Workbooks
In-depth reading material across all cybersecurity domains. Structured into learning paths from beginner to expert.
Generated from 79 content files · 27 free · 52 members · 0 unstated ·0 of them appear on no hand-written card today
🚀 Zero to Hacker
16 workbooksBash Scripting
Shell scripting, conditionals, loops, and automation on Linux.
CTF Beginner's Guide
How CTFs work, common categories, tools, and tips for first-timers.
Cybersecurity Essentials
The CIA triad, threat actors, vulnerability lifecycle, and security frameworks.
Documentation & Reporting
Executive summaries, technical findings, remediation tables, and templates.
HTTP & Web Requests
How HTTP works: methods, headers, cookies, proxies, and Burp basics.
Introduction to Penetration Testing
What pentesting is, legal context, scope, phases, and methodology.
Kali Linux Fundamentals
Kali toolset, configuration, and staying organised during engagements.
Linux for Beginners
Start from zero — navigation, files, permissions, processes, bash basics.
macOS Fundamentals
macOS architecture, filesystem, security model (SIP, Gatekeeper), and the command line.
Networking Deep Dive
TCP/IP, subnetting, DNS, routing, OSI model, and packet analysis.
OSINT & Reconnaissance
Google dorking, Shodan, WHOIS, theHarvester, Maltego, and recon reports.
Pre-Engagement & Setting Up
Scope documents, rules of engagement, and lab environment configuration.
Python Fundamentals
Variables, functions, loops, file I/O, and scripting for automation.
Windows Fundamentals
Windows OS, registry, services, file system, and PowerShell basics.
🕸️ Web Security
5 workbooks🏰 Infrastructure & AD
6 workbooksActive Directory Fundamentals
AD architecture, objects, Kerberos, NTLM, GPOs, and trusts before attacking AD.
Privilege Escalation — Linux & Windows
SUID, sudo, services, tokens, DLL hijacking — complete privesc reference.
Windows Active Directory for Pentesters
Deep dive into AD administration, enumeration, and attack paths.
🛡️ Defensive
7 workbooksDetection Engineering
Writing detection rules, YARA, Sigma, and tuning for low false positive rates.
Digital Forensics & Incident Response
Evidence acquisition, chain of custody, disk and memory forensics fundamentals.
Incident Handling
Incident lifecycle, communication, containment, eradication, and post-mortems.
💣 Exploit Dev
2 workbooks📡 Wireless
1 workbook☁️ Cloud
2 workbooks🌐 Networking
1 workbook🤖 AI Security
18 workbooksAI Literacy: Embeddings and Retrieval
How text becomes numbers, how similarity is computed, and what a RAG pipeline really does to a prompt. Worked by hand in three dimensions, then run for real on a CPU.
AI Literacy: LLM Mechanics
What happens between your prompt and the model's reply: tokenisation, the context window, the decoding loop, and the mechanism behind hallucination and non-determinism.
AI Literacy: The Confusion Matrix and Base Rates
TP/FP/TN/FN, precision and recall, and the base-rate arithmetic that decides whether a detector is useful or useless. Worked on the page, with a napkin method you can use in a meeting.
AI Literacy: Thresholds and Confidence
Threshold sweeps worked by hand, ROC and AUC explained without calculus, and the misconception that causes more misplaced trust in AI output than any other: confidence is not correctness.
Containers for AI Labs: Docker and Compose from Zero
Docker and Compose from zero — images vs containers, volumes, ports, logs, cleanup, and a worked compose.yaml that runs a local model.
Fundamentals of AI
AI vs ML vs DL vs GenAI, supervised vs unsupervised, what a model is as a file on disk, training vs inference, and an honest statement of what this track will not teach you.
Python for AI Work: Environments, Data, and Tests
venv/uv and committed lockfiles, HTTP and JSON, CSV and pandas, scikit-learn as an API only, the chat-completions message shape, and pytest as the grading mechanism.
