ASM & Dark Web Monitor

@vishal1145

Your dark-web crawler will fail if you're not handling Tor circuit rotation properly - I've seen scrapers get blacklisted within hours because they hammer .onion sites from the same exit node. That's the difference between a tool that runs once and a production system that stays operational. Quick question - are you expecting to scan a single domain or multiple organizations? And what's your acceptable false-positive rate for credential leaks? I ask because tuning MongoDB aggregation pipelines for correlation logic changes drastically if you're processing 500 domains versus 5. Here's the architectural approach: - PYTHON + FASTAPI: Build two microservices (ASM + DarkWeb) sharing a common authentication layer and event bus, so alerts from either module trigger unified webhooks without duplicating logic. - DOCKER + TOR PROXY: Run Tor as a sidecar container with SOCKS5 proxy rotation every 10 requests, preventing IP bans and ensuring .onion crawls don't stall after 50 pages. - MONGODB CHANGE STREAMS: Use native change streams to detect new subdomain records or credential mentions in real-time, pushing alerts to Slack/webhook within 2 seconds instead of polling every minute. - WEB SCRAPING + OSINT: Integrate subfinder and amass for subdomain enumeration, then layer Nmap service detection with version fingerprinting - storing diffs in a time-series collection so you see exactly when port 22 appeared on staging.example.com. - LINUX + SYSTEMD: Package the stack with health checks and auto-restart policies so a crashed Tor circuit doesn't kill the entire pipeline. I've built similar OSINT platforms for two security firms that needed continuous monitoring of 200+ domains. The last one processed 15K .onion pages daily without rate-limit issues because we implemented request throttling and circuit isolation. I don't start builds where the alert logic isn't defined upfront. Let's jump on a 15-minute call to clarify your correlation rules and acceptable latency before I scope the MVP timeline.

@ixorawebmob

Hello, I’ve gone through your project details and this is something I can definitely help you with. I have 10+ years of experience in mobile and web app development, working with technologies that span across Python, Docker, and web scraping solutions. My expertise ensures a scalable architecture, particularly for your ASM and Dark Web Monitor requirements. For the ASM module, I will implement an automated discovery of sub-domains and maintain historical data for clear trend analysis, while utilizing FastAPI for clean REST endpoints. The Dark Web monitoring will focus on efficient crawling and scraping of TOR sites, ensuring accurate correlation with your asset list and alerting mechanisms. I will create a lightweight dashboard for visualizing key metrics and alerts, efficiently using technologies like React or minimal HTML. Documentation will be thorough, and environment variables will be managed securely. Here is my portfolio: https://www.freelancer.in/u/ixorawebmob I’m intrigued by your project and would love to understand more specifics to ensure the best approach. Could you clarify your preferred database between MongoDB and PostgreSQL for this project? Let’s discuss over chat! Regards, Arpit Jaiswal

@muneeb6767

I can deliver a fast MVP with Python (FastAPI), ASM scanning (subdomains, ports, history) + Tor-based dark web monitoring, all Dockerized with a simple dashboard and alerting via email/Slack/webhooks. Modular, scalable, and ready for rapid iteration within days.

@KarthikTechCon

Hello, I’m Karthik with 15+ years of experience in Python, backend systems, OSINT-style automation, API development, and security-focused monitoring tools. I can build your ASM + Dark Web Monitoring MVP as a modular Python stack with fast prototype delivery. Approach for MVP: • ASM Module: subdomain/asset discovery, port/service scanning, change tracking, historical storage, FastAPI REST endpoints • Dark Web Module: Tor-routed crawling of .onion sources, keyword/brand/email/credential matching, correlation with ASM assets, alert triggers • Stack: Python, FastAPI, MongoDB/PostgreSQL, Docker Compose, dotenv, webhook/email/Slack alerts • Dashboard: lightweight React/Vue/minimal web UI for findings, trends, exposed assets, and alerts Delivery plan: Core API + DB schema + Docker setup ASM discovery/scanning + history tracking Tor crawler + leak detection + correlation Dashboard + alerts + unit tests Why me: Hands-on experience with Python automation, monitoring systems, API-first architecture, scraping workflows, and rapid MVP execution with clean documentation. I can prioritize a working prototype in days, then iterate quickly for coverage, accuracy, and resilience. Warm Regards, Karthik B

@DigitalNightOwl8

Hello Already have something live to show you I am professional mobile software engineer with skills including Web Design, PHP, Website Development, Content Writing, Elementor, HTML, WordPress and Website Design. Please send a message to discuss more about this project. Always happy to hear from you Thanks

@abdf2010

Hey, your project, ASM & Dark Web Monitor looks like a great fit for my skills. I've worked on similar PHP projects and can deliver solid results. Let me know if you'd like to chat about the approach.

@shabahathabib

Hi, I can deliver a fast MVP for your ASM + Dark Web monitoring platform with a modular Python backend (FastAPI), shared API layer, and Dockerized deployment. Approach: ASM module: subdomain discovery (OSINT + APIs like Shodan/Censys), port/service tracking, historical storage (PostgreSQL/MongoDB) Dark web module: TOR-routed crawler (.onion), keyword/credential detection, correlation with ASM assets Dashboard: lightweight React/Vue UI with real-time alerts (email/Slack/webhooks) Infra: Docker Compose, dotenv config, retry/failover handling, unit tests for critical flows I’ve worked with OSINT tools and scraping pipelines, and can deliver a working prototype within days, then iterate quickly.I’m ready to start immediately BEST REGARDS SHABAHAT HABIB*

@Hrolgar

I've built Python + FastAPI + Docker stacks like this before -- modular APIs backed by MongoDB, containerized with Docker Compose, the whole thing. Here's how I'd approach this in two phases: Phase 1 (days 1-5): ASM module. Subdomain enumeration via subfinder/amass, port scanning with nmap/masscan, service fingerprinting, change tracking over time. All exposed through clean FastAPI endpoints. Historical data stored in MongoDB so you can spot newly exposed services at a glance. Dashboard shows asset inventory, open ports, and change diffs. Phase 2 (days 6-10): Dark web module. Tor-routed .onion crawling for brand/email/credential mentions, correlated against the ASM asset list. Alert pipeline fires via webhook, email, or Slack when new leaks surface. Infrastructure: single docker-compose up spins everything -- API, workers, MongoDB, Tor proxy, dashboard. Dotenv config, unit tests on critical routes and scraping functions. I've worked with OSINT tooling and API integrations (Shodan, Censys-style services) professionally. Happy to walk through architecture before we start. 10 days for full MVP, ASM module demo available midway.

@excel4engineers

Hi there! I am a skilled full-stack developer and data specialist with extensive experience in delivering high-quality results on time and within budget. I have a proven track record of successfully completing similar projects with high client satisfaction ratings. I would love to discuss the details of your project and share my approach. Looking forward to working with you!

@jaroslavcaprata

Hello, I hope you are doing well and thank you for the detailed and well-structured requirements. My name is ⭐⭐Jaroslav⭐⭐ and I have strong experience building security-focused systems in Python, including OSINT tools, asset discovery pipelines, and automated monitoring solutions. I have previously worked on projects involving subdomain enumeration, service scanning, and integrating data from sources like Shodan and custom crawlers, along with TOR-based scraping for intelligence gathering. For your project, I would design a modular FastAPI backend serving both ASM and dark-web modules, with scalable data storage and clear REST endpoints. The ASM layer will handle continuous discovery, port tracking, and historical analysis, while the dark-web module will safely route through Tor, extract relevant data, and trigger alerts with proper correlation logic. I will deliver a Dockerized setup, clean dashboard, and reliable alerting system with strong logging and test coverage. I am confident I can deliver a fast and effective MVP and would be glad to collaborate with you. I look forward to your response.

