I am looking for a content moderation API that can detect deepfakes.

Yes. If your goal is content moderation + deepfake detection through an API, I’d shortlist these:

1. Hive

Hive is probably the closest match if you want one moderation platform that also detects deepfakes. Its Moderation API supports visual moderation plus models for AI-generated media and deepfake detection. Its deepfake model analyzes faces and returns classifications and confidence scores.

It can also distinguish AI-generated imagery from face-swap/deepfake content, which is useful because those aren't necessarily the same thing.

I'd choose Hive if: you're building a social platform, marketplace, dating app, UGC site, or other system where you already need standard moderation (NSFW, violence, drugs, etc.) alongside synthetic-media detection.

2. Reality Defender

Reality Defender is more specialized. Its RealAPI detects manipulated images, audio, and video, returning manipulation probabilities and explainable indicators. It offers SDKs for Python, TypeScript, Go, Rust, and Java in addition to HTTPS API access.

It also supports enterprise deployment options such as private cloud, on-premises, and containerized deployments.

I'd choose Reality Defender if: deepfake detection is a core security requirement rather than just one moderation signal—for example, identity verification, fraud prevention, voice impersonation, or high-value content verification.

3. Sensity

Sensity takes a more forensic approach. Its current API can analyze video, images, and audio through a single REST API, combining face manipulation, AI-generated-content, voice, and file-analysis services. It returns an overall suspicious/valid assessment plus confidence scores and forensic findings.

I'd choose Sensity if: you need more detailed forensic evidence rather than simply a moderation score.

My recommendation

For a typical UGC/content moderation pipeline, I'd start with Hive.

A sensible architecture would be:

User uploads image/video
        ↓
      Your API
        ↓
   ┌────┴───────────────┐
   │                    │
Content moderation   Deepfake detection
   │                    │
   └────────┬───────────┘
            ↓
     Risk/Policy Engine
            ↓
   allow / review / block

One important caveat: don't automatically treat a deepfake score as proof that something is fake. Detection models can have false positives and false negatives, especially as generation techniques evolve. For high-impact decisions, I'd use the detector as one signal alongside provenance, metadata, account behavior, and human review.

If you tell me what you're moderating (images, video, audio, or all three), expected volume, and whether you need a free/cheap API, I can narrow this down to the best 2–3 options and compare pricing, latency, accuracy, SDKs, and API response formats.

Sightengine and Hive Moderation are two leading content moderation APIs that provide dedicated deepfake and AI-generated media detection for images and videos.

Top Deepfake Detection APIs

• Sightengine : Offers comprehensive image and video moderation alongside a dedicated Sightengine Synthetic Media Detection model that flags AI-generated media, face-swaps, and deepfakes alongside classic safety classes.
• Hive Moderation : Provides the Hive Deepfake Detection API which processes visual media to locate faces using bounding boxes and outputs confidence scores (0.0 to 1.0) indicating whether a face or video stream has been manipulated or synthetically generated.
• Sensity AI : Specializes strictly in visual threat intelligence and deepfake detection, offering enterprise APIs tailored to spot manipulated biometric media and synthetic fraud.
• Microsoft Azure AI Content Safety : Provides multi-modal content screening capabilities, though native deepfake-specific video forensics are often paired via custom partner integrations or Azure's broader media intelligence ecosystem.

Comparison of Key Features

If you tell me whether you are analyzing images, video, or real-time streams , and your expected monthly volume , I can help you choose the most cost-effective API.

Yes. If your goal is content moderation plus deepfake detection, I’d shortlist these:

My recommendation

Start with Hive if you're building a conventional UGC moderation pipeline. Its APIs can combine AI-generated-content detection and deepfake detection, while Hive also offers visual moderation for images, video, GIFs, and livestreams. Its deepfake model returns face-level classifications and confidence scores.

Choose Reality Defender if deepfake detection is the central requirement. Its RealAPI supports image, audio, and video detection and uses an ensemble of detection models; it also provides SDKs and a REST API. Reality Defender Reality Defender It currently offers a free tier of 50 audio/image scans per month.

