Lab — Data Apps
Pack classification, app wrapping, DLP — data pillar file from $ZT_LAB data folder.
Visual · t40_data_apps_lab
Lab: data pillar pack. $ZT_LAB only. Original Cyberlium.
Data pack merges classification matrix, app delivery table, and DLP stub — data-centric ZT slice for LAB-ZT-001 capstone.
Merge M7 lessons into data-pillar-pack.md with diagram: User → App (wrapped) → Data tier → DLP enforce. Cross-link M6 ZTNA app path and M8 policy engine. No real PII, exfil tools, or employer DLP export. Next: Quiz — Data and Apps.
1. Lab contract: data pillar pack
data-pillar-pack.md: classification + app wrapping + DLP + data-flow diagram.
LAB SAMPLE label; placeholder data only.
Command guide
Try these commands — Lab contract: data pillar pack
═══ TOOLS & WEBSITES ═══ Browse / read these (authorized learning only — stay in YOUR lab / program scope)
CISA ZTMM Data — https://www.cisa.gov/zero-trust-maturity-model NIST SP 800-207 — https://csrc.nist.gov/publications/detail/sp/800-207/final
═══ INSTALL ═══
Linux (Debian/Ubuntu):
Command — copy this
sudo apt install python3
macOS:
Command — copy this
brew install python3
Windows: Download https://python.org/downloads/
═══ LINUX / macOS ═══
Command — copy this
export ZT_LAB=${ZT_LAB:-$HOME/cyberlium-lab/t40-zt}
export ZT_DATA=${ZT_DATA:-$ZT_LAB/LAB-ZT-001/data}
cat > "$ZT_DATA/data-pillar-pack.md" <<'EOF'
# Data Pillar Pack — LAB-ZT-001
Includes: classification-matrix.csv, app-wrapping-table.md, dlp-policy-stub.md
```
User → App (wrapped) → Data tier → DLP enforce point
```
Cross-ref: M6 ZTNA app path, M8 PDP data attribute input
Refused: exfil tools; real customer data
LAB SAMPLE — NOT FOR PRODUCTION ARCHITECTURE CLAIMS
EOFCommand — copy this
grep -E 'Data Pillar|DLP enforce|Refused|LAB SAMPLE' "$ZT_DATA/data-pillar-pack.md" cat > "$ZT_LAB/notes/data-apps-lab-summary.md" <<'EOF' # Data Apps Lab Summary — YOUR lab - classification + app wrapping + DLP aligned by tier ## Refusals - No exfil scripts; placeholder data only EOF
Command — copy this
grep -E 'Refusals|classification' "$ZT_LAB/notes/data-apps-lab-summary.md" wc -l "$ZT_DATA/data-classification-matrix.csv"
═══ WINDOWS ═══
Command — copy this
Get-Content $HOME/cyberlium-lab/t40-zt/LAB-ZT-001/data/dlp-policy-stub.md | Select-String DLP-001
Primary tools to practice this lesson: grep, python3. Reference sites: CISA ZTMM Data (https://www.cisa.gov/zero-trust-maturity-model); NIST SP 800-207 (https://csrc.nist.gov/publications/detail/sp/800-207/final). Run every command in the box — install first, then the usage lines — only on YOUR lab / program scope.
2. Cross-check
Grep real emails, PAN, SSN patterns, exfil keywords — remove.
Link Restricted tier to isolation and DLP rows consistently.
3. Lock
chmod 600. Quiz next — PEP PDP Named.
Data pack feeds policy engine data attributes in M8.
4. What you ship: data pillar pack
Merged data artifacts in LAB-ZT-001/data/. $ZT_LAB. chmod 600.
5. What you record before the next lesson
Date. Data pack path. $ZT_LAB named. File t40-m07-l04-data-apps-lab.txt chmod 600.
6. Wrong vs right: bypass cookbooks vs YOUR ZT design
Worked failure — same MSF word, opposite target. Right never needs a café Wi-Fi or classmate laptop.
- Wrong: Include sample exfil Python script. Paste employer DLP incident export.
- Right: Write data pillar pack for $ZT_LAB. Next: Quiz — Data and Apps.
Mission: data pillar pack
1) Merge M7 sections. 2) Data-flow diagram with DLP point. 3) Tier consistency check. 4) chmod 600.
Stuck? Ask Cyberlium AI Mentor
Classification → app delivery → DLP is the data pillar story arc.
APPLY: Data lab pack includes:
APPLY: True or False: Restricted tier links to stronger isolation and DLP.
APPLY: Data lab refuses: