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ThreatByte

Intelligent Threat Detection Pipeline

Website Coming Soon

The Objective

Modern phishing campaigns and tunnel-based threats bypass traditional signature-based security mechanisms with ease. The objective of ThreatByte was to engineer a robust, latency-optimized threat evaluation pipeline capable of identifying zero-day infrastructure permutations in under 1 second, without sacrificing deep classification accuracy.

Implementation Architecture

Unlike legacy scanners that ping a static database, ThreatByte operates as a 5-Layer sequential pipeline that evaluates targets both mathematically and visually.

  • Layer 0: Pre-Processing - Parses payload dynamics and safely de-obfuscates routing/tunneling endpoints before they hit core systems.
  • Layer 1: Intelligent Validation - Custom in-memory database instantly whitelists globally trusted domains to save compute overhead.
  • Layer 2: Ensemble Brain - Parallel node cluster mapping 100+ heuristic rule-sets and executing ML inference for zero-day deviations.
  • Layer 3: Telemetry Sync - Securely cross-references suspicions via global threat consortium APIs.
  • Layer 4: DOM Sandbox - Headless containers physically render and dissect deceptive login overlaps without exposing the host environment.

Execution Flow Pipeline

// Backend Microservices Auth Flow

Node_1 [ Pre-Flight Extraction ]

Node_2 [ In-Memory Verification ]

Node_3 [ ML & Heuristics Core Engine ]

Node_4 [ Telemetry Consensus ]

Node_5 [ Sandboxed DOM Render ]

[+] Verdict -> Structured Threat JSON Emitted
Project Specs
Status ● Active Build
Architecture 5-Layer Pipeline
Target Focus Zero-Day Phishing
98.7%
Accuracy
<1s
Response
Core Stack
Python Flask Scikit-Learn Docker Redis