Secure Generative AI Apps: Learn concepts and explore practical such as prompt injection, insecure output handling etc.
β±οΈ Length: 2.0 total hours
β 4.32/5 rating
π₯ 5,599 students
π October 2025 update
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- Course Overview
- Explore the transformative power of Generative AI and Large Language Models, rapidly reshaping digital interactions.
- Understand the paramount necessity for robust cybersecurity as advanced AI systems integrate into core applications.
- Discover unique, evolving attack surfaces presented by LLMs, fundamentally distinct from traditional software vulnerabilities.
- This course meticulously adapts OWASP security principles, providing a structured approach to emerging AI-specific threats.
- Gain essential, practical insights tailored for developers, security professionals, and architects deploying GenAI solutions.
- Learn to construct secure-by-design LLM applications, embedding resilient security from initial development phases.
- Requirements / Prerequisites
- A foundational understanding of basic software development concepts and general application architecture is highly beneficial.
- Familiarity with common cybersecurity fundamentals, including typical web vulnerabilities, provides valuable contextual insight.
- Participants should possess a conceptual grasp of Generative AI capabilities and how Large Language Models generally function.
- No advanced AI/ML expertise, deep technical background in model training, or complex algorithm knowledge is strictly required.
- A strong, proactive interest in securing AI systems and understanding their unique threat models is essential for engagement.
- Skills Covered / Tools Used
- Skills:
- Master methodologies for comprehensive threat modeling specifically tailored for Generative AI and LLM applications.
- Implement secure coding practices crucial for prompt engineering and the safe integration of LLMs into various systems.
- Design and deploy highly effective input validation and sanitization techniques to prevent malicious data compromise.
- Develop robust strategies for detecting and efficiently responding to adversarial attacks targeting LLM behavior.
- Secure critical API endpoints that facilitate interaction with Large Language Models, safeguarding data flow and access.
- Establish fortified data pipelines across the AI model lifecycle, protecting training, fine-tuning, and inference processes.
- Evaluate inherent security risks and potential vulnerabilities of third-party AI models and external components.
- Tools:
- Engage with interactive demonstration environments meticulously simulating real-world LLM application vulnerabilities.
- Explore conceptual frameworks and libraries designed to implement secure prompt design and LLM interaction guardrails.
- Understand the principles behind tools for analyzing LLM outputs, identifying data leakage or malicious content generation.
- Witness practical examples using standard development environments, such as Python scripting or Jupyter notebooks.
- Skills:
- Benefits / Outcomes
- Elevate your capability to confidently design, develop, and securely deploy robust, threat-resistant Generative AI applications.
- Cultivate a proactive security mindset, enabling you to anticipate and defend against AI-specific cybersecurity risks effectively.
- Significantly reduce the potential for damaging data breaches, intellectual property theft, and reputational harm from LLM vulnerabilities.
- Ensure your AI initiatives maintain strong compliance with current and forthcoming AI security regulations and critical industry standards.
- Approach complex security challenges within the dynamic and fast-paced AI ecosystem with newfound competence and strategic confidence.
- Boost your professional marketability by acquiring highly sought-after expertise at the intersection of AI and advanced cybersecurity.
- PROS
- Offers highly pertinent and current content, directly addressing the most pressing cybersecurity concerns for Generative AI.
- The focused 2-hour duration is perfectly optimized for busy professionals seeking to acquire crucial knowledge efficiently.
- Emphasizes practical learning through engaging, real-world demos, ensuring a concrete understanding of threats and countermeasures.
- Boasts an exceptional student rating and high enrollment numbers, affirming its proven quality and widespread positive reception.
- Provides a structured and comprehensive overview of the OWASP Top 10 for LLM Apps, serving as a critical security blueprint.
- CONS
- While comprehensive for its duration, the concise 2-hour format may limit extensive deep-dive project work or cover every niche vulnerability in extreme detail.
Learning Tracks: English,IT & Software,Network & Security
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