Automated Vehicle Data Crawler with Anti-Bot Bypass
A robust WinForms-based crawler app that mimics human behavior to bypass anti-bot systems and extract vehicle data, documents, and related media from classified websites.
This Windows-based crawler application was built for a client needing to automate the extraction of used vehicle data from a high-traffic classified site. Built with C#, .NET Framework, WinForms, and Selenium, the app uses ChromeDriver with rotating proxies to bypass bot detection and simulate human interactions like scrolling, clicking, and timed browsing.
The crawler extracts detailed vehicle specifications, price, location, and media attachments (including documents and YouTube videos). It categorizes the data and saves each vehicle’s information in structured folders organized by make, model, or region.
Additionally, the application incorporates anti-captcha bypass mechanisms to ensure uninterrupted crawling across sessions. This solution allows businesses to perform market analysis, competitor research, or build proprietary vehicle databases with minimal manual intervention.
Client Benifits
This crawler replaced the need for manual scraping, enabling the client to gather data at scale without triggering security mechanisms. It provided categorized, ready-to-use datasets for business analysis and documentation.
Bypassed 99% of Anti-Bot Measures
Seamless crawling across protected platforms with human-like behavior simulation.
Organized 50,000+ Vehicle Records
Data was stored in a structured folder system with supporting documents and videos.
Downloaded 20,000+ YouTube Clips & PDFs
Efficient media and document acquisition process for each vehicle listing.
Achieved 70% Faster Data Acquisition
Compared to manual processes, crawling was significantly faster and more scalable.
