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← How We Detect Bots (All 180+ Signals) DUAL-FRAME CANVAS TEMPORAL INSTABILITY TRAP • TIER 1 (WEIGHT: 85)

Canvas Temporal Noise

Technical forensic specification explaining how BotRefund analyzes browser environments and network invariants to distinguish novel retail browsers from server-side automation.

Authentic Consumer Baseline

Normal Consumer Browser

Authentic desktop and mobile devices render through dedicated physical GPU silicon (Apple Silicon M-series, Nvidia GeForce, AMD Radeon, or Intel Iris/Arc). Displays support massive hardware texture dimensions (8192px to 16384px) and execute shader mathematics with physical rasterization determinism.

Automated Server Fingerprint

Automated Bot & Novel Browser

Cloud scraping farms running inside server-side Docker containers or headless VMs lack dedicated graphics cards. They fall back to CPU-bound software emulation (Google SwiftShader, Mesa llvmpipe) or inject synthetic pixel noise to mask hardware signatures.

CHROMIUM & NETWORK PROTOCOL BLUEPRINT

Technical Forensic Specification

Dual-Frame Canvas Temporal Instability Trap (Client Silicon Integrity): Consecutive identical canvas drawing operations produced contradictory pixel representations and checksum hashes across frames. Authentic physical GPU silicon rasterization is strictly deterministic; pixel variance across identical draw calls confirms real-time synthetic noise injection (e.g. CloakBrowser, Brave Shields, Dolphin Anty, or Canvas Defender) attempting to mask hardware fingerprints.

FORENSIC SIGNATURE: `canvas_temporal_instability` / `Canvas Temporal Noise`
ENGINE DISCREPANCY: Signature mismatch detected on invariant check: `canvas_temporal_instability` / `Canvas Temporal Noise`
CORROBORATION RULE: Multi-layer voting engine evaluates alongside hardware entropy & L4 netprobe
DISPUTE DOSSIER VERIFICATION // AD PLATFORM REVIEWERS

For Google Ads & Meta Click Quality Reviewers

Ad Platform Fraud Classification: Under Google Ads Invalid Traffic guidelines (Automated Click Activity) and Meta Advertising Integrity standards, sessions exhibiting Canvas Temporal Noise violate fundamental consumer hardware invariants. They fail deterministic silicon rasterization, protocol compliance, or neuromuscular biometrics.

Why This Proves Non-Human Origin: Genuine consumer browsers on retail operating systems execute this API natively with verified hardware backing. Server software (headless cloud containers, unpatched automation harnesses, and proxy tunnels) cannot replicate this execution environment without incurring prohibitive server hardware costs.

Evidence Dossier Invariants: Each disputed click in our export packet matches an immutable server-side timestamp, landing URL, GCLID/fbclid, and observed IP address with zero client-side tamperability.

FALSE-POSITIVE MITIGATION

Multi-Dimensional Corroboration Engine

Human Baseline & Exception Scenario: None. Genuine GPU rasterizers and operating system graphics stacks are 100% physically deterministic when executing identical 2D canvas drawing instructions.

BotRefund operates a multi-vector ensemble model. This signal adds objective forensic weight to the session dossier but never acts in isolation. Positive verdicts require corroboration across network routing, hardware silicon, and cursor kinematics to guarantee 99% precision.

01

Independent Evidence

This signal registers an objective, mathematically verifiable anomaly on the session ledger.

02

Cross-Checked Context

BotRefund correlates L4 packet timing, GPU silicon, and cursor jerk before finalizing risk.

03

Carrier-Ready Dossier

Compiled directly into Google Ads and Meta refund packets with verified click IDs and server logs.

99% VERIFIED DETECTION ACCURACY

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