@pulkit0729

I understand the critical need for real-time visibility over public assets and dark-web exposure. I will build a modular Python backend using FastAPI, integrating ASM to auto-discover assets, track ports/services with historical trend storage, and expose clean REST endpoints. For dark-web monitoring, I’ll develop a TOR crawler to scrape .onion sites for brand/email mentions, correlating with ASM data and triggering alerts via Slack/email/webhooks. MongoDB will handle structured storage, and a lightweight React dashboard will visualize key metrics and alerts. The entire system will be containerized with Docker Compose for seamless deployment. I have experience with OSINT tools, Shodan API integration, TOR automation, and Python scraping frameworks. I’ll deliver a working MVP within days, focusing first on core scanning and alerting, then iterating rapidly. Unit tests and clear documentation will ensure reliability and maintainability throughout.

@Hemantt841

Gaining comprehensive, real-time insight into an organization’s attack surface alongside vigilant dark-web monitoring is critical for proactive cybersecurity defense. The dual focus on ASM and dark-web exposure requires a tightly integrated system that not only discovers and tracks internet-facing assets but also correlates that data with dark-web intelligence to detect and alert on emerging threats. This project demands a seamless fusion of automated asset discovery, continuous service monitoring, and stealthy dark-web scraping with reliable alerting and historical trend analysis. Leveraging Python’s FastAPI for a clean, modular REST API will ensure both ASM and dark-web modules share a robust backend, while MongoDB or PostgreSQL will provide efficient, structured storage for asset histories and crawling results. The ASM module will incorporate automated sub-domain enumeration, port scanning, and service fingerprinting, capturing changes over time with clear trend visualization. The dark-web crawler will be engineered to navigate TOR networks securely with fail-over mechanisms, scraping for brand and credential mentions and linking these directly to known assets. A lightweight React or Vue dashboard will surface critical metrics and instantly push alerts via email, Slack, or webhook, ensuring rapid response. Commitment to quality includes delivering a fully containerized stack with Docker Compose for effortless deployment and environment management, clear documentation, and comprehensive unit tests covering key API and scraping logic. An MVP can be delivered swiftly by focusing first on core scanning and alerting capabilities, enabling iterative enhancements thereafter. Let’s connect to align on target specifics and accelerate this project toward a secure, actionable intelligence

@Visharaa2024

Hello, I can build a fast, modular, and production-ready ASM and dark-web monitoring system that gives you real-time visibility across both your public attack surface and hidden exposure. I have strong experience with Python (FastAPI), OSINT tools like Shodan and Censys, TOR-based scraping, and scalable backend systems using Docker and modern databases. For the ASM module, I will implement automated asset discovery (subdomains, services, ports), continuous tracking with historical data, and clean REST APIs. For the dark-web module, I will develop a TOR-routed crawler with failover that detects brand, email, and credential mentions, correlates them with your assets, and triggers real-time alerts via dashboard, email, or webhook. The system will use MongoDB or PostgreSQL, include a lightweight dashboard for visibility, and be fully containerized with Docker Compose for one-command deployment. I will also ensure proper documentation, dotenv-based configuration, and unit tests for key components. I can deliver a working MVP within a few days and then iterate quickly to enhance coverage and performance. I’m ready to start immediately and discuss your initial test targets.

@indreshpnk

Hello, I understand you need real-time visibility over public-facing assets and dark-web exposure. The goal is to deliver a secure, scalable, and real-time monitoring solution that meets your expectations. Here’s what I can provide: Develop ASM module for automated asset discovery, port/service tracking, and historical analysis with REST APIs using FastAPI Build dark-web monitoring system using TOR scraping to detect leaks, correlate data, and trigger instant alerts Deliver Dockerized setup with MongoDB/PostgreSQL, lightweight dashboard, and webhook/email/Slack alerts I bring over 4+ years of experience in Python, FastAPI, Docker, and Web Scraping, with a strong focus on building reliable and scalable systems. I’ve worked on security tools, OSINT-based solutions, and automation systems, ensuring performance and clean architecture. Just to clarify a few things: Do you have any preferred tools like Shodan/Censys integration? What alert channels should be prioritized initially? Please come to the chat box to discuss more about your project. Best regards Indresh Kushwaha

@hockfx

You need real-time visibility over public-facing assets and dark-web exposure, with two critical modules: ASM and Dark-Web Monitoring. ASM Module: I will implement automated sub-domain discovery and port/service scanning, storing historical data for trend analysis. REST endpoints will be exposed using FastAPI for seamless integration. Dark-Web Monitoring: I will develop a crawler to scrape TOR sites for brand or credential mentions, correlating with ASM data and triggering alerts for new leaks. Core System: A Python backend will serve both modules with MongoDB for storage. A lightweight dashboard will display key metrics and send alerts via email, Slack, or webhook. Docker Compose will be used for deployment. Timeline: Expect a working prototype in 5 days, with rapid iterations following. Could you specify if there are any particular TOR sites or asset types you want prioritized in the initial scan?

@bilal0156

Hi, This is an interesting and advanced project. I can build an MVP covering both ASM and dark web monitoring with a modular Python backend (FastAPI), database integration, and a simple dashboard. For the ASM module, I can implement subdomain discovery, port scanning, and change tracking. For dark web monitoring, I can set up a Tor-based scraper with keyword detection and alerting. I suggest starting with a fast MVP (core scanning + basic alerts) within a few days, then iterating to improve coverage and reliability. Let’s discuss your target scope and priorities so I can plan the quickest and most effective approach. Best regards

@ViktorUmanskyi

Greetings, With over 3 years in backend-focused Python development, I have the skills and expertise to deliver a reliable and efficient solution for your "ASM & Dark Web Monitor" project. My experience with scalable API-driven platforms, Django/DRF, PostgreSQL, and async processing aligns well with the functional requirements of this project. You can count on me for clean code, predictable output, and stable performance under load - hallmarks of my work so far. Lastly, my familiarity with CI/CD, cloud deployments, and AWS will ensure that the final product is optimized for high availability in a SaaS environment. Given your emphasis on rapid prototyping and iterative development, my ability to communicate well while pushing projects forward without handholding will be an asset. Let's build this end-to-end ASP & Dark Web Monitor together in days rather than weeks!

@srdank001

Hello! This project aligns well with my experience building modular Python systems focused on monitoring, data pipelines, and secure automation. I can design a FastAPI-based backend where ASM and dark-web monitoring work together, with clean REST endpoints and a shared, well-structured data model. The ASM module will handle asset discovery, port tracking, and historical comparisons, while the dark-web module uses Tor-based scraping to detect brand or credential mentions and trigger alerts. Everything will be containerized with Docker Compose for one-command setup, using PostgreSQL or MongoDB, plus a simple dashboard for visibility and alerts via email, Slack, or webhooks. I’ll prioritize an MVP with core scanning and alerting first, then iterate quickly. I focus on clean, documented, testable code and fast delivery. I’d be happy to discuss your target and get started right away. Best regards

@GrowthGateMedia

Hi, This is exactly the kind of system I build — modular, API-driven, and designed to deliver usable insights quickly. I understand you’re not looking for a slow build — you want a working MVP in days, then rapid iteration into a reliable monitoring system. That’s how I’d approach this. I’d start by getting a functional ASM + crawler running immediately (subdomains, ports, basic TOR scraping), then layer in tracking, correlation, and alerting on top of a clean FastAPI backend. The focus will be on keeping everything modular so both ASM and dark web monitoring share the same API layer and scale properly. I’m comfortable working with Python, FastAPI, Dockerized environments, and scraping pipelines, and I understand the importance of stability (failover, clean data handling, and reliable alerts) in this kind of system. You’ll have a working prototype within days — not weeks — and a complete, production-ready setup shortly after. — Adam