RedEye / Course

AI Security Foundations

Six modules covering the AI threat landscape, adversarial ML, defensive operations, tooling, ethics, and risk management. Self-paced. Complete all six to unlock the assessment.

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Course Modules
1
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AI Threat Landscape
How AI is reshaping the attack surface — MITRE ATLAS, AI-accelerated threats, and the dual-use risk of defensive AI tools.
⏱ 20 min 📄 4 concepts
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2
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AI-Augmented Attack Vectors
Adversarial ML techniques — data poisoning, adversarial evasion, prompt injection, and model extraction attacks.
⏱ 20 min 📄 4 concepts
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3
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Defensive AI in Security Operations
Deploying AI for detection and triage — concept drift, explainability requirements, and maintaining model accuracy over time.
⏱ 20 min 📄 4 concepts
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4
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AI Security Tooling & Implementation
Evaluating and securing AI tools — ML-BOM, vendor assessment frameworks, least privilege, and shadow AI governance.
⏱ 20 min 📄 4 concepts
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5
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AI Ethics & Governance in Cybersecurity
EU AI Act risk tiers, NIST AI RMF, GDPR and AI training data, and accountability structures for high-stakes AI decisions.
⏱ 20 min 📄 4 concepts
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6
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AI Adoption & Risk Management
Building a defensible AI adoption strategy — phased deployment, model lifecycle management, and CISO risk ownership.
⏱ 20 min 📄 4 concepts
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