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Datasets:
AxonData
/
replay-attack-dataset

Tasks:
Image Classification
Video Classification
Languages:
English
Size:
10K<n<100K
Tags:
replay-attack
replay-attack-dataset
face-anti-spoofing
face-liveness-detection
liveness-detection
presentation-attack-detection
License:
Dataset card Files
xet
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Dataset Viewer
The dataset viewer is not available for this dataset.
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Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
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                      jwt=token,
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                      options=options,
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                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
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                      leeway=leeway,
                  )
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                  )
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                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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Commercial collection of 10,000+ replay attack videos covering both display-based and mobile-based replay spoofing. Captured from 2,500+ unique participants with balanced gender and ethnicity representation. Suitable for training face anti-spoofing models and preparing for iBeta PAD Level 1 certification

Dataset Summary

Replay attacks are one of the most common presentation attack types in face biometric systems. Attackers replay a video or image of a genuine user on a screen (phone, tablet, monitor) to bypass liveness detection. A robust liveness model must see diverse replay scenarios during training

This dataset combines two attack streams into a single training resource:

  • Display replay attacks - captured from a variety of screen devices (monitors, laptops, tablets) with diverse lighting conditions
  • Mobile replay attacks - captured across 15+ different phone models spanning low-end, mid-range, and high-end segments, including Samsung Galaxy A54, Honor 70, Google Pixel 7

Both attack streams share the same capture protocol: slow camera movement, multi-angle coverage

Dataset Characteristics

Feature Value
Total attack videos 10,000+
Unique participants 2,500+
Attack sub-types Display replay + Mobile replay
Mobile device coverage 15+ phone models (incl. Galaxy A54, Honor 70, Pixel 7)
Camera behavior Slow movement, multi-angle
Gender distribution Balanced
Ethnicity distribution Balanced
iBeta compliance Level 1 (PAD)

For commercial use, production deployment, or access to the full 10,000+ video dataset, contact Axon Labs at axonlab.ai

Use Cases

  • Face anti-spoofing model training: expand replay attack coverage beyond narrow academic datasets
  • iBeta PAD Level 1 preparation: replay attacks are a required category for iBeta Level 1 certification
  • Cross-device generalization: evaluate model performance across display types and phone models
  • Benchmarking: compare production PAD models on diverse replay scenarios
  • Fraud prevention R&D: detect screen replay attempts in KYC and remote onboarding systems

What Makes This Dataset Different

  • Both attack streams in one: most public replay datasets cover either display OR mobile, not both
  • Realistic mobile coverage: 15+ real phone models
  • Commercial license available: suitable for production deployment, not research-only
  • Consent-based: all subjects provided explicit consent for AI training use
  • Scale: 10,000+ videos is larger than most publicly available replay collections

Related Datasets from Axon Labs

Full catalog: axonlab.ai/datasets

About Axon Labs

Axon Labs creates high-quality datasets for AI training, with a focus on biometric security, face recognition, and liveness detection

Other Axon Labs datasets on Hugging Face: huggingface.co/AxonData
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