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AI systems represent the new digital attack surface. As organizations deploy complex models, securing the underlying architecture is critical. In this masterclass episode, InfosecTrain breaks down the full AI security lifecycle, from threat modeling to deploying practical defenses against machine learning and LLM exploits.
The "course titled" Practical AI Security Engineering Program provides hands-on expertise to defend your AI pipelines.
📘 What You’ll Learn:
Foundations of AI Security: Mapping out unique AI attack surfaces, threat modeling approaches, and fundamental security controls.
Exploiting AI Vulnerabilities: Real-world breakdown of how adversaries target machine learning models, LLMs, and autonomous agentic AI workflows.
Defending AI Pipelines: Applying end-to-end security controls across data pipelines, model training environments, and production endpoints.
LLM & AppSec Safeguards: Securing generative AI applications against prompt injections, data poisoning, and model inversion attacks.
Governance & Responsible Adoption: Integrating risk frameworks to support secure, compliant, and scalable enterprise AI deployment.
🎧 Essential listening for security engineers, AppSec teams, AI developers, SOC analysts, and GRC leaders building next-generation AI defenses.
Watch Full video here: https://www.youtube.com/watch?v=iwaTgPD9h1A
By InfosecTrain3.7
33 ratings
AI systems represent the new digital attack surface. As organizations deploy complex models, securing the underlying architecture is critical. In this masterclass episode, InfosecTrain breaks down the full AI security lifecycle, from threat modeling to deploying practical defenses against machine learning and LLM exploits.
The "course titled" Practical AI Security Engineering Program provides hands-on expertise to defend your AI pipelines.
📘 What You’ll Learn:
Foundations of AI Security: Mapping out unique AI attack surfaces, threat modeling approaches, and fundamental security controls.
Exploiting AI Vulnerabilities: Real-world breakdown of how adversaries target machine learning models, LLMs, and autonomous agentic AI workflows.
Defending AI Pipelines: Applying end-to-end security controls across data pipelines, model training environments, and production endpoints.
LLM & AppSec Safeguards: Securing generative AI applications against prompt injections, data poisoning, and model inversion attacks.
Governance & Responsible Adoption: Integrating risk frameworks to support secure, compliant, and scalable enterprise AI deployment.
🎧 Essential listening for security engineers, AppSec teams, AI developers, SOC analysts, and GRC leaders building next-generation AI defenses.
Watch Full video here: https://www.youtube.com/watch?v=iwaTgPD9h1A

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