Dark › Module 3 › Lesson 1
OPSEC Basics
OPSEC named literacy covers threat modeling, compartmentation, metadata awareness, and need-to-know handoff — draft OPSEC rows on YOUR $DW_LAB fictional scenarios before identity compartment lesson.
Visual · t39_opsec_named
OPSEC named literacy. $DW_LAB only. Original Cyberlium.
Opening
Anonymity tools fail without OPSEC — literacy teaches threat model vocabulary so $DW_LAB notes document what you protect and from whom, not criminal target profiling.
OPSEC — Operations Security — asks who the adversary is, what you protect, what you accept as risk, and how metadata leaks deanonymize even encrypted content. On Cyberlium you practice on fictional scenario rows in YOUR $DW_LAB — lab persona alert stubs, placeholder metadata fields — never real target profiling, doxxing, or victim PII. Cyberlium maps OPSEC named row on YOUR $DW_LAB — threat model summary, compartmentation note, metadata awareness, need-to-know handoff boundary. Next: Identity Compartment.
1. OPSEC components (named)
Threat model: identify adversary, assets to protect, and accepted risks on YOUR fictional scenario. Compartmentation: separate identities, devices, and accounts — lab vocabulary for privacy engineering. Metadata: timing, location, billing, device fingerprints — not just message content. Need-to-know: share minimum for defender handoff through legal channels only.
On $DW_LAB, write OPSEC named row — adversary, asset, metadata field example, handoff boundary.
Command guide
Try these commands — OPSEC components (named)
═══ TOOLS & WEBSITES ═══ Browse / read these (authorized learning only — stay in YOUR lab / program scope)
EFF SSD — https://ssd.eff.org/ Tor Project — https://www.torproject.org/ NIST privacy — https://www.nist.gov/privacy-framework
═══ INSTALL ═══
Linux (Debian/Ubuntu):
Command — copy this
sudo apt install python3
macOS:
Command — copy this
brew install python3
Windows: Download https://python.org/downloads/
═══ LINUX / macOS ═══
Command — copy this
export DW_LAB=${DW_LAB:-$HOME/cyberlium-lab/t39-dw}
cat > "$DW_OPSEC/opsec-named-literacy.txt" <<'EOF'
OPSEC literacy — NAMED rows:
Threat model: who adversary is; what you protect; what you accept
Compartmentation: separate identities, devices, accounts — lab vocabulary
Metadata: timing, location, billing, device fingerprints — not just content
Need-to-know: share minimum for defender handoff — legal channels only
Lab: fictional scenario rows on YOUR notes — not real target profiling
EOFCommand — copy this
grep -E 'Threat model|Metadata|fictional' "$DW_OPSEC/opsec-named-literacy.txt"
python3 -c "print('OPSEC literacy: threat model + metadata on YOUR $DW_LAB notes')"Primary tools to practice this lesson: grep, python3. Reference sites: EFF SSD (https://ssd.eff.org/); Tor Project (https://www.torproject.org/); NIST privacy (https://www.nist.gov/privacy-framework). Run every command in the box — install first, then the usage lines — only on YOUR lab / program scope.
2. Why OPSEC precedes hardened OS literacy
Tails and Whonix address technical isolation — OPSEC addresses behavioral and organizational leaks. Defenders triaging dark-web alerts need metadata vocabulary to scope corroboration without over-collection.
Students draft lab OPSEC rows on notes — production OPSEC follows org policy and authorized monitoring programs.
3. Lab boundary
Forbidden: real target profiling, doxxing exercises, criminal persona research blending with employer credentials. Allowed: OPSEC named card — fictional scenario rows with $DW_LAB FAKE/LAB labels.
Ship: OPSEC named row for YOUR lab notes. Next: Identity Compartment.
4. What you ship: OPSEC named row for $DW_LAB
Threat model, compartmentation, metadata, need-to-know. $DW_LAB named. chmod 600.
5. What you record before the next lesson
Date. OPSEC named row. $DW_LAB named. File t39-m03-l01-opsec-named.txt chmod 600.
6. Wrong vs right: criminal markets vs YOUR OPSEC lab
Worked failure — same MSF word, opposite target. Right never needs a café Wi-Fi or classmate laptop.
Wrong
Profile real individuals for OPSEC lab exercise. Skip adversary definition because 'it's obvious.'
Right
Write OPSEC named row for fictional scenario on YOUR $DW_LAB. Next: Identity Compartment.
Mission: draft OPSEC vocabulary on YOUR lab notes
1) Name adversary and asset in fictional scenario. 2) Write one metadata leak example. 3) Add need-to-know handoff boundary. 4) chmod 600.
Stuck? Ask Cyberlium AI Mentor
OPSEC rows use fictional scenarios — not real people or victim data.
Knowledge Check
APPLY: OPSEC named literacy on Cyberlium primarily:
Multiple choice
Knowledge Check
APPLY: True or False: Metadata includes timing, location, and billing — not just message content.
True or False
Knowledge Check
APPLY: OPSEC literacy on Cyberlium uses:
Multiple choice