AI › Module 5 › Lesson 2
Deepfake Detection
Deepfake detection literacy names synthetic media signals, verification habits, and fraud context — defender skills on YOUR $AI_LAB notes, not deepfake fraud kits.
Visual · t32_deepfake_detection
Deepfake detection literacy. $AI_LAB only. Original Cyberlium.
Opening
Seeing is not believing — literacy names deepfake detection so you verify high-risk media, not build fraud impersonation kits.
Deepfakes synthesize face, voice, or video to impersonate executives, family, or public figures — used in fraud, disinformation, and extortion. Detection signals: lip-sync mismatch, unnatural blinking, audio spectral artifacts, metadata gaps, and out-of-band verification. Defender fix: callback policies, multi-factor approval for wire transfers, and media forensics tools — literacy only; NO deepfake fraud kit building on Cyberlium. Cyberlium writes deepfake detection card on YOUR $AI_LAB — analyze labeled courseware clips or fictional indicators on paper. Next: AI Malware Named.
1. Deepfake detection signals (named)
Visual: lip-sync drift, lighting inconsistency, edge artifacts around face. Audio: robotic cadence, missing breath sounds, clone mismatch on uncommon words. Process: verify via second channel — call back on known number, not callback number in message.
On $AI_LAB, write detection checklist — five signals and one out-of-band verification step for fictional exec-voice scenario.
Command guide
Try these commands — Deepfake detection signals (named)
═══ TOOLS & WEBSITES ═══ Browse / read these (authorized learning only — stay in YOUR lab / program scope)
CISA deepfake guidance — https://www.cisa.gov/ai NIST AI RMF — https://www.nist.gov/itl/ai-risk-management-framework MITRE ATLAS — https://atlas.mitre.org/
═══ INSTALL ═══
Linux (Debian/Ubuntu):
Command — copy this
sudo apt install python3
macOS:
Command — copy this
brew install python3
Windows: Download https://python.org/downloads/
═══ LINUX / macOS ═══
Command — copy this
export AI_LAB=${AI_LAB:-$HOME/cyberlium-lab/t32-ai}
cat > "$AI_LAB/threats/deepfake-detection-signals.md" <<'EOF'
# Deepfake Detection Signals (literacy — no creation steps)
- Video: lip-sync mismatch, unnatural blinking, hair/ear artifacts
- Audio: robotic cadence, missing breath sounds, spectral clipping
- Metadata: unknown encoder, reverse image search hits
- Process: verify identity via second channel; policy for wire transfers
HARD BAN: deepfake creation for fraud or impersonation kits
EOFCommand — copy this
grep -E 'Detection Signals|HARD BAN|lip-sync' "$AI_LAB/threats/deepfake-detection-signals.md"
python3 -c "print('Deepfake literacy: detection only — never fraud creation')"Primary tools to practice this lesson: grep, python3. Reference sites: CISA deepfake guidance (https://www.cisa.gov/ai); NIST AI RMF (https://www.nist.gov/itl/ai-risk-management-framework); MITRE ATLAS (https://atlas.mitre.org/). Run every command in the box — install first, then the usage lines — only on YOUR lab / program scope.
2. Why verification policy beats pixel hunting alone
Detection ML arms race continues — organizations enforce 'no wire transfer from voice note alone' and executive callback lists. Analysts document indicators for awareness training with redacted fictional media — not live fraud deployment.
Students refuse deepfake fraud kit tutorials — detection and policy literacy only.
3. Literacy ≠ deepfake fraud kits
Forbidden: building voice-clone fraud kits, impersonating real executives for transfer requests, or distributing synthetic media of real people without consent. Allowed: deepfake detection card — signals, verification policy, fictional scenario on $AI_LAB.
Ship: deepfake detection card for YOUR lab notes. Next: AI Malware Named.
4. What you ship: deepfake detection card for $AI_LAB
Five signals, verification policy, fictional scenario. $AI_LAB named. NO fraud kits. chmod 600.
5. What you record before the next lesson
Date. Deepfake detection card. $AI_LAB named. File t32-m05-l02-deepfake-detection.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
Build voice-clone kit to call real finance team. Skip out-of-band verification in policy notes.
Right
Write deepfake detection card for YOUR $AI_LAB. Next: AI Malware Named.
Mission: write deepfake detection on YOUR lab
1) List five detection signals. 2) Write one verification policy step. 3) Describe fictional exec-voice scenario (training only). 4) chmod 600.
Stuck? Ask Cyberlium AI Mentor
Call back on a number you already trust — not the number the urgent voice message gives you.
Knowledge Check
APPLY: Deepfake detection on Cyberlium focuses on:
Multiple choice
Knowledge Check
APPLY: True or False: Out-of-band verification on a known number reduces voice-clone fraud risk.
True or False
Knowledge Check
APPLY: Deepfake literacy avoids:
Multiple choice