<!-- Copyright (c) 2026 defconxt. All rights reserved. -->
<!-- Licensed under AGPL-3.0 — see LICENSE file for details. -->
---
name: analyzing-deepfake-threats
description: >-
  Detect, analyze, and defend against deepfake audio and video used in social engineering attacks.
domain: cybersecurity
subdomain: social-engineering
tags:
  - deepfake
  - ai-threats
  - social-engineering
  - media-forensics
version: "1.0"
author: defconxt
license: AGPL-3.0
metadata:
  mitre-attack: ["T1566"]
---

# Analyzing Deepfake Threats

## Overview

Detect, analyze, and defend against deepfake audio and video used in social engineering attacks.

## Prerequisites

| Requirement | Install |
|---|---|
| FFmpeg | `apt install ffmpeg` |
| ML models | Deepfake detection |
| Python 3.10+ | For agent tooling |

## Key Concepts

Deepfake threats use AI-generated audio/video to impersonate
executives. Detection involves media forensics, artifact analysis,
spectral analysis, and authentication procedures.

## Quick Reference

```bash
node agent.js analyze-audio --file executive-call.wav
node agent.js analyze-video --file board-meeting.mp4
node agent.js voice-match --sample call.wav --baseline ceo-voice.wav
node agent.js assess --incident DF-2026-003
```

## Workflow

1. Receive suspected deepfake
2. Extract streams
3. Spectral analysis
4. Video frame analysis
5. Compare baselines
6. Assess confidence
7. Recommend procedures

## Verification

- Verify audio detects artifacts
- Confirm video identifies inconsistencies
- Validate voice comparison
- Check confidence levels
- Verify procedures prevent attacks

## References

- OWASP Testing Guide — https://owasp.org/www-project-web-security-testing-guide/
- MITRE ATT&CK — https://attack.mitre.org/
- NIST SP 800-53 — https://csf.tools/reference/nist-sp-800-53/
