AI for Ethical Hacking & Cybersecurity (2026)

Set up a Kali Linux virtual lab using Oracle VirtualBox and the Kali ISO. Allocate RAM, CPUs, and disk, use Debian 64-bit, and complete guided partitioning with grub.

Explore how to craft effective ChatGPT prompts to explain security concepts, generate safe commands or scripts, analyze logs, and simulate learning attacks, guided by golden rules for ethical hacking.

Learn to craft good prompts for ChatGPT in ethical hacking, perform safe host discovery on a lab subnet, and run focused nmap scans with clear output formats.

Discover few-shot prompting to produce consistent incident notes, summarize logs, and rewrite aggressive commands into safe alternatives for security tasks in a lab setting.

Combine terminal commands with ChatGPT prompts to create a prioritized, safe privilege escalation triage plan and benign validation commands, using outputs from whoami, id, sudo -l, and tool paths.

Learn to perform vulnerability scanning with Nikto on a web app, parse results with ChatGPT, and generate a ten-line prioritized, benign verification checklist (curl tests, x-frame-options header) for ethical hacking.

Learn detection engineering from weblogs using ChatGPT to identify sql injection attempts in Apache logs and generate sigma-style yaml rule and a bash one-liner to extract timestamp, ip, and url.

Learn to use ChatGPT to generate a hardened sshd_config for a lab, produce a unified diff, outline minimal changes, and validate safely with non-disruptive syntax checks.

Explore prompt injection and jailbreaking, learn attacker techniques to bypass AI guardrails, identify indicators, and apply layered defenses, input validation, and monitoring to safely test AI systems.

Explore direct prompt injection techniques using the Gandalf Lakara AI game to reveal passwords across escalating levels, practicing defenses and bypass strategies in a hands-on ethical hacking lab.

Explore indirect prompt injection in ChatGPT, showing how HTML comments, CSV data, and user prompts can override instructions, expose the system node, and compromise model behavior.

Practice defensive prompting to harden prompts against injection attacks, using blue team guardrails, untrusted content rules, and testing with HTML, CSV, and markdown in a hands-on prompt injection defense.

Conduct an AI‑augmented penetration test with ChatGPT as your partner, from reconnaissance to exploitation on Metasploitable 3, including SMB enumeration and EternalBlue testing.

Set up shell GPT in the terminal by generating and saving your OpenAI API key, installing dependencies, and using the command line to run and even execute prompts and commands.

Explore how shell GPT automates hacking tasks from analyzing vulnerabilities and crafting post-exploitation scripts to producing phishing payloads and triggering reverse shells, with nmap scans and msf console exploits.

Use shell GPT to run reconnaissance with nmap, analyze results for vulnerabilities and CVEs, explore exploits in Metasploit, and generate payloads like a Python reverse shell.

Apply Python-based machine learning to automate penetration testing from reconnaissance to exploitation, building AI tools for fingerprinting, web host and subdomain discovery, and payload generation.

Learn to set up a Python project, install machine learning libraries, and train a model that classifies IP activity as suspicious or normal based on behavior.

Build a machine learning pipeline to detect normal versus suspicious IP activity from an IP CSV, using label encoding, port count, average time between connections, and a decision tree classifier.

Train a malicious bash command detector from dataset.csv using tf-idf vectorization and a random forest classifier; learn from command and label columns and test new inputs.

Explore how a transformer-based text classification pipeline flags prompts as negative or positive, showing the limits of sentiment models for security and introducing a security-detection approach.

Use Python and lang chain to automate reconnaissance with OpenAI chat models, building a subdomain finder and interpreting scan results while securely managing the OpenAI API key.

Use AI with search results to locate PDFs for reconnaissance, then read, extract, and summarize key content with a Chat OpenAI model.