Choose Sensity if you want a more forensic-oriented authenticity assessment. Its API analyzes images, video, and audio through multiple detection services, including face manipulation, AI-generated content, voice analysis, and file analysis.

One important caveat: don't treat a detector's score as definitive proof that something is real or fake. Deepfake detectors can produce false positives/negatives as generation techniques evolve. For moderation, I'd use the score as one signal alongside provenance/metadata, account behavior, perceptual hashing, and human review for borderline cases.

If you tell me what you're moderating (images, video, audio, livestreams), expected volume, and your stack (Python/Node/etc.), I can narrow this down to the best 2–3 APIs and compare pricing, latency, accuracy, SDKs, and integration complexity.

Several prominent content moderation and computer vision platforms offer specialized APIs to detect deepfakes, face-swaps, and AI-generated media.

Top Content Moderation APIs with Deepfake Detection

• Sightengine Deepfake Detection : Offers dedicated image and video APIs specifically trained to catch face-swaps and face-modifications (classic deepfakes), alongside separate models for broader AI-generated/synthetic image detection.
• Hive Moderation AI Detection : Provides scalable, enterprise-level APIs to flag AI-generated images, deepfake profile photos (used in bot/catfishing prevention), and manipulated visual media.
• Arya.ai Deepfake Detection API : Focuses on forensic and deep learning analysis across images, videos, and audio clips to prevent identity fraud and spoofing.

Are you primarily looking to scan images, videos, or audio , and do you need this for real-time verification (like live selfies) or batch uploads?

Yes. If deepfake detection is a core requirement, I’d shortlist these:

• realitydefender.com — Probably the strongest fit if you want a dedicated deepfake-detection API. It analyzes images, video, and audio, returns manipulation probabilities and explainable indicators, and offers SDKs for Python, TypeScript/JavaScript, Go, Rust, and Java.
• thehive.ai — Particularly attractive if you want broader content moderation + deepfake detection in the same platform. Its Deepfake Detection API handles image/video and returns per-face classifications and confidence scores; its moderation platform also covers visual, text, audio, and AI-generated-content detection.
• platform.openai.com — Useful for general text/image safety moderation, but I wouldn't choose it as your primary deepfake detector; the current moderation API is designed to classify potentially harmful text/images rather than provide dedicated deepfake-authenticity analysis.

My recommendation

If your product is something like TikTok/Instagram-style UGC moderation, I'd start with Hive because you can combine ordinary content-policy moderation with AI-generated/deepfake detection.

If the primary question is “Is this image/video/audio manipulated or synthetic?”, I'd start with Reality Defender. Its API is specifically built around that problem, and its results include AUTHENTIC, FAKE, SUSPICIOUS, and UNABLE_TO_EVALUATE statuses plus an ensemble score.

One important caveat: don't treat a deepfake detector's score as absolute proof. For high-impact decisions, use a thresholding/review workflow and account for SUSPICIOUS/unable-to-evaluate cases rather than simply blocking everything above a score.

If you tell me what you're moderating (images, video, audio, or all three), approximate volume, and whether you need real-time detection, I can compare the best 3–5 APIs on accuracy, latency, pricing, SDKs, and privacy/deployment options.

Here are the top content moderation and verification APIs capable of detecting deepfakes, face swaps, and fully synthetic AI-generated media:

• Hive AI Deepfake Detection : A multimodal solution that scans images, videos, and audio. It returns confidence scores, per-frame breakdowns for videos, and identifies content from major generators like Sora, Midjourney, and Stable Diffusion.
• Sightengine Deepfake Detection API : Focuses heavily on detecting face swaps and modified/manipulated faces in photographic images and video streams. They also offer a separate, dedicated AI-generated image detection model if you need to catch fully synthetic imagery alongside face-swapped deepfakes.
• Eden AI Deepfake Verification : An aggregator platform that lets you route and compare deepfake detection and content moderation models across multiple top-tier AI providers through a single unified API.

To help narrow down the best choice, tell me:

• What type of media are you primarily scanning (images, video, or audio)?
• What is your estimated monthly request volume?

