Fortinet 151 FortiWeb 5.0 Patch 6 Administration Guide
Auto-learningProtection settings can be configured manually or with assistance from auto-learning.
Auto-learning can teach you a great deal about the threats your web assets face. It also helps
you to understand your web applications’ structures, and how end-users use them. Most
importantly, though, auto-learning can help you to quickly tailor FortiWeb’s configuration to suit
your web applications.
Auto-learning discovers the URLs and other characteristics of HTTP and/or HTTPS sessions by
observing traffic that is passing to your web servers. It:
• compares the request to attack signatures
• observes inputs such as cookies and URL parameters
• tracks your web servers’ response to each request, such as 401 Unauthorized or
500 Internal Server Error
to learn about whether the request is legitimate or a potential attack attempt. By learning from
your traffic, the FortiWeb appliance can suggest appropriate configurations, and help you to
quickly generate profiles designed specifically for your unique traffic.
How to adapt auto-learning to dynamic URLs & unusual parameters
When web applications have dynamic URLs or unusual parameter styles, you must adapt
auto-learning to recognize them.
By default, auto-learning assumes that your web applications use the most common URL
structure:
• All parameters follow after a question mark ( ? ). They do not follow a hash ( # ) or other
separator character.
• If there are multiple name-value pairs, each pair is separated by an ampersand ( & ). They
are not separated by a semi-colon ( ; ) or other separator character.
• All paths before the question mark ( ? ) are static — they do not change based upon input,
blending the path with parameters (sometimes called a dynamic URL).
For data centers, colocation centers, and complex web applications, auto-learning-assisted
configuration can save significant amounts of time compared to purely manual configuration.
However, auto-learning is also resource-intensive and can decrease performance while
gathering data. For strategies on minimizing the impact to your network, see “Running
auto-learning” on page 180 and “Regular expression performance tips” on page 615.
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