materials also identify MCP security, addressing risks in systems that use the Model Context Protocol.
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Hands-on labs and defensive applications
SpecterOps says the course includes hosted labs and practical exercises. Examples described by the company include creating agentic workflows, evaluating agent runs with MLflow, and using Codex to reverse malware. The stated focus is practical assessment and defense, rather than just using AI tools without examining their behavior.
How do you secure AI agents against prompt injection?
Prompt injection is one of the threats named in the course curriculum. In an agentic system, the concern is not only what a model says in response to a prompt, but also how untrusted instructions may affect the agent’s decisions and actions through connected tools or data. SpecterOps lists prompt injection, jailbreaks, agent architecture, threat modeling, and infrastructure weaknesses as training topics; its public course descriptions do not set out a specific mitigation checklist or guarantee that a particular defense will prevent attacks.
The course’s stated combination of threat modeling, observability, evaluation, and hands-on agent work is relevant to examining those risks in context. Readers looking for a practical defense course should check the current syllabus and lab details to confirm that the depth matches their systems and responsibilities.
Who should take LLM security training?
SpecterOps positions the course for security practitioners, researchers, engineers, defenders, and technical leaders who need to understand, evaluate, or secure LLM-enabled workflows. Its modular structure may suit learners who want to concentrate on one area, such as foundations, evaluation, agent and MCP security, defensive application, or AI-assisted reverse engineering.
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It is digital training with hosted labs. The official descriptions do not identify a required physical product, textbook, or hardware accessory.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.When does the course start, and what is included?
SpecterOps’ September 30, 2026 announcement says course materials become available October 15, 2026, and that participants receive 30 days of course-content access. However, SpecterOps’ official pages differ on the included AI-tool access: the announcement says participants receive 30 days of Codex access, while the launch blog says each cohort includes a ChatGPT Pro subscription alongside 30 days of course materials and labs.
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