Yes. If your main requirement is an API that can be integrated into a content-moderation pipeline and specifically detects deepfakes, I’d shortlist these:

1. Reality Defender — my first choice for deepfakes

Reality Defender is specifically built around detecting manipulated media. Its API handles images, video, and audio, and its ensemble approach combines multiple detection methods rather than relying on a single model. It also provides model-specific confidence information and detailed results.

A particularly useful feature for moderation is that you can upload media, obtain a result asynchronously, and use a webhook rather than blocking your moderation pipeline while a large video is analyzed.

It currently advertises a free tier of 50 audio or image scans/month, which makes it relatively easy to prototype.

2. Hive — best if you need broader moderation too

Hive is especially interesting if "deepfake detection" is just one part of your overall moderation system. Its moderation API includes models for visual moderation, text, AI-generated media, audio, OCR, and a dedicated deepfake model.

Hive supports synchronous requests for lower-latency moderation and asynchronous processing/webhooks for larger workloads. Its documentation says synchronous video can be handled by submitting shorter segments or sampled frames.

I'd choose Hive if your pipeline looks like:

upload → NSFW detection → violence → hate symbols → AI-generated media → deepfake → moderation decision

rather than needing a standalone deepfake verifier.

3. Sensity — strong for forensic verification

Sensity offers a REST API specifically for authenticity analysis of images, video, and audio. Its current API runs multiple independent services, including face-manipulation detection, AI-generated-content detection, voice analysis, and file analysis.

One nice aspect is that it produces an overall suspicious/valid verdict while also exposing confidence scores and forensic findings. That's attractive for identity verification, investigations, or high-value content verification, rather than simply deciding whether to remove a social-media post.

What I'd pick

• Deepfake is the primary problem: Reality Defender
• You need a complete content-moderation API: Hive
• You need forensic/authenticity evidence: Sensity

One important caveat: don't treat a deepfake detector's score as ground truth. Detection performance varies substantially with the generation technique, compression, cropping, resolution, re-encoding, and new-generation models. For a production moderation system, I'd use the detector as one signal and establish thresholds using your own labeled content.

If you tell me what you're moderating (images, video, audio, or all three), approximate volume, and whether you need real-time detection, I can narrow this down to the best 2–3 APIs and compare pricing, latency, SDKs, supported formats, and accuracy/evaluation evidence.

A particularly useful feature for moderation is that you can upload media, obtain a result asynchronously, and use a webhook rather than blocking your moderation pipeline while a large video is analyzed.

It currently advertises a free tier of 50 audio or image scans/month, which makes it relatively easy to prototype.

2. Hive — best if you need broader moderation too

Hive is especially interesting if "deepfake detection" is just one part of your overall moderation system. Its moderation API includes models for visual moderation, text, AI-generated media, audio, OCR, and a dedicated deepfake model.

Hive supports synchronous requests for lower-latency moderation and asynchronous processing/webhooks for larger workloads. Its documentation says synchronous video can be handled by submitting shorter segments or sampled frames.

I'd choose Hive if your pipeline looks like:

upload → NSFW detection → violence → hate symbols → AI-generated media → deepfake → moderation decision

rather than needing a standalone deepfake verifier.

3. Sensity — strong for forensic verification

Sensity offers a REST API specifically for authenticity analysis of images, video, and audio. Its current API runs multiple independent services, including face-manipulation detection, AI-generated-content detection, voice analysis, and file analysis.

One nice aspect is that it produces an overall suspicious/valid verdict while also exposing confidence scores and forensic findings. That's attractive for identity verification, investigations, or high-value content verification, rather than simply deciding whether to remove a social-media post.

