Signature-based Request Detection

Signature-based request detection is the second step. This approach identifies the HTTP request header features in user requests, matches mainstream development frameworks and HTTP libraries, stimulates known bots, and uses automated programs to detect bots. If a request matches a bot signature, the request will be handled based on the configured protective action.

Type	Description
Abnormal request header	A request header that does not contain User Agent or whose User Agent is empty is abnormal.
Impersonators of known bots	If this function is enabled, the system checks whether the source IP address of a known bot request is its valid client IP address to prevent spoofing.
Development frameworks and HTTP libraries	A mainstream development framework and HTTP library have the following features: aiohttp, Apache-HttpClient, Apache-HttpAsyncClient, Commons-HttpClient, HttpComponents, PhantomJS, CakePHP, curl, Jetty, wget, http-kit, python-requests, Ruby, WebClient, WinHttpRequest, HttpUrlConnection, OxfordCloudService, http_request2, PEAR HTTPRequest, Python-urllib, RestSharp, Mojolicious (Perl), PHP, libwww-perl, okhttp, HTMLParser, Go-http-client, axios, Dispatch, LibVLC, node-superagent, curb, Needle, IPWorks, lwp-trivial, Custom-AsyncHttpClient, Convertify, AsyncHttpClient, Embed PHP Library, Apache Synapse, node-fetch, electron-fetch, asynchttp, Dolphin http client, EventMachine HttpClient, httpunit, Zend_Http_Client, Python-httplib2, spray-can, http_requester, AndroidDownloadManager, bluefish, Java, git, and Prerender.cloud
Automation program	The service can detect automation programs with crawler behavior characteristics but unclear purposes.