Artificial Intelligence is transforming cybersecurity, but it also introduces critical attack surfaces already being exploited. In this session, InfosecTrain breaks down how AI systems get hacked, covering prompt injection, model poisoning, and practical defense frameworks to help security teams protect machine learning pipelines effectively.
The "course titled" Practical AI Security Engineering Program provides hands-on expertise to defend your AI architecture.
📘 What You’ll Learn:
AI Attack Surfaces: Demystifying how machine learning components, data pipelines, and deep neural networks introduce novel security risks.
Prompt Injection & Exploits: Analyzing adversarial manipulation, backdoor attacks, and real-world system exploitation techniques.
Red Teaming & Methodologies: Applying structured AI threat modeling and offensive security methodologies to test AI resilience.
OWASP Top 10 for LLMs: Exploring the top security risks specifically impacting Large Language Model applications and integrations.
Governance Frameworks: Aligning technical AI security controls with ISO 42001 and NIST AI RMF compliance standards.
🎧 Essential listening for security engineers, red teamers, AppSec specialists, SOC analysts, and GRC professionals securing enterprise AI deployments.
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InfosecTrain. Innehållet i podden är skapat av InfosecTrain och inte av,
eller tillsammans med, Poddtoppen.
