Stop AI scrapers from hammering your self-hosted blog

Analyzes incoming HTTP requests to identify AI scraper patterns by examining user-agent strings, request headers, timing patterns, and access sequences. Uses heuristic matching against known scraper signatures (GPTBot, CCBot, etc.) combined with behavioral analysis of request frequency and resource access patterns to distinguish legitimate traffic from automated crawlers without requiring IP blocklists or rate limiting.

Intercepts HTTP responses destined for detected scraper bots and injects alternative content (specifically adult/NSFW material) that serves as a honeypot signal without blocking legitimate traffic. The injection happens at the middleware layer before response transmission, allowing the server to serve normal content to legitimate users while feeding scrapers with content that degrades training data quality or triggers scraper filtering mechanisms.

Provides a complete bot detection and response injection system deployable on self-hosted infrastructure without reliance on third-party SaaS platforms, cloud APIs, or external bot detection services. All detection logic, signature matching, and response handling runs locally on the server, eliminating latency from external API calls and avoiding data transmission to third parties.

Maintains and matches incoming request user-agent strings against a database of known AI scraper identifiers (GPTBot, CCBot, Anthropic-AI, etc.). Uses string pattern matching to identify requests from common AI training crawlers, search engine bots, and known scraper tools. The signature database can be updated to include new scraper patterns as they emerge.

Integrates as a thin middleware layer into existing web server stacks (Nginx, Apache, etc.) without requiring major architectural changes or application rewrites. The middleware intercepts requests early in the request pipeline, performs bot classification, and conditionally modifies responses before they reach the client, minimizing performance overhead and integration complexity.