Solid intro to prompt injection defenses, though the section on indirect injection felt a bit rushed.
AI Security: Preventing Prompt Injection
A practical guide for developers and security professionals to understand and mitigate prompt injection vulnerabilities in AI systems.
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About this course
As large language models (LLMs) become integrated into more applications, they introduce new and unique security risks. The most common and critical vulnerability is prompt injection, where a malicious user can hijack the model's behavior.
This course provides a foundational understanding of AI security, focusing on the practical skills needed to defend against these attacks. You will learn to think like an attacker to spot vulnerabilities and then build robust defenses, or 'guardrails', to protect your LLM-powered applications and their users.
What you'll learn:
- Understand the core principles of prompt injection and its variants, including jailbreaking.
- Learn to identify common attack patterns in user-facing applications.
- Apply defensive techniques such as input sanitization, instructional defense, and output filtering.
- Practice building secure wrappers for API calls to large language models.
- Configure basic monitoring and logging to detect potential security threats.
- Discover the broader landscape of AI security risks, including data privacy concerns.
The course begins with the fundamental concepts of prompt engineering and the mechanics of injection attacks, then progresses to hands-on defense strategies and best practices for building secure systems.
This course is designed for developers, security analysts, and tech professionals who are new to the security challenges of AI. No prior experience in AI security is required, though a basic understanding of software development concepts is helpful.
Begin your journey into AI security and learn to build more resilient applications.
What you'll get
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Short & focused
2h 30m of practical content
Reviews (18)
Il corso spiega bene come riconoscere i tentativi di prompt injection con esempi concreti presi da casi reali. Da sviluppatore ho trovato utili i controlli suggeriti per validare gli input verso il modello. Avrei solo gradito qualche esercizio pratico in più da svolgere da soli.
As someone who builds internal tools on top of LLMs, this course finally gave me a structured way to think about prompt injection instead of just patching things reactively. It walks through several real attack patterns, including indirect injection through documents and web content, which I hadn't fully considered before. The defensive techniques are practical rather than theoretical, with concrete input validation and sandboxing approaches you can apply immediately. My only complaint is that the section on securing agentic tool calls feels a little thin compared to everything else. Still, I came away with a checklist I'm now actually using at work.
Modul tentang cara penyerang menyelitkan arahan tersembunyi dalam input pengguna benar-benar membuka mata saya. Teknik sanitasi dan pengasingan prompt sistem diterangkan dengan jelas, cuma saya harap ada lebih banyak contoh serangan sebenar pada sistem produksi.
এই কোর্সে prompt injection আসলে কীভাবে কাজ করে সেটা খুব বাস্তবসম্মতভাবে দেখানো হয়েছে, শুধু তত্ত্ব নয়। ডেভেলপার হিসেবে আমি সহজেই বুঝতে পেরেছি কোথায় আমার নিজের অ্যাপে ফাঁক ছিল। শুধু কয়েকটা উদাহরণ আরেকটু আপডেটেড হলে ভালো হতো।
The way this course separates direct and indirect prompt injection made everything click for me. Each mitigation strategy is backed by an explanation of the underlying weakness it addresses. I walked away with a much more rigorous approach to validating anything that reaches my model.
Курс хорошо разбирает механику prompt injection на конкретных примерах, а не только в теории. Понравилось, что показывают реальные способы защиты, которые можно сразу внедрить в проект. Не хватило разве что более глубокого раздела про многоагентные системы.
Praktisch en duidelijk over prompt injection.
I've read a handful of blog posts on prompt injection but never had a clear mental model until this course. It starts with simple direct injection examples and builds up to more subtle indirect attacks hidden in retrieved documents, which was eye-opening. The instructor explains why common naive defenses like simple keyword filtering fail, which I appreciated since I'd tried exactly that approach before. Each mitigation technique comes with a reasoning for why it works, not just a copy-paste snippet. I immediately went back and rewrote the input handling in one of my own projects after finishing this.
Ce cours démystifie vraiment le prompt injection avec des exemples concrets d'attaques réelles. J'ai apprécié la partie sur les injections indirectes via des documents, un angle que je n'avais jamais considéré. Je repars avec des techniques de validation que j'ai déjà intégrées dans mon propre projet.
Kursus ini menjelaskan prompt injection dengan sangat jelas, lengkap dengan contoh kasus nyata yang pernah terjadi. Sebagai developer saya jadi paham cara memvalidasi input sebelum masuk ke model AI. Materinya langsung bisa saya terapkan di proyek yang sedang saya kerjakan.
Finally understand prompt injection properly.
Excellente explication des attaques par injection de prompt, avec des contre-mesures que j'ai pu appliquer tout de suite.
Good breakdown of how prompt injection attacks actually work against real applications, not just a surface-level overview. The mitigation techniques section is genuinely practical for anyone building on top of an LLM. I would have liked a bit more coverage on multi-agent systems specifically.
Cleared up prompt injection for me in a way that actually makes sense from a security engineering angle, not just theory.
Turned an abstract security concept into something I could actually test and defend against in my own codebase.
Solid practical content on defending against prompt injection, aimed clearly at people who already write code. The examples involving injected instructions hidden in uploaded files were particularly useful for my own security review. Wish there was a bit more on testing methodology to actually verify your defenses work.
프롬프트 인젝션 방어법이 확실히 정리됐어요.
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