Deepfake Detector

Deepfake Detector is an AI tool for checking whether an image, video, or audio clip has been manipulated using AI techniques like face swapping, voice cloning, or text-to-image generation. You upload the media to the web interface and get back a confidence score indicating how likely the content is to be a deepfake. It's aimed at journalists, trust and safety teams, HR departments, and individuals verifying suspicious content.

No detector is 100% accurate, and accuracy varies by generation technique and media quality. Modern detectors typically achieve 85–95% accuracy on well-known deepfake datasets, but performance drops on novel generation methods, heavily compressed media, and adversarially crafted content. Always treat detection results as one signal among several — not a definitive verdict. Human review remains essential for high-stakes decisions.

Many modern detectors, including Deepfake Detector, are trained to recognize images generated by Stable Diffusion, Midjourney, DALL-E, Flux, and other popular models. Accuracy is higher for unmodified outputs and lower for heavily edited or re-rendered images. As generation models improve, detection models need continuous updates to keep up — this is an ongoing cat-and-mouse game in the AI safety research community.

Yes — there's typically a free tier with limited daily uploads that's suitable for individuals casually verifying suspicious content. Paid tiers unlock higher volume, API access for programmatic scanning, faster processing, and enterprise features like bulk upload and compliance reporting. Always check the current pricing page for exact quotas.

Yes — audio deepfake detection is one of the modalities supported. Upload a voice recording and the tool analyzes it for signs of AI generation or voice cloning. Detection is particularly important as voice cloning has become trivially easy to do with tools like ElevenLabs, Play.ht, and open-source models, and phone scams using cloned voices have become a real threat in 2024–2026.

Yes — that's one of the primary use cases. Newsrooms often run suspicious viral videos, photos, and audio through deepfake detection as part of their verification workflow, alongside traditional techniques like reverse image search, metadata analysis, and source contact. Detection is one tool in a broader verification toolkit — not a replacement for editorial judgment or human expertise.

Paid tiers typically include API access so trust and safety teams can scan incoming media at scale, journalists can build custom verification pipelines, and enterprise customers can integrate detection into existing content moderation workflows. Check the current API documentation for supported media formats, rate limits, and authentication.

Reality Defender is a well-funded enterprise deepfake detection company that targets governments, large enterprises, and financial institutions with a more complex product suite. Deepfake Detector sits at a more accessible price point and is easier for individuals and small teams to try. For enterprise-grade compliance and dedicated infrastructure, Reality Defender is usually the stronger fit; for casual or mid-sized use, Deepfake Detector is simpler.