This project was created by researchers from ModSecurity and Fastly to help provide rigorous tests for WAF rules. It uses the OWASP Core Ruleset V3 as a baseline to test rules on a WAF. Each rule from the ruleset is loaded into a YAML file that issues HTTP requests that will trigger these rules.

Goals / Use cases include:

• Find regressions in WAF deployments by using continuous integration and issuing repeatable attacks to a WAF
• Provide a testing framework for new rules into ModSecurity, if a rule is submitted it MUST have corresponding positive & negative tests
• Evaluate WAFs against a common, agreeable baseline ruleset (OWASP)
• Test and verify custom rules for WAFs that are not part of the core rule set

• git clone git@github.com:fastly/ftw.git
• cd ftw
• Make sure that pip is installed apt-get install python-pip
• pip install -r requirements.txt

• Create YAML files that point to your webserver with a WAF in front of it
• py.test test/test_default.py --ruledir test/yaml

If you require an environment for testing WAF rules, there has been one created with Apache, Modsecurity and version 3.0.0 of the OWASP core ruleset. This can be deployed by:

• Checking out the repository: git clone https://github.com/fastly/waf_testbed.git
• Typing vagrant up

• start your test web server
• py.test test/test_default.py --ruledir=test/yaml --destaddr=domain.com --port 443 --protocol https

• py.test test/integration/test_logcontains.py -s --ruledir=test/integration/

1. Create a *.py file with the necessary imports, an example is shown in test/integration/test_logcontains.py
2. All functions with test* in the beginning will be ran by py.test, so make a function def test_somewaf
3. Implement a class that inherits LogChecker
4. Implement the get_logs() function. FTW will call this function after it runs the test, and it will set datetimes of self.start and self.end
5. Use the information from the datetime variables to retrieve the files from your WAF, whether its a file or an API call
6. Get the logs, store them in an array of strings and return it from get_logs()
7. Make use of py.test fixtures. Use a function decorator @pytest.fixture, return your new LogChecker object. Whenever you use a function argument in your tests that matches the name of that @pytest.fixture, it will instantiate your object and make it easier to run tests. An example of this is in the python file from step 1.
8. Write a testing configuration in the *.yaml format as seen in test/integration/LOGCONTAINSFIXTURE.yaml, the log_contains line requires a string that is a regex. FTW will compile the log_contains string from each stage in the YAML file into a regex. This regex will then be used alongside the lines of logs passed in from get_logs() to look for a match. The log_contains string, then, should be a unique rule-id as FTW is greedy and will pass on the first match. False positives are mitigated from the start/end time passed to the LogChecker object, but it is best to stay safe and use unique regexes.
9. For each stage, the get_logs() function is called, so be sure to account for API calls if thats how you retrieve your logs.

Although it is preferred to make requests using the YAML format, often automated tests require making many dynamic requests. In such a case it is recommended to make use of the py.test framework in order to produce test cases that can be run as part of the whole. Generally making an HTTP request is simple:

1. create an instance of the HttpUA() class
2. create an instance of the Input() class providing whatever parameters you don't want to be defaulted
3. provide the instance of the input class to HttpUA.send_request()

For some examples see the http integration tests