Stamped
Capture Authenticity Not Just Images
The problem Stamped solves
Digital platforms increasingly rely on photos as operational evidence whether for logistics documentation, inspections, property listings, field operations, or vendor onboarding. However, once an image is uploaded to a platform, there is currently no reliable way to verify whether the photo actually originated from a real camera capture or from a generated, reproduced, or manipulated source.
This problem is becoming significantly worse with the rise of generative AI. AI-generated images, screenshots, and reproduced media can easily pass through existing moderation systems. Metadata such as EXIF data can be stripped or modified, and post-upload detection systems remain probabilistic and unreliable. As a result, companies must treat critical visual inputs as untrusted data, leading to disputes, fraud risks, and costly manual verification processes.
Stamped solves this by introducing a verifiable capture layer for images.
Instead of trying to determine whether an image is fake after upload, Stamped verifies how the image was captured at the moment of capture itself. The system enforces a trusted capture environment and generates a cryptographically verifiable authenticity record that accompanies the image.
Key capabilities include:
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Capture environment verification (device integrity checks)
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Detection of reproduced images such as screens or prints
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Cryptographic signing of the capture record
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Privacy-preserving proof generation
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Secure documentation storage and collaboration
Stamped can be used in many real-world workflows including:
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Logistics and shipment documentation
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Property inspection and real estate listings
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Field worker documentation
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Vendor onboarding and product verification
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Construction site documentation
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Insurance claims evidence
By converting ordinary photos into verifiable digital evidence, Stamped helps organizations reduce disputes, prevent fraud, and build trust in image-driven workflows.
Challenges I ran into
1. Zero-Knowledge Proof Generation
One of the most technically challenging aspects was implementing the zero-knowledge proof layer for capture verification. The goal was to prove that a valid capture event occurred without revealing sensitive information such as device identifiers or private metadata.
Designing efficient circuits and ensuring proof generation remained computationally practical was difficult. Early implementations resulted in proofs that were too slow for real-world usage. This required redesigning parts of the proof structure and optimizing the verification pipeline so that proofs could be generated and verified within acceptable performance limits.
Balancing privacy guarantees with performance constraints was a major engineering challenge.
2. Fileverse Integration
Another key hurdle was integrating Fileverse as the decentralized document layer for capture records.
Fileverse provides encrypted collaborative documents stored in a decentralized manner. The challenge was designing a system where capture records could be securely written, updated, and shared while maintaining strong privacy guarantees.
This required designing a clean workflow for:
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Writing capture metadata into Fileverse documents
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Maintaining encrypted document states
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Ensuring compatibility with Fileverse APIs
Structuring capture records in a format suitable for both humans and automated verification systems
Once implemented, Fileverse allowed Stamped to provide tamper-resistant and encrypted capture documentation that can be shared without relying on centralized platforms.
3. BitGo Wallet Infrastructure
Integrating BitGo introduced another set of challenges related to privacy-preserving wallet infrastructure.
The system uses BitGo wallets to:
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Manage cryptographic identities
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Generate fresh addresses
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Sign transactions programmatically
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Enforce wallet-level policies
Designing a workflow that maintained privacy while still allowing programmable verification required careful handling of wallet keys and transaction flows.
Ensuring that capture verification records could interact with BitGo wallets without leaking identity information required careful architecture design and testing.
4. System Architecture
The biggest overall challenge was designing an architecture that integrates:
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device trust verification - device attestation (play integrity)
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zero-knowledge proofs
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decentralized document storage
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wallet infrastructure
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capture verification
while still keeping the system usable in real-world workflows.
Multiple iterations were required before arriving at a design that balanced security, usability, and privacy.
Tracks Applied (6)
Privacy
DeFi
Best Privacy Application using BitGo
BitGo
Best DeFi Application using BitGo
BitGo
Build What Big Tech Won't
Fileverse
BEST Overall Project
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