suspicious-activity-detection

🛡️Efficient anti-bot protection for PHP (+Wordpress), Java, NodeJS, and Python using suspicion vectors, honeypots and secured proofs of work ⚡Sandbox host :

Real-time fall detection & human activity recognition using YOLO26-Pose — INT8 OpenVINO/TensorRT deployment with geometry-invariant fall rules for corner-mounted CCTV.

This is an official implement for "Detecting Suspicious Activity in the NFT Ecosystem using Temporal Graph Analysis"

PiLENS-Ai__based Suspicious Activity Detection System using Deep Learning Models and Computer Vision

This project focuses on identifying and removing suspicious or unnecessary browser extensions. It explores extension permissions, privacy risks, unwanted advertisements, redirects, and potential exposure of browsing data. The task provides practical experience in browser security, privacy protection, threat identification, and safe extension manage

The Log Analyzer Tool analyzes server logs to detect suspicious activities and generates reports and visualizations.

"Python-based security tool for detecting suspicious processes"

An experimental framework for evaluating AML investigation agents across grounding, safety, context engineering, compliance, and governance.

AI Chat Monitoring & Suspicious Activity Detection System - A real-time chat application that uses Machine Learning (TF-IDF + Logistic Regression/SVM) to detect suspicious or harmful messages, trigger admin alerts, and ensure secure communication with encryption and live monitoring.

A Windows system tray application that silently monitors URLs — from your clipboard and every link you click — and warns you before a phishing page can load.

Vigil Fluminis - Windows Firewall Analysis - various criteria to generate a "suspicious" score

👁 Detect suspicious activity in real-time with AI-powered night vision surveillance on Raspberry Pi for reliable low-light security monitoring.

Real-Time Suspicious Activity Detection through Behavioral Modeling leverages machine learning to identify anomalies by modeling normal user/system behavior. It enables real-time threat detection, fraud prevention, and security monitoring by detecting deviations from expected patterns.

AML AI Investigator is a pipeline and FastAPI service for AML case evidence packages, policy retrieval (local RAG), and structured LLM copilot summaries, built on Spark‑generated case packets with Docker deployment support.

Blue Team cybersecurity project using Splunk Enterprise to investigate a simulated Fidelity-inspired security incident through detection engineering, threat hunting, dashboards, SPL queries, and MITRE ATT&CK mapping.

Data visualisation meets financial investigation

Prototype for automating Suspicious Activity Report (SAR/STR) drafting. Transforms structured transaction records into compliance-ready narratives using Python templates, with built-in evaluation for completeness, readability, and consistency.