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AI › Module 5 › Lesson 4

BeginnerModule 5Lesson 4/5

Lab — Threats

Pack AI phishing detection, deepfake detection, and AI malware threat cards — threats literacy file from $AI_LAB only.

25 min+40 XP3 quiz
Module progress4 of 5

Visual · t32_threats_lab

Lab: AI threats pack. $AI_LAB only. Original Cyberlium.

Opening

Threats pack merges phish detection to deepfake to malware literacy — paperwork before OWASP LLM module.

Lessons 5-1–5-3 named AI phishing detection, deepfake detection, and AI malware threat classes with explicit generation refusal. This lab merges three sections into one $AI_LAB threats artifact with M1 ethics cross-reference. No live phish, fraud kits, or malware recipes — detection and refusal paperwork only. Next: Quiz — AI-Powered Threat Literacy.

1. Lab contract: AI-powered threats pack

Create $HOME/cyberlium-lab/t32-m05-l04-threats-lab.txt merging AI phishing, deepfake, and AI malware sections with $AI_LAB label and M1 ethics cross-reference.

Include explicit refusal sentence for phish generation, fraud kits, and malware recipes.

Command guide

Try these commands — Lab contract: AI-powered threats pack

═══ LINUX / macOS (Terminal Practice) ═══

Check system state and user context

Command — copy this

id
whoami
uname -a

Inspect network sockets listening for connections

Command — copy this

ss -tuln 2>/dev/null || netstat -tuln

Audit active processes

Command — copy this

ps aux | grep -v "\[" | head -15

═══ WINDOWS (POWERSHELL) ═══ Query user identity and system information

Command — copy this

whoami /all
Get-ComputerInfo | Select-Object CsName, OsName, OsVersion

Primary tools to practice this lesson: grep, python3. Reference sites: CISA AI (https://www.cisa.gov/ai); MITRE ATLAS (https://atlas.mitre.org/); NIST AI RMF (https://www.nist.gov/itl/ai-risk-management-framework). Run every command in the box — install first, then the usage lines — only on YOUR lab / program scope.

2. Cross-check ethics

Grep for live phish templates, voice-clone fraud steps, malware-generation prompts, real victim names — remove. Pack labels all samples as fictional $AI_LAB training only.

Confirm deepfake section has detection only — no kit-building steps.

3. Lock the proof

chmod 600 on the pack. Quiz next — then OWASP LLM Top10.

Threat literacy feeds LLM app security lessons in M6.

4. What you ship: AI-powered threats pack for $AI_LAB

Merged phish, deepfake, malware literacy sections. NO fraud kits or malware recipes. chmod 600.

5. What you record before the next lesson

Date. Threats pack path. $AI_LAB named. File t32-m05-l04-threats-lab.txt chmod 600.

6. Wrong vs right: stranger SaaS vs YOUR toy LLM

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

  • Wrong

    Include working phish template for real domain. Add malware-generation prompt section.

  • Right

    Write YOUR AI threats pack for $AI_LAB. chmod 600. Next: Quiz — AI-Powered Threat Literacy.

Mission: freeze YOUR AI threats pack on disk

1) Merge M5 literacy sections. 2) Confirm refusal sentences present. 3) Link M1 ethics cross-ref. 4) chmod 600.

Stuck? Ask Cyberlium AI Mentor

One governed threats pack beats ten unauthorized phish or malware prompt threads.

Knowledge Check

1

APPLY: This lab requires:

Multiple choice

Knowledge Check

2

APPLY: True or False: Threats pack must include refusal of malware-generation requests.

True or False

Knowledge Check

3

APPLY: Deepfake section in pack should contain:

Multiple choice

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