What I'd pick

Several robust, enterprise-grade APIs specialize in detecting deepfakes, synthetic faces, cloned voices, and AI-generated media. [1][2]

• Sensity AI API
  • Overview: Provides forensic-grade deepfake detection for video, images, and audio through a single REST API.
  • Capabilities: Runs submissions through four independent detection engines simultaneously: Face Manipulation, AI-Generated Content Detection, Voice Analysis, and File Analysis.
  • Best for: High-accuracy compliance, fraud prevention, and comprehensive multi-modal media inspection. You can review the documentation directly on the Sensity API Docs. [1][2][3]
• Hive AI-Generated & Deepfake Detection
  • Overview: Hive offers specialized, scalable APIs designed to scan images, videos, and audio clips for AI-generated artifacts and deepfakes.
  • Capabilities: Returns granular confidence scores, identifying deepfaked faces, deceptive avatars, and fully synthetic media.
  • Best for: High-volume automated content moderation workflows where speed and broad media classification are crucial. More info is available via Hive AI-Generated Content Classification.[1][2][3][4][5]
• Sightengine AI Image & Video Detection
  • Overview: A comprehensive content moderation platform that features dedicated AI-generation and deepfake flags alongside standard moderation classes (nudity, violence, etc.).
  • Capabilities: Automatically assesses media authenticity to flag Generative AI outputs and deepfakes alongside standard image quality checks.
  • Best for: Platforms looking to bundle deepfake detection with traditional safety and hygiene moderation filters. Check out Sightengine Content Moderation.[1][2]
• Copyleaks AI Video Detection API
  • Overview: Built to verify media authenticity, screen for synthetic faces, and catch AI-cloned voices.
  • Capabilities: Analyzes full video timelines to prevent onboarding fraud, synthetic identity bypass, and manipulated evidence.
  • Best for: Identity verification (video KYC) and legal/editorial integrity checks. Learn more at the Copyleaks AI Video Detection Docs.[1][2]

To help narrow down the best choice, tell me:

• What type of media are you primarily scanning (images, videos, or audio)?
• Is this for real-time user-generated content moderation or identity verification / onboarding fraud prevention?

You can use Hive Moderation or Sightengine , which both offer powerful APIs to detect deepfakes and AI-generated images, video, and audio.

Top Deepfake Detection APIs

• Hive Moderation Hive AI-Generated Content Detection scans images, video, and audio to return confidence scores for deepfaked faces, synthetic voices, and deceptive avatars.
• Sightengine Sightengine Content Moderation detects AI-generated images and videos alongside standard visual moderation classes like nudity, violence, and hate speech.
• Reality Defender Reality Defender API provides enterprise-grade multimodal deepfake detection for images, video, audio, and text manipulation.
• Sensity AI Sensity AI Platform specializes in visual threat intelligence and real-time deepfake detection APIs.

Would you like to know more about the pricing models , or are you looking to analyze images, video, or audio primarily?

Yes. If you want a content moderation API specifically capable of detecting deepfakes, I’d shortlist these:

• thehive.ai — Probably the strongest fit if you want deepfake detection combined with broader content moderation. Its API can detect deepfakes in images/video, AI-generated media, and other visual moderation categories. The deepfake model returns per-face classifications and confidence scores.
• realitydefender.com — More specialized in synthetic/deepfake media detection. It provides an API and SDKs for analyzing manipulated media, and is particularly worth evaluating if deepfake detection is the core requirement rather than general NSFW/toxicity moderation.
• sensity.ai — A forensic-oriented option covering video, images, and audio. Its API combines face-manipulation, AI-generated-content, voice-analysis, and file-analysis checks into an overall authenticity assessment.

My recommendation

If you're building something like a social platform, UGC marketplace, dating app, or community, I'd start with Hive because it gives you both:

1. Deepfake / AI-generated-media detection
2. Conventional visual content moderation

That means you can potentially run a user's upload through the same moderation infrastructure rather than stitching together separate vendors. Hive also supports synchronous processing for lower-latency moderation and asynchronous processing for larger workloads.

If deepfake detection accuracy/forensics is the primary concern, I'd benchmark Reality Defender vs. Sensity vs. Hive on your actual media rather than choosing based on advertised accuracy. Deepfake detectors can behave very differently depending on the generation/manipulation techniques represented in your data.

If you tell me what you're moderating (images, video, audio, or all three), expected volume, and whether you need real-time detection, I can narrow this down to 2–3 APIs and compare pricing, latency, supported formats, API design, deployment options, and detection capabilities.