CPP v1.4 Release Notes

Release Date: January 29, 2026

Overview

CPP v1.4 adds the Depth Analysis Extension for screen detection and expands platform support to include physical cameras, drones, surveillance systems, and embedded devices.

What's New

🔬 Depth Analysis Extension (OPTIONAL)

• LiDAR/ToF-based screen detection to identify photo-of-screen attacks
• Statistical depth analysis (min, max, mean, standard deviation)
• Plane analysis for surface flatness detection
• Screen detection verdict with confidence scoring
• Privacy-preserving: raw depth data is NOT stored, only statistical summaries

📷 Multi-Platform Support

New DeviceClass field supporting 13 device categories:

• Smartphone, Tablet - Mobile devices
• DigitalCamera - DSLR, mirrorless, compact cameras
• ActionCamera - GoPro, DJI Action
• Drone - DJI Mavic, Autel
• Surveillance - IP cameras, CCTV
• BodyCamera - Axon, law enforcement cameras
• Dashcam - Vehicle-mounted cameras
• IndustrialCamera - Machine vision (Basler, FLIR)
• MedicalImaging - Endoscopes, dermascopes
• Webcam, Embedded, Other

🔧 New Data Model Fields

• DeviceInfo.DeviceClass - Platform identification
• DeviceInfo.CaptureDevice - Physical camera metadata (lens, aperture, ISO, etc.)
• DeviceInfo.SecurityModule - TPM/HSM/SecureElement support
• SensorData.DepthAnalysis - Complete depth analysis object

📊 16 Depth Sensor Types

Platform-independent sensor identification:

• Mobile: LiDAR, TrueDepth, ToF, StructuredLight, Stereo
• Camera: DualPixelAF, PhaseDifferenceAF
• Industrial: IndustrialLiDAR, IndustrialToF, RGBD, Radar, Ultrasonic
• External: ExternalLiDAR, ExternalToF, StructuredLightScanner

Embedded Systems Support

Minimum requirements for resource-constrained implementations:

• CPU: ARM Cortex-M4+
• RAM: 256KB
• Flash: 512KB
• Optional: SHA-256 hardware acceleration

Backward Compatibility

• All v1.3 events remain valid
• DepthAnalysis is OPTIONAL - existing implementations unaffected
• Merkle tree construction unchanged from v1.3

Migration Guide

No migration required. To adopt v1.4 features:

1. Add DeviceClass to DeviceInfo
2. Optionally add DepthAnalysis to SensorData if depth sensor available
3. Optionally add CaptureDevice for physical camera metadata

Reference Implementation

• VeraSnap iOS - First CPP v1.4 compliant application
• App Store: https://apps.apple.com/app/id6757994770

Links

• Full Specification
• VeraSnap Product Page
• VSO Website

CPP v1.0 - Capture Provenance Profile

Release Date: 2026年01月18日
Status: Release Candidate

Overview

CPP (Capture Provenance Profile) is an open specification for cryptographically verifiable media capture provenance. Part of the VAP (Verifiable AI Provenance) Framework.

Key Features

🔐 Completeness Invariant

Mathematical deletion detection using XOR hash sums - detects ANY missing events in the capture chain.

⏱️ External Third-Party Verification

RFC 3161 TSA mandatory (Silver+) - eliminates self-attestation vulnerabilities found in existing solutions.

🔒 Privacy by Design

• Location OFF by default
• Zero-knowledge biometric attestation (ACE)
• GDPR-compliant crypto-shredding

🔗 C2PA Interoperability

Designed to complement C2PA, not compete. Export format included.

What's Included

• docs/CPP-Specification-v1.0.md - Main specification
• docs/C2PA-Interoperability.md - C2PA integration guide
• schemas/cpp/ - JSON schemas for core events
• schemas/ace/ - ACE extension schemas
• examples/ - Sample events and verification packs
• test-vectors/ - Conformance test data
• tools/ - Reference implementation (Python)
• regulatory-mapping/ - EU AI Act, GDPR mapping

Conformance Levels

Links

• Specification: CPP-Specification-v1.0.md
• VAP Framework: github.com/veritaschain/vap-spec
• Website: veritaschain.org

License

• Specification: CC BY 4.0
• Code/Schemas: Apache 2.0

VeritasChain Standards Organization
standards@veritaschain.org