The Open Web Application Security Project (OWASP) is a community that produces information and tools in the field of web application security like the Core Rule Set (CRS). The CRS is a set of generic attack detection rules for use with ModSecurity. The CRS aims to protect web applications from a wide range of attacks, including the OWASP Top 10, with minimum false alerts. The Core Rule Set provides protection against many common attack categories including:
There are three types of important files included in this rule set: configuration, rule sets, and data files. The rule sets and data files are located in the rules folder while the configuration resides in the main directory. The list below will describe the file naming scheme and the purpose of each set of files.
crs-setup.confis the main configuration file for the CRS. It gives the user a way to edit the default actions of the CRS.
90Xfiles are rule exclusions to combat false positives.
91Xfiles detect malicious clients (scanners and bots).
92Xfiles detect protocol violations.
94Xfiles detect application attacks (SQLi, LFI, XSS, PHP, RFI, LFI).
95Xfiles detect data leaks.
*.datafiles hold information for the previous rules. For example
sql-errors.datawill be used to scan the response body for SQL errors, to prevent data leakages.
A disruptive action occurs when a successful rule blocks or denies a request. As of ModSecurity V3, the default scoring method is called Anomaly Scoring. Anomaly Scoring is less harsh than Traditional disruptive methods. The goal of Anomaly Scoring is to reduce the number of false positives. To do this, there is a threshold that must be hit for a disruptive action to occur. Each successful SecRule will increment a counter rather than block automatically. This is done using the
As shown above, the variable
anomaly_score is incremented by
critical_anomaly_score, a variable set in
crs-setup.conf in rule
900110. Specific rules can be set to block a request once a specific anomaly score threshold has been broken. There are four default anomaly scoring levels:
critical_anomaly_score, set to 5, is generated by application attack rules (
94Xfiles). This usually results in an automatic deny/block.
error_anomaly_score, set to 4, is generated by outbound leakage rules (
95X files). This usually results in an automatic deny/block.
warning_anomaly_score, set to 3, is generated by malicious client rules (
notice_anomaly_score, set to 2, is generated by protocol rules (
The two main anomaly score are
outbound_anomaly_score_threshold, set to 5 and 4 by default. These thresholds represent request threshold and response threshold. There are other thresholds used throughout the CRS. Some SecRules check just against the anomaly score, like the example above. Another example is
sql_injection_score which scores the risk of SQLi related issues. Other thresholds are set in the file
REQUEST-901-INITIALIZATION.conf in rule
Another way to combat false positives is the inclusion of a paranoia level. The paranoia level dictates how many rules should be considered. The higher the paranoia level, the more rules that are enabled, possibly creating false positives. The default paranoia level is 1. Rules with a paranoia level 2 or higher will log be logged in the audit log. The paranoia level is set in the file
REQUEST-901-INITIALIZATION.conf in rule
900000. The paranoia levels are as follows:
Before going into production, it is best to see how Varnish WAF works with the current web application. There can be false positives blocking users where they should not be blocked and take up unnecessary compute resources. A method to scale down the amount of false positives is shown in the following steps:
crs-setup.confset the rule,
900110, containing the inbound and outbound anomaly thresholds to a very high number such as 1,000 to make sure all requests pass through (resulting in no little to no blocked requests).
O’Reilly has a tutorial about limiting the amount of false positives that follows similar logic as the one described above but with some useful grep based tools to further examine the amount of false positives. Furthermore, some other tools that will help you navigate your web application looking for vulnerabilities like those in the OWASP top 10, include OWASP’s Zed Attack Proxy Protocol, Zap, and Nikito. Both of these tools are open source projects that scan and attack web applications to help fill security holes. The usage of these tools are outside of the scope of this documentation.