![]() ![]() ![]() There's a question of practicality as well: some approaches are more costly and difficult to implement. What approaches would you take to ensure that requests are coming from human users? How would you define human behavior as opposed to bot behavior, and what metrics can you use to discern the two? Imagine you are the person trying to detect and block bot activity. the user did actually click on the button) before the API request is made.Īnd many many more techniques. ![]() Mouse and keyboard tracking techniques: if the server knows that a certain API can only be called when the user clicks a certain button, they can write front-end code to ensure that the proper mouse-activity is detected (i.e. If too many requests fail to satisfy that condition, it's a telltale sign they might be coming from a bot. For example, the server may send down a certain key (via cookies, headers, in the response body, etc) and expect that your browser include or otherwise use that key for the subsequent request it makes to the server. In combination with other headers, a server might be able to figure out that requests are coming from an unknown or otherwise exploitative source.Ī stateful combination of authentication tokens, cookies, encryption keys, and other ephemeral pieces of information that require subsequent requests to be formed and submitted in a special manner. Browsers send predictable User-Agent headers with each request that helps the server identify their vendor, version, and other information. Regularity of incoming requests rate, for example, a sustained flow of 10 requests per second may seem like a robot programmed to make a request, wait a little, make the next request, and so on. Counting number of requests per IP per unit of time is a very common, and arguably effective, technique. Total number of requests from a certain IP per specific time frame, for example, anything more than 50 requests per second, or 500 per minute, or 5000 per day may seem suspicious or even malicious. At the core of all of them is to build heuristics and statistical models that can identify non-human-like behavior. There's a large array of techniques that internet service providers use to detect and combat bots and scrapers. ![]()
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