Explications claires sur les guardrails et l'injection.
Securing LLM Applications: Prompt Injection and Guardrails
Learn to protect AI-driven applications from vulnerabilities, implement effective guardrails, and secure sensitive data in modern backend systems.
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About this course
As Large Language Models (LLMs) become central to modern software, securing them against emerging threats is a critical skill. This foundational course introduces AI security concepts tailored for backend developers and security enthusiasts. You will explore the unique vulnerabilities of LLM-integrated systems and learn practical techniques to defend against them. What you will learn includes how to: understand essential LLM architecture concepts and common AI security risks; identify and mitigate prompt injection and jailbreaking attacks; implement robust guardrails to filter inputs and control model outputs; secure Retrieval-Augmented Generation (RAG) pipelines and vector databases against data leakage; apply data protection principles to handle sensitive user information safely; and practice secure prompt engineering techniques to minimize unintended model behavior. The course begins by establishing key terminology and basic concepts of AI security before advancing to practical defense strategies. You will read through clear explanations and analyze written code snippets that demonstrate how to build secure backend integrations for LLMs. Designed for beginners and transitioning backend engineers, this program requires no prior cybersecurity expertise. Start learning today to build secure and resilient AI applications.
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2h 48m of practical content
Reviews (19)
Der Kurs zeigt sehr anschaulich, wie Prompt-Injection-Angriffe tatsächlich ablaufen und wie man mehrschichtige Guardrails dagegen aufbaut. Besonders gut fand ich die praktischen Übungen, bei denen man selbst versucht, ein Modell auszutricksen, bevor man lernt, wie man genau das verhindert. Dadurch bleibt das Wissen viel besser hängen als bei reiner Theorie.
De uitleg over hoe je guardrails opzet tegen prompt injection is heel praktisch, al had ik graag wat meer diepgang gezien bij de sectie over output-validatie.
Я работаю с LLM-приложениями уже около года, но именно системного понимания атак через prompt injection мне не хватало — этот курс закрыл этот пробел. Преподаватель разбирает конкретные примеры того, как злоумышленник может через обычный текст заставить модель проигнорировать системные инструкции, и сразу показывает, как строить защиту от такого поведения. Особенно полезной оказалась часть про многослойные guardrails: не полагаться на один фильтр, а комбинировать проверку входа, выхода и логику самого промпта. Материал подан последовательно, без лишней воды, и почти каждая тема сопровождается практическим заданием. После курса я переработал защиту в двух своих проектах и стал куда спокойнее за их безопасность.
프롬프트 인젝션 방어 정말 실용적이었어요
কোর্সটা প্রম্পট ইনজেকশন আর গার্ডরেইল নিয়ে বেশ পরিষ্কারভাবে বুঝিয়েছে, তবে কিছু ল্যাব অংশ আরেকটু বিস্তারিত হলে ভালো হতো।
Mình học khá nhiều framework bảo mật nhưng khóa này về prompt injection vẫn khiến mình bất ngờ vì góc nhìn rất thực tế. Giảng viên đưa ra từng ví dụ tấn công cụ thể, từ chèn lệnh ẩn trong văn bản đến việc lừa mô hình bỏ qua hướng dẫn hệ thống, rồi giải thích cách dựng guardrail để chặn từng loại. Phần thực hành xây dựng lớp kiểm tra đầu vào và đầu ra giúp mình áp dụng ngay vào một chatbot nội bộ đang làm. Tốc độ giảng dạy vừa phải, không dồn ép nhưng vẫn đủ sâu để hiểu bản chất vấn đề chứ không chỉ học thuộc quy tắc. Sau khóa học mình tự tin hơn hẳn khi review bảo mật cho các ứng dụng AI của công ty.
ผมดูแลระบบที่มีแชตบอตให้ลูกค้าใช้ เลยกังวลเรื่องความปลอดภัยมาตลอด คอร์สนี้อธิบายเรื่อง prompt injection ได้เห็นภาพมาก ทำให้เข้าใจว่าผู้ไม่หวังดีหลอกโมเดลได้อย่างไรและเราจะวาง guardrails ป้องกันได้แบบไหน ส่วนที่สอนการปกป้องข้อมูลอ่อนไหวในระบบหลังบ้านก็นำไปใช้กับงานจริงได้ทันที ตัวอย่างชัดเจนและทำตามได้ไม่ยาก เสียดายนิดเดียวที่อยากให้ลงลึกเรื่องการตรวจจับการโจมตีแบบใหม่ ๆ มากกว่านี้ โดยรวมถือว่าคุ้มค่าและช่วยให้ผมมั่นใจกับแอปมากขึ้นเยอะ
Gute Grundlagen, könnte etwas tiefer gehen.
