20 AI-Powered Security Labs
Real tools. Real scenarios. An AI analyst beside you the whole time — analyzing your output, explaining techniques, and guiding your investigation.
Wireshark + AI Traffic Analysis
Capture live packets, analyze protocol distributions, and use AI to flag anomalous flows and identify attack signatures in PCAP files.
AI-Powered SIEM (Splunk)
Build ML-based correlation rules in Splunk, detect brute force and lateral movement patterns in real security logs with AI-assisted query building.
Static Malware Analysis with AI
Analyze suspicious executables using REMnux tools — strings, PE headers, FLOSS, Capa. AI helps interpret indicators and map behavior to MITRE ATT&CK.
Dynamic Malware Analysis + Sandbox
Execute malware in a controlled Flare-VM environment. Monitor processes, registry changes, and network activity. AI synthesizes behavioral IOCs automatically.
Phishing Detection with NLP
Build a Python NLP model that classifies phishing emails with 95%+ accuracy. Use AI to explain why specific emails are flagged and generate detection rules.
Network Anomaly Detection
Use Isolation Forest and Autoencoder models in Python to detect outliers in NetFlow data. AI explains each anomaly's risk score and suggests next steps.
Behavioral Analytics (UEBA)
Profile normal user activity from Windows event logs. Build AI-powered baselines and trigger alerts on insider threat patterns like off-hours access and bulk downloads.
AI Incident Response Automation
Simulate a ransomware incident. AI orchestrates the IR playbook: containment decisions, evidence collection commands, and a full written incident report.
Cloud Security AI Monitoring
Ingest AWS CloudTrail logs and use AI to detect privilege escalation, impossible travel, and credential abuse in real time with automated alert triage.
Deepfake & Social Engineering Defense
Analyze deepfake audio/video samples using open-source detection tools. AI explains manipulation artifacts and builds organizational detection policies.
Vulnerability Triage with AI (Nessus)
Run Nessus scans against Metasploitable. AI prioritizes CVEs by CVSS score, exploit availability, and business impact — generating an executive-ready report.
Active Directory Attack & AI Defense
Execute Kerberoasting and Pass-the-Hash attacks against a lab AD environment. AI detects each attack from Windows event logs and writes Sigma detection rules.
Memory Forensics with Volatility
Analyze a memory dump from a compromised system. Extract running processes, network connections, and injected code. AI identifies malware artifacts and persistence mechanisms.
Disk Forensics & Timeline Analysis
Forensically image a disk, recover deleted files, and build a super-timeline with Plaso/log2timeline. AI correlates artifacts to reconstruct attacker activity.
Reverse Engineering with Ghidra + AI
Decompile a real malware sample in Ghidra. AI explains assembly and decompiled C code, identifies key functions, and maps behavior to MITRE ATT&CK techniques.
AI Threat Intelligence Aggregator
Build a Python tool that pulls OTX, AbuseIPDB, and MISP feeds, then uses AI to surface critical IOCs, cluster threat actors, and prioritize response actions.
Log Analysis & IOC Extraction with AI
Parse Windows Event Logs, Syslog, and web server access logs. AI automatically extracts IOCs, identifies attack patterns, and writes a detection hypothesis.
YARA Rule Writing with AI
Analyze a malware family, identify unique byte patterns and strings, then use AI to write and test YARA detection rules against a sample corpus.
DevSecOps Pipeline Security
Embed SAST (Semgrep), DAST (OWASP ZAP), and AI code review into a GitHub Actions CI/CD pipeline. Block vulnerable builds automatically.
Full SOC Simulation — AI Analyst
Capstone lab: a full-scope attack scenario (initial access → lateral movement → exfiltration). AI triages alerts, coordinates response, and generates the final post-incident report.