How much is AI Threat Detective?

AI Threat Detective is listed for sale at $2,000 USD.

AI Threat Detective - Sell Project

Listed March 20, 2026

About AI Threat Detective

Neural engine for real-time fraud detection. Full source + white-label rights.

AI Threat Detective Neural engine for real-time anomaly detection in DeFi/Web3 transactions. AI Threat Detective analyzes transaction windows and returns an anomaly score plus business-ready explanations (risk factors + recommendations) so teams can act before funds are drained. How it works (under the hood) Input: transactions (single tx or window) via REST or WebSocket Feature engineering: tabular window features + graph metrics (from→to) Model scoring: Transformer + GNN + Tabular models Fusion: mean-based fusion across available modules (safe fallback if some artifacts are missing) Decision: isanomaly based on a configurable threshold XAI output: summary, riskfactors, recommendations for CFO/CISO/ops What’s included Full source code REST API + WebSocket streaming XAI layer for human-readable explanations (DeFi-focused templates) Fusion ML architecture: Transformer + GNN + Tabular + fallback-safe scoring Docker image + artifacts workflow Optional alerting via webhook when anomalies are detected API keys + rate limiting (for multi-tenant / customer usage) White-label rights: rebrand and resell as your own service Why buy Save months of engineering: built as an integration-focused AI engine, not a research prototype Faster deployment: deploy and integrate using Docker + provided endpoints and examples Practical explainability: explanations are designed to be understandable by non-ML stakeholders Multi-chain ready: chainid support + adapter pattern (Ethereum mainnet streaming included as an example) Important note on model training Current training scripts generate synthetic MVP datasets. The architecture is designed for fine-tuning and re-training on your own labeled or customer datasets for production calibration. Tech stack Python, PyTorch, PyTorch Geometric, FastAPI, scikit-learn, Docker

Project details

Next step: <h2 _msttexthash="297452233" _msthash="2487">How buyers can push the project forward Buyers can expand AI Threat Detective into a production threat intelligence and monitoring system by calibrating it with their own data and integrating their own on-chain and off-chain pipelines. Calibrate and retrain on real data: collect labeled incidents (or internal alerts), adjust the decision threshold (ATD_ANOMALY_THRESHOLD), and retrain the models using the included training scripts (scripts/retrain_all.py or model training). Add data adapters for their environment: implement a small adapter that maps their transactions/events to a transmission scheme (single TX or Windows). The engine is reused across the entire EVM chain (via chain_id) and can be extended for non-EVM sources using a custom adapter. Improve the quality of XAI evidence by enriching token_transfers and input logs (when available) and expanding risk factor templates in ai_threat_detective/xai/ to match the buyer's specific DeFi protocols and compliance workflows. Integrate the real mempool / streaming: connect them to the RPC/WebSocket provider and connect the real transaction flow to either the local scoring pipeline or the public APIs (/score, /ws). Strengthen production: deploy behind an HTTPS reverse proxy, add operational controls (secret management, centralized logging, dashboard monitoring, and alert routing). Multi-tenancy scaling: Replace the standard SQLite layer with PostgreSQL/Redis if necessary, and implement policies for each client (thresholds, speed limits, quotas, and routing). Operational evaluation: Add offline evaluation reports (ROC/AUC, accuracy/recall) and online metrics (latency, throughput, and alert volume) to continuously improve performance and reduce false positives.</h2>

For sale

Asking price: $2,000 USD

What's included

Source code, All related data

Reason for selling

Проект доведён до работоспособного MVP и может быть быстро реализован. Дальнейшая разработка требует коммерческой поддержки и фокуса на новых продуктах, поэтому я продаю права и готовую структуру для внедрения под вашим брендом (white label).

Project metrics

Average Monthly Revenue: Pre-revenue