

Instructor-Led Training
Live, instructor-led sessions with hands-on labs and direct access to instructors.
AI Security, AppSec, Cloud & Container Security, and DevSecOps through hands-on labs and real-world scenarios.
What Our Trainings Cover
Multiple Tracks
Choose your training
Live
Real-time interaction
Small Cohorts
Direct instructor access
Hands-on Labs
Browser-based, no setup
Who Should Take This Course
Student Requirements
Read the prerequisites before you book.
Some trainings require you to bring your own cloud account (AWS, GCP, or both) with billing enabled and admin privileges. Labs will not run without it, so confirm you meet every prerequisite below before the session.
Hard requirement for corporate laptops: admin permission to install tools, endpoint security and antivirus disabled, and the required lab domains not blocked on your network. Confirm this with your IT team before you register - troubleshooting a locked-down laptop mid-session is not possible.
Note: each participant must bring their own AWS account (with billing and admin privileges). This gives you isolated access to your own EKS cluster for running attack and defense labs safely.
Prerequisites
Additional Benefits
Post-Training Support
Lifetime access to Slack community for ongoing support and networking
Hands-on Lab Resources
Access to all lab resources and exercises for continued practice
Interview Question Guide
Comprehensive guide with common interview questions and answers
All Trainings
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Practical Security Engineering for Tech Teams
OWASP Top 10, Containers, DevSecOps, AWS Security, AI Security & AI-Assisted Security Reviews. 46 hands-on labs across 10 sections, run live over two days in browser-based labs. No local setup, no VM, no fight with a corporate laptop.
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Hands-on
Practical Kubernetes Attack Defense Training
Escape containers, enumerate a cluster and steal secrets, then harden it with RBAC, network policy, admission control, service mesh and runtime detection. Finish with CIS Kubernetes Benchmark audits, HashiCorp Vault secret management and Falco threat detection in production.
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Hands-on
AWS Attack & Defend Security for Startups
The AWS mistakes small teams actually ship: over-permissive IAM, public S3, exposed metadata and long-lived keys. Attack each one, fix it without a platform team, then close with the AWS Security Agent and Bedrock AI security.
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Workshop
Ace Your Cloud Security Interview with Hands-on Assignment
In this hands-on workshop, you'll tackle real-world AppSec scenarios through interactive mock interviews. Practice explaining OWASP Top 10 findings, cloud misconfigurations and secure code review out loud, and get direct feedback on how you would perform in a live technical round.
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Hands-on
Offensive Container Security
Break out of a container, then close every door you just walked through: namespaces, capabilities, and the image layers attackers dig through. Lock it down again with SBOM generation, image CVE scanning with Trivy, and secure Dockerfile defaults you can take back to your own pipeline.
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Hands-on
AWS EKS Security Masterclass with OWASP EKS Goat
Attack a deliberately vulnerable EKS cluster with OWASP EKS Goat: lift credentials via IMDSv2, enumerate ECR and backdoor an image, then break out from pod to node. Apply the RBAC, network policy and GuardDuty fixes that would have stopped you.
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Hands-on
Offensive EKS & GKE: Breaking & Defending Managed Kubernetes
Break EKS and GKE through registry and IAM misconfigurations, then defend with IRSA, Workload Identity, Kyverno, Tetragon and Falco. Compare the two clouds' managed Kubernetes attack surface side by side, and leave with policy-as-code guardrails for both.
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Hands-on
Hack and Defend Google Kubernetes Engine (GKE)
Exploit real GKE misconfigurations across IAM, Workload Identity, and Artifact Registry, then defend with least privilege and runtime detection. Walk the same kill chain an attacker would inside a real GCP project, from a leaked service account key to cluster-admin.
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Hands-on
Hands-On AI, LLM & MCP Red Teaming
Red team the AI surface: prompt injection, RAG poisoning, and the tool-use and MCP paths that turn a model into a foothold. Then put the guardrails back: least-privilege tool scoping, input and output filtering, and monitoring built for LLM applications.
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