cybersecurity-edu — Defensive/Analysis Security Teaching Arsenal
Purpose: Support elite (MSc/PhD) cybersecurity teaching: how attacks work (for defenders), malware analysis, reverse engineering, forensics, detection engineering, CTF, secure coding. All work is analysis/defensive/lab-oriented.
Installed (Python, /usr/bin/python3, verified 2026-06-21)
- Reverse engineering / static:
capstone6.0,unicorn2.1,pefile,lief,flare-capa(capa),r2pipe,rzpipe - Detection/classification:
yara-python4.5 - Memory forensics:
volatility32.28 - Network analysis:
scapy2.7 - CTF / exploitation teaching:
pwntools4.15 (+ ropgadget, pyelftools, vivisect) - Detection engineering:
sigma-cli/pysigma,mitreattack-python(ATT&CK)
Typical workflows
- Malware static triage:
capa <sample>+ YARA rules +pefile/lieffor PE/ELF structure. - Behavioral/dynamic: run sample ONLY inside the isolated Docker/VM lab (see
lab/), capture withscapy/tshark. - Memory forensics:
vol -f mem.raw windows.pslistetc. - Detection authoring: write Sigma rules →
sigma convertto SIEM backends; YARA for file signatures. - CTF teaching:
pwntoolsfor exploit-dev exercises against the lab's intentionally-vulnerable targets.
CLI tools (host VPS, via SSH)
- ✅ Installed on host (2026-06-27):
radare2,nmap,tcpdump. - ⏳ Optional (large / not yet): Ghidra (headless, needs Java ~1GB), Suricata, Zeek, Wazuh — install on host on request.
Lab (isolated training targets) — lab/
Docker Compose for DVWA + OWASP Juice Shop + CTFd on an internal-only network.
Runs on the HOST (the openclaw container has no docker.sock). See lab/README.md.