Kernel Internals and Architecture
Monolithic architecture, major subsystems, user/kernel boundary, system calls, /proc and /sys interfaces, task_struct.
Course preview
A 5-day, 40-hour hands-on training on writing, debugging, hardening, and reviewing production-quality Linux kernel modules with emphasis on the networking subsystem.
Real-world context
Students analyze real rootkit code for networking, hiding, and detection throughout the course — not contrived textbook examples.
Lab-first delivery
Students write real kernel modules from Day 1. Labs build on each other and culminate in a capstone network monitoring LKM.
10 modules across 5 days
From kernel fundamentals to a capstone project. Networking gets a full day. Security runs through every module.
Monolithic architecture, major subsystems, user/kernel boundary, system calls, /proc and /sys interfaces, task_struct.
Module lifecycle, init/exit, parameters, Kbuild, /proc and sysfs interfaces, symbol exports, cross-version compatibility.
Full network stack from NIC to socket layer, sk_buff, Netfilter hooks, connection tracking, kernel TCP/UDP sockets, KoviD case study.
Virtual address space, memory zones, kmalloc/vmalloc/slab, GFP flags, DMA mapping, KASAN, KFENCE, memory pools.
Spinlocks, mutexes, RCU deep dive, per-CPU variables, atomic operations, wait queues, memory barriers, lockdep.
printk, ftrace, kprobes/kretprobes, eBPF and BCC tools, perf and flame graphs, crash analysis, KGDB.
Kernel threat model, buffer and integer overflows, use-after-free, TOCTOU, input validation, capability checks.
Build-time hardening, KASLR, CFI, module signing, kernel lockdown, LSM framework, rootkit detection techniques.
Kernel coding style, checkpatch, sparse, smatch, coccinelle, security-focused review checklist, KUnit testing.
Build a complete Secure Network Monitoring LKM integrating Netfilter, per-CPU counters, RCU, /proc, capability checks.
Before you start
This training assumes working-level Linux and C skills. It is not an introductory course.
Who this is for
Built for teams that work close to the kernel and need practical, lab-verified skills.
Validating Linux detection coverage, building kernel-level visibility, or training engineering teams on module development.
Building detection engineering workflows, understanding rootkit techniques, and hardening kernel configurations.
Running Linux fleets in cloud or on-prem environments and needing kernel-level debugging and hardening skills.
Looking for a serious, lab-heavy curriculum they can deliver to internal teams or training cohorts.
Preview materials
A sample lab, the full environment setup, and how the AI tutor works.
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