Generative AI Cybersecurity Solutions
Securing Generative AI-Based Products, AI Firewalls and AI Security Posture Management (AI-SPM) & Much More
5.00 (6 reviews)
6
students
2 hours
content
Jun 2025
last update
$19.99
regular price
What you will learn
Understand the unique security risks of Generative AI, including prompt injection, hallucinations, and data exfiltration
Analyze and defend against the OWASP Top 10 threats for LLM applications
Identify GenAI-specific attack surfaces such as embeddings, plugins, vector stores, and API endpoints
Implement AI Firewalls using token filtering, response moderation, and behavioral rule sets
Design and enforce Security Posture Management (AI-SPM) for prompts, agents, tools, and memory
Mitigate prompt-based attacks with detection engines, heuristic checks, and red teaming tools like PromptBench and PyRIT
Harden Vector Stores and RAG architectures against poisoning, drift, and adversarial recall
Apply sandboxing, runtime controls, and execution boundaries to secure LLM-powered SaaS and enterprise agents
Secure multi-agent orchestration frameworks (LangChain, AutoGen, CrewAI) from memory poisoning and plugin hijacking
Use identity tokens, task chains, and capability boundaries to protect agent workflows
Build and automate AI-specific security test suites and integrate them into CI/CD pipelines
Deploy open-source and commercial AI security tools (e.g., Lakera, ProtectAI, HiddenLayer) effectively
Integrate MLOps and SecOps to monitor, respond, and remediate threats across GenAI pipelines
Apply cloud-native guardrails via Azure AI Studio and GCP Vertex AI for enterprise-grade compliance and moderation
Ensure traceability, auditability, and compliance with GDPR, HIPAA, and DORA in GenAI deployments
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6686665
udemy ID
24/06/2025
course created date
02/07/2025
course indexed date
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