Enhance Account Security with Shadow Watch's Behavioral Intelligence

Enhance Account Security with Shadow Watch's Behavioral IntelligenceEnhance Account Security with Shadow Watch's Behavioral Intelligence

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Tanishq Dasari

• Jun 12

Shadow Watch — Behavioral Intelligence & Account Security Platform

Description

Shadow Watch is a behavioral intelligence platform that continuously analyzes user interaction patterns to build behavioral profiles, detect anomalies, and strengthen account security without introducing friction to the user experience.

Instead of relying solely on passwords or one-time verification checks, Shadow Watch observes behavioral continuity over time to establish trust signals and identify potentially compromised sessions.

The system combines behavioral fingerprinting, activity analysis, risk scoring, and anomaly detection to help organizations recognize suspicious account activity before it escalates into an account takeover event.

Key Features

Behavioral fingerprint generation

User activity intelligence

Trust score calculation

Session anomaly detection

Account takeover prevention

Temporal behavior analysis

Privacy-conscious architecture

Tech Stack Python • FastAPI • PostgreSQL • Security Engineering • Behavioral Analytics • Risk Scoring

Security Engineering FastAPI PostgreSQL Python

Afifudin Zuhri

pro

• Jun 11

Stratum is a cybersecurity brand built around the idea that trust should always be verified. Through structured forms, clean typography, and a layered visual system, the identity reflects security, clarity, and control.

I'd love to hear your feedback. Does the identity effectively communicate trust and security?

Logo Design Brand Design Motion Design

MD Rafee Alam

• Jun 11

The layered mark paired with "Trust nothing. Protect everything." lands well. Monochrome keeps it sharp. The business card mockup shows it can hold its own in print too.

Rohit Mahale

• Jun 11

Built a Customer Behavior Dashboard analyzing 3.9K customers, tracking average purchase amount, review ratings, revenue by category, and sales by age group. Created using Power BI with interactive filters for gender, category, and shipping type. This project demonstrates end-to-end data analytics from raw data to business insights.

Data Analysis Microsoft Power BI Data Visualization Jupyter Python

Neelanshu Karn

• Jun 11

Adrexon One domain in. Full outreach out. Adrexon finds lookalike companies, surfaces C-suite decision-makers, resolves verified emails, and sends personalised outreach - zero manual steps between stages. Built with Python, Flask, and a 4-API chain (Apollo.io · Prospeo · Brevo). Includes a CRM collaborative workspace, suppression list, resumable runs, rate-limit resilience, and a safety checkpoint before any email fires. A production-grade B2B SaaS tool - not a demo.

Completed work