Recently NT OBJECTives announced NTODefend and its ability to generate “perfect-fit” custom patches for WAF & IPS. This marketing term “perfect-fit” has been the cause of some questions. People are wondering how our “perfect-fit” rules differ from what other DAST vendors are doing, as well as solutions like ThreadFix (aka Vulnerability Manager) from Denim Group. Those who know me, know that I don’t like when vendors overstate their capabilities, and I make sure NTO does not do this either, so I think this term deserves some explanation.
The other solutions that are able to generate virtual patches work from pre-defined templates based on categories of attacks, such as SQL Injection, Cross-Site Scripting, OS Injection. So if a given input is vulnerable to SQL Injection, then the SQL Injection template will be used to generate a virtual patch for the vulnerable input.
NT Objectives’ approