Методы защиты от веб-скрапинга и как их обойти

Web scraping is an automated data collection from websites. It may be needed for various tasks, including information search, creation of information catalogs, monitoring changes and updates, as well as web indexing. However, web scraping (also known as parsing) is not always used solely for informational and statistical purposes — it is also applied in a number of other tasks, often related to commercial activities:

• Collection of valuable or paid data;
• Plagiarism or gaining unfair competitive advantage;
• Overloading a specific site’s server (as an act of a technical attack);
• Reducing revenue flows of competitors’ sites (parsing bots bypass subscription models);
• Distorting website traffic analytics. Therefore, site owners implement protections against scraping, guided by security, legal, and commercial considerations.

Existing Methods of Web Scraping and Ways to Circumvent Them

1. Speed limiting or IP blocking. Multiple and too frequent requests from one IP or its range are detected (for example, hundreds of requests per second), after which such IPs are blocked or request frequency is limited within a certain time frame. Workaround methods:

1. IP Rotation, using IPs from different ranges and regions.
2. Setting request delays and random intervals.
3. Introducing random actions between requests to imitate human user behavior.

1. User-Agent filtering. Blocking suspicious or missing HTTP headers. Workaround methods:

1. Mimicking real browser headers.
2. Periodic header changes.
3. Randomizing User-Agent strings between sessions.

1. Executing JavaScripts. Providing data only after full rendering of the webpage by client-side JavaScript, possibly with delay in rendering. Workaround methods:

1. Using headless browsers.
2. Using browser-based rendering services.

1. Captcha. Tasks related to human cognitive activity (recognition of objects in images, text input, rotating objects, etc.). Workaround methods:

1. Using automated or human-assisted services for recognition and solving Captchas.
2. Avoiding triggering Captcha by simulating human behavior on pages.
3. Using tools to prevent Captcha triggering.

1. Browser fingerprint recognition. Collecting data and analyzing device properties (WebGL, Canvas, fonts, operating system, screen extensions, etc.) to identify bots. Workaround methods:

1. Hidden plugins.
2. Data substitution tools.
3. Using real browser profiles with periodic rotation.

1. Cookie tracking. Monitoring sessions and analyzing them for "human" behavior. Workaround methods:

1. Processing cookie files with tools that simulate humane sessions.
2. Saving session information between requests.
3. Periodic cookie cleanup.

1. Adding invisible fields for filling out and submitting forms. Hidden Honeypot fields on web pages are usually filled only by bots, not humans, marking them as suspicious. Workaround methods:

1. Analyzing web pages for Honeypots to avoid filling and submitting hidden forms.

1. Token-based authorization specific to sessions. Issuing tokens to each visitor for each unique session. Workaround methods:

1. Pre-analyzing the page for such tokens before starting data collection requests.

1. Mouse movement analysis. Detects lack of mouse movement or unnatural movements that are uncharacteristic of humans. Workaround methods:

1. Mimicking natural mouse movements, including scrolling and clicking.
2. Using libraries that simulate natural mouse behavior.

1. Traffic pattern analysis. Tracking request frequency, sequence, timing, and other behaviors that may indicate automation. Workaround methods:

1. Simulating real human behavior when navigating the site’s page tree.
2. Adding random delays between requests.
3. Crawling pages in unpredictable order.

Conclusion

Modern web scraping is far from always harmless, so websites need to implement protection methods against it, differentiating between bots and human users.