Open folder
Open your project folder in the chat interface.
Your login page receives many automated attempts. DevSpan reads your access logs to find the abuse pattern. It writes a configuration file that caps requests per IP address. The agent runs a small test script against your staging server. You review the diff before accepting the change. You can distinguish scanning-like request patterns by behaviour, such as request rate, failing logins, and odd paths, rather than relying on user-agent text. To stop vulnerability scanning bots on my site, you should monitor these patterns closely.
Open your project folder in the chat interface.
Use grep to find repeated login failures.
Use write_file to create the limits plan.
Run your test command to verify the limit.
https://staging.example.com/api/loginstatus 200access.log pattern=4293 matchestest_script.phpexit 0rate-limits.txtsaved# Rate limits for staging
route=/api/login limit=5 window=60s action=429
route=/api/reset limit=3 window=60s action=429
route=/api/data limit=20 window=60s action=429
route=/api/health limit=60 window=60s action=200
# Monitoring allowed
route=/api/monitor limit=100 window=60s action=200This plain text file defines rules for your own routes. Each line sets a limit and window for a specific path.
DevSpan reads your access logs to identify unusual request patterns and writes a configuration file that sets a cap once deployed for your own staging server. You review the diff. The agent caps requests per IP address for each unique user. You can prevent bots from form submission by limiting the rate of requests from a single source. The agent runs a small test script against your staging server to verify the limit. This approach protects inventory from scalping bots by restricting traffic. Bot mitigation often starts with form submissions that spam your database. The agent does not block traffic itself but prepares the rules you deploy.
DevSpan locates scanning patterns in your access logs and writes a configuration file that blocks excessive requests from those sources so the server stays stable. It simulates. You review the diff before accepting the change to verify the exact limits. This approach provides effective anti bot protection for your specific routes. Bot mitigation helps maintain stability for your specific routes and services. You can protect inventory from scalping bots by applying these same limits to your checkout endpoints. The agent prepares the rules and code that you deploy to your own server. Limits reduce load from repeated requests but very heavy traffic needs protection from the host or provider.