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Course guide

How to Do & Submit Work

Contents6 sections

Platforms: AWS Academy Learner Lab (the AWS modules + Knowledge Checks — provided through Classroom) + Google Classroom (our worksheets, flags, grades). All offensive work is on the two approved sandboxes only — see ETHICS.md.

How this course is graded (read once): ~40% of your grade is AWS Academy's own auto-graded Learner Lab activities + Knowledge Checks — identical for everyone, run on AWS's machinery. The layer we author and grade on top is the local Docker labs + worksheets + Audit-the-AI in this repo. Both matter; this page covers how to submit our layer.

One-time setup (Lesson 1)

  1. Join the Google Classroom (code given in class) and accept the AWS Academy Learner Lab invite posted there.
  2. Install Docker Desktop + Git, then get this course's repo — the local add-on labs all begin with cd labs/lessonNN-…, so you need it on your own machine:
   git clone https://github.com/nutthakorn7/cloud-infrastructure-security.git
   cd cloud-infrastructure-security

Each add-on lab is then docker compose up. All the reading is also published at learn.zcr.ai/learn/cloud-security/ — no sign-in needed.

  1. Confirm you can start your Learner Lab and reach the AWS console.

Per-lesson — how to do & submit

Do it (in order):

  1. AWS first: complete that lesson's real AWS Academy module + Knowledge Check in your Learner Lab (this is where you learn the actual AWS console/service). AWS grades this part.
  2. Then the local add-on lab: stand up the week's target (cd labs/lesson<NN>-… → docker compose up, per that lab's README) and work the worksheet (labs/lesson<NN>…/worksheet.md): for each task record the payload/command, a screenshot of the result, and a short mitigation. Conceptual lessons (no Docker target) center the Audit-the-AI exercise instead of an exploit.
  3. Capture your lab's flag where the lab mints one (LAB/HYBRID lessons).

Submit → Google Classroom: | Part | What | |------|------| | Worksheet | the completed worksheet exported to PDF (screenshots embedded) | | Flag | the captured FLAG{…} for that lesson (LAB/HYBRID lessons) |

File name: Lesson<NN>_<StudentID>.pdf (e.g. Lesson04_65123456.pdf) Deadline: before the next class session (unless told otherwise). Grading: the rubric in each worksheet; the AWS Knowledge Checks are graded by AWS.

Knowledge Checks & quizzes

  • Weekly knowledge checks run inside the AWS Academy Learner Lab (part of the licensed curriculum) — there is no separate quiz file to submit for those.
  • Any additional in-class quiz is posted in Classroom at quiz time; the form is the submission.

Term work / capstone

  • If a capstone or write-up is assigned, submit it via Google Classroom with an AI-tool usage disclosure (state how you used any AI tool — search, code, translate — "None" is valid).

Rules for every submission

  • Name + Student ID on every file; labs are individual unless a task says otherwise.
  • AI-tool disclosure on worksheets/reports.
  • Late: −10%/day, up to 3 days (see course-plan.md); submit what you have.

Academic Integrity & Anti-Cheating

This is a security course — we practice the same rigor on your own work. Assume your submission is checked.

  • Your flags are unique to you. Each student receives personalized lab flags derived from your student ID. A flag is traceable to the person it was issued to — submitting someone else's flag is detected automatically and counts as a violation for both parties.
  • Your screenshots must show you. Evidence must include a terminal running printf '%s | %s | ' "$(whoami)" '<YOUR-STUDENT-ID>'; date '+%F %T %Z' in the same image as the evidence. When the evidence is a browser page, a DevTools panel or a rendered response, put that terminal beside the browser and capture the whole screen — a cropped window carries nothing that identifies you, and the lab's own output is byte-identical for the whole cohort by design, so the stamp is the only thing that makes the shot yours. Generic or borrowed screenshots are not accepted.
  • Random live checks. You may be asked to reproduce a task or explain your fix live. Answers you can't explain in your own words score zero.
  • Explain, don't copy. Reflection and Audit-the-AI questions are graded on your reasoning about your results.

Allowed: discussing concepts, helping a classmate debug their own setup, using AI tools if disclosed. Not allowed: sharing flags/answers/screenshots, copying a write-up, touching anyone else's Learner Lab.

Violations follow the ethics & academic-integrity policy, the AWS Academy terms, and KOSEN's conduct process.

All lessons in Cloud Infrastructure & Security