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BeginnerModule 7Lesson 1/5

Data Classification

Data-centric ZT literacy — classify data, label sensitivity, map to access policies — classification matrix on YOUR $ZT_LAB data folder.

15 min+40 XP3 quiz
Module progress1 of 5

Visual · t40_data_classification

Data classification. $ZT_LAB. Original Cyberlium.

Opening

ZT protects data — not just networks — label Public/Internal/Confidential/Restricted rows on LAB-ZT-001 data inventory.

Data classification tiers drive encryption, DLP, sharing, and microseg rules. Map fictional datasets: customer PII placeholder, finance reports, source code, public marketing — to tiers and handling rules. No real customer data in lab. Write classification matrix with owner and control column. Next: App Wrapping.

1. Classification tiers (named)

Public: no harm if disclosed. Internal: org-only. Confidential: limited need-to-know. Restricted: regulated/high impact (PII/PCI placeholders literacy).

Each tier links to encryption, sharing, retention checklist rows.

Command guide

Try these commands — Classification tiers (named)

═══ 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-classification-matrix.csv" <<'EOF'
dataset_id,name,tier,owner,storage_stub,controls
DS-001,Public marketing site,Public,Marketing,web-cdn,integrity-check
DS-002,Internal wiki,Internal,IT,share-internal,access-control
DS-003,Customer account PII placeholder,Confidential,Product,saas-db,encrypt+DLP-audit
DS-004,Finance reports,Confidential,Finance,erp-vault,encrypt+limited-share
DS-005,Payment flow placeholder,Restricted,Compliance,payment-segment,encrypt+DLP-block+PCI-literacy
DS-006,Source code repo,Confidential,Engineering,git-saas,SSO+branch-protection
EOF

Command — copy this

grep -E 'dataset_id|Restricted|Confidential|DS-00' "$ZT_DATA/data-classification-matrix.csv"
python3 -c "print('Classification: placeholder data only — no real PII/PAN')"

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. Labeling literacy

Manual labels, MIP/AIP sensitivity labels, metadata tags in cloud storage literacy. Labels feed DLP and CASB policies in M7 L3.

Unlabeled data = policy gap on stub — document remediation.

3. Lab matrix

Ten fictional datasets with tier, owner, storage location stub, required controls.

Ship: data classification matrix. Next: App Wrapping.

4. What you ship: data classification matrix

Ten fictional datasets with tiers and controls. $ZT_LAB placeholders only. chmod 600.

5. What you record before the next lesson

Date. Classification matrix. $ZT_LAB named. File t40-m07-l01-data-classification.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

    Import real customer CSV into lab matrix. Mark everything Public for simplicity.

  • Right

    Write classification matrix with Restricted tier example. Next: App Wrapping.

Mission: data classification matrix

1) Define four classification tiers. 2) List ten fictional datasets. 3) Map control requirements per tier. 4) chmod 600.

Stuck? Ask Cyberlium AI Mentor

Restricted tier row forces encryption + DLP link — do not skip.

Knowledge Check

1

APPLY: Data classification drives:

Multiple choice

Knowledge Check

2

APPLY: True or False: Unlabeled sensitive data is a ZT policy gap.

True or False

Knowledge Check

3

APPLY: Classification matrix uses:

Multiple choice

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Answer all 3 knowledge checks to continue. (0/3 answered)