Курс разложил по полочкам, как устроены атаки через prompt injection и почему обычная фильтрация ключевых слов не спасает. Понравилось, что каждую технику защиты сразу пробуешь руками на своём мини-проекте, а не просто слушаешь теорию. После прохождения я пересмотрел архитектуру одного внутреннего чат-бота и добавил нормальную проверку выхода модели.
Saya baru sedar betapa terdedahnya aplikasi LLM saya sebelum mengikuti kursus ini. Bahagian tentang prompt injection benar-benar membuka mata, kerana ia menunjukkan dengan jelas bagaimana penyerang boleh memperdaya model dan bagaimana kita menghalangnya. Saya belajar memasang guardrails yang menapis input berbahaya dan melindungi data sensitif dalam sistem backend. Setiap konsep disertai contoh praktikal yang boleh terus saya gunakan pada projek sendiri. Selepas menerapkan teknik di sini, saya jauh lebih yakin dengan keselamatan aplikasi AI saya. Amat saya syorkan kepada sesiapa yang membina produk berasaskan LLM.
Prompt injection saldırılarının nasıl çalıştığını ve guardrail'leri gerçek örneklerle nasıl kurabileceğimi bu kadar net anlatan başka bir kaynak görmemiştim.
دخلت هذه الدورة وأنا لا أعرف الكثير عن هجمات prompt injection، وخرجت بفهم واضح لكيفية استغلال الثغرات في تطبيقات الذكاء الاصطناعي وكيفية بناء طبقات حماية فعالة. المدرب يشرح أمثلة حقيقية لمحاولات اختراق النماذج اللغوية، ثم ينتقل مباشرة إلى كيفية تصميم guardrails تمنع هذه الهجمات دون أن تعطل تجربة المستخدم العادية. أعجبني بشكل خاص الجزء العملي حيث نبني معاً طبقة تحقق من المدخلات وأخرى من المخرجات، فهذا النهج المتعدد المستويات أكثر واقعية من الاعتماد على فحص واحد بسيط. الشرح متسلسل ومنطقي، ولم أشعر بالضياع رغم أن الموضوع تقني نوعاً ما. الآن أشعر بثقة أكبر عند مراجعة أمان أي تطبيق يعتمد على نماذج لغوية كبيرة.
El curso explica muy bien cómo funcionan los ataques de prompt injection y cómo diseñar guardrails para mitigarlos, con ejemplos concretos que se entienden sin ser experto en seguridad. Lo que más valoro es que no se queda en la teoría, sino que te hace implementar las defensas paso a paso. Eso sí, algunas de las demostraciones de laboratorio se sienten un poco apuradas y hay que pausar el video varias veces para no perderse.
Great guardrails course, wish it went deeper.
গার্ডরেইল বসানোর প্র্যাক্টিক্যাল অংশটা এত সহজভাবে দেখানো হয়েছে যে সরাসরি নিজের প্রজেক্টে প্রয়োগ করতে পেরেছি।
I went into this course knowing almost nothing about prompt injection attacks and came out with a working mental model for how attackers actually try to jailbreak LLM apps. The instructor walks through real examples of injection payloads and then shows how to build guardrails that actually catch them instead of just filtering obvious keywords. I especially liked the section on layered defenses, where you combine input sanitization with output validation rather than relying on a single check. The pacing was steady enough that I could follow along and test things in my own sandbox as we went. By the end I had rewritten the safety layer on a small chatbot project I'd been neglecting for months. Genuinely one of the more hands-on security courses I've taken.
Entrei nesse curso sem saber quase nada sobre segurança de aplicações com LLM e saí com uma visão bem prática de como ataques de prompt injection realmente acontecem. O instrutor mostra exemplos reais de tentativas de manipular o modelo para ignorar instruções do sistema, e depois ensina a construir guardrails em camadas para bloquear esse tipo de comportamento. A parte que mais gostei foi quando implementamos validação tanto na entrada quanto na saída do modelo, em vez de confiar só em um filtro simples de palavras-chave. O ritmo das aulas é bom, dá tempo de acompanhar e testar cada técnica no próprio ambiente antes de seguir para a próxima. Depois do curso já apliquei várias dessas ideias num chatbot interno que eu tinha deixado sem nenhuma proteção real.
प्रॉम्प्ट इंजेक्शन समझाना बहुत आसान बना दिया
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