Reading AI-Written Code: Review from Week One
A repeatable six-question review pass, then six flawed AI-generated snippets with the flaw, the cause, the fix, and a failing test.
Shell and Data Wrangling for AI Work
Terminal, filesystem, permissions, processes and ssh, plus the text-processing verbs used to inspect model output and datasets.
AI Security Essentials: Detection, Segmentation and Model Operations
ML detection and the base-rate problem, AI dev-environment segmentation, SIEM correlation, safe LLM use at work, model backups and drift — for beginners, with three CPU-only labs.
AI Security Essentials: Non-Human Identity and Behavioural Authentication
Non-human identities, the owner/expiry/review rule, agent authority and behavioural authentication, for beginners — with a CPU-only lab that builds a broker refusing to issue a bad credential.
AI Security Essentials: Poisoning, Bias and Governance
Poisoning, bias and AI under GRC, taught from first principles for beginners — with a CPU-only lab in which you backdoor a spam classifier you trained yourself.
AI Security Essentials: Start Here
Orientation for a four-page AI security series for beginners: the four framings that make every later topic recognisable, and a CPU-only Docker lab box you build once and reuse.
AI Governance with the NIST AI Risk Management Framework
The four AI RMF functions, the Generative AI Profile (AI 600-1), and the governance artefacts that turn framework prose into exit codes.
AI Red Teaming: A Methodology
Scope, threat-model, attack, evidence and report an AI system — the discipline, not a list of jailbreak prompts.
Applications of AI in InfoSec
Six real uses of AI in security work, the specific way each one fails, and the control that bounds it.
ISO/IEC 42001: The AI Management System, and How It Meets ISO 27001
AIMS clauses 4–10, the Annex A control themes, the Statement of Applicability as a checked file, and where ISO 27001 stops and 42001 starts.
The EU AI Act After the Omnibus: Who Owes What, and When
Risk tiers, the provider/deployer split, GPAI duties, and the Article 50 transparency rules that are live right now.
💻 Programming
7 workbooksIntroduction to C#
.NET, C# basics, and Windows development context for security work.
Java Fundamentals
Java OOP, JVM, serialisation, and security-relevant Java concepts.
JavaScript Basics
ES6+, DOM, async/await, and security implications of JavaScript.
SQL Fundamentals
SELECT, INSERT, JOIN, subqueries, and understanding SQL for injection attacks.
C++ Fundamentals
Memory management, pointers, and C++ for understanding binary vulnerabilities.
Python for Hackers
Sockets, subprocess, ctypes, pwntools, and offensive Python scripting.
Secure Coding
Input validation, output encoding, and secure SDLC practices.
📚 Other
3 workbooks📈 Guided Tracks
11 workbooksFoundational Incident Response
Complete incident response from detection to lessons learned.
Foundational Threat Hunting
Hypothesis-driven hunting, data sources, TTP mapping, and Elastic/Splunk.
Security Operations & Defensive Analysis
Complete SOC analyst track: detection, response, and documentation.
Advanced AI Red Teaming
Advanced adversarial attacks on AI systems, data poisoning, and model extraction.
Advanced Web Attacks & Exploitation
Advanced techniques: request smuggling, deserialization, prototype pollution, and more.
Advanced Windows Exploitation
Heap exploitation, kernel basics, ROP chains, and 64-bit exploits.
Evasion Techniques & Breaching Defenses
AV evasion, EDR bypass, AppLocker, AMSI bypass, and living-off-the-land.
Penetration Testing with Kali
Full enterprise pentest from external recon to domain dominance.
Secure Java Development
Secure Java coding patterns, OWASP Java guidance, and code review.
Web Attacks with Kali
Complete web attack track: injection, authentication, client-side, and serialisation.
Windows User-Mode Exploit Development
Stack overflows, SEH, egghunters, shellcoding on 32-bit Windows.