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BeginnerModule 4Lesson 4/5

Lab — AWS Data

Pack S3 hygiene, CloudTrail, and GuardDuty cards — AWS data and logging file from $CLOUD_LAB only.

25 min+40 XP3 quiz
Module progress4 of 5

Visual · t31_aws_data_lab

Lab: AWS data pack. $CLOUD_LAB only. Original Cyberlium.

Opening

AWS data pack merges storage hygiene to audit trail to detection — paperwork before Azure module.

Lessons 4-1–4-3 named S3 hygiene, CloudTrail enablement, and GuardDuty triage. This lab merges three sections into one $CLOUD_LAB AWS data artifact with M1 ethics cross-reference. No stranger bucket or account work — data and logging literacy paperwork only. Next: Quiz — AWS Data and Logging.

1. Lab contract: AWS data and logging pack

Create $HOME/cyberlium-lab/t31-m04-l04-aws-data-lab.txt merging S3, CloudTrail, and GuardDuty sections with $CLOUD_LAB account ID and M1 ethics cross-reference.

Optional: note BPA status from sandbox console read-only — no bucket policy secrets.

Command guide

Try these commands — Lab contract: AWS data and logging pack

═══ TOOLS & WEBSITES ═══ Browse / read these (authorized learning only — stay in YOUR lab / program scope)

S3 API — https://docs.aws.amazon.com/cli/latest/reference/s3api/ CloudTrail CLI — https://docs.aws.amazon.com/cli/latest/reference/cloudtrail/ AWS security hub — https://docs.aws.amazon.com/securityhub/

═══ INSTALL ═══

Linux (Debian/Ubuntu):

Command — copy this

pipx install awscli  # or official AWS CLI v2

macOS:

Command — copy this

brew install awscli

Windows: Install AWS CLI v2 from Amazon

═══ LINUX / macOS ═══

Command — copy this

export CLOUD_LAB=${CLOUD_LAB:-$HOME/cyberlium-lab/t31-cloud}

YOUR ACCOUNT — S3 + logging lab (read-only on buckets you own)

Command — copy this

aws sts get-caller-identity
aws s3api list-buckets --query 'Buckets[].Name' --output text 2>/dev/null | tr '	' '
' | head -5 || echo 'List buckets in YOUR account only'
aws s3api get-public-access-block 2>/dev/null || echo 'Check Block Public Access in YOUR account'
aws cloudtrail describe-trails --query 'trailList[].Name' 2>/dev/null || echo 'CloudTrail review YOUR account'
grep -E 'S3|CloudTrail|NEVER' "$CLOUD_LAB/aws/s3-hygiene-checklist.md" "$CLOUD_LAB/aws/cloudtrail-checklist.md"

═══ WINDOWS ═══

YOUR ACCOUNT — AWS data lab

Command — copy this

aws sts get-caller-identity
Get-Content $HOME/cyberlium-lab/t31-cloud/aws/s3-hygiene-checklist.md | Select-String Block

Primary tools to practice this lesson: aws, grep. Reference sites: S3 API (https://docs.aws.amazon.com/cli/latest/reference/s3api/); CloudTrail CLI (https://docs.aws.amazon.com/cli/latest/reference/cloudtrail/); AWS security hub (https://docs.aws.amazon.com/securityhub/). Run every command in the box — install first, then the usage lines — only on YOUR lab / program scope.

2. Cross-check ethics

Grep for stranger bucket URLs, access keys, bucket scanner commands — remove. Pack labels all artifacts as $CLOUD_LAB training only.

Confirm S3 section has no steps targeting stranger storage.

3. Lock the proof

chmod 600 on the pack. Quiz next — then Azure Defender Named.

AWS data literacy feeds Azure lessons in M5.

4. What you ship: AWS data and logging pack for $CLOUD_LAB

Merged S3, CloudTrail, GuardDuty sections. $CLOUD_LAB named. NO stranger buckets. chmod 600.

5. What you record before the next lesson

Date. AWS data pack path. $CLOUD_LAB named. File t31-m04-l04-aws-data-lab.txt chmod 600.

6. Wrong vs right: stranger tenants vs YOUR cloud accounts

Worked failure — same MSF word, opposite target. Right never needs a café Wi-Fi or classmate laptop.

  • Wrong

    Include stranger S3 object URL in pack. Skip CloudTrail section.

  • Right

    Write YOUR AWS data pack for $CLOUD_LAB. chmod 600. Next: Quiz — AWS Data and Logging.

Mission: freeze YOUR AWS data and logging pack

1) Merge M4 literacy sections. 2) Confirm zero stranger refs. 3) Link M1 ethics cross-ref. 4) chmod 600.

Stuck? Ask Cyberlium AI Mentor

One governed data pack beats ten public bucket screenshots.

Knowledge Check

1

APPLY: This lab requires:

Multiple choice

Knowledge Check

2

APPLY: True or False: AWS data pack must label scenarios as $CLOUD_LAB training only.

True or False

Knowledge Check

3

APPLY: S3 hygiene in pack feeds:

Multiple choice

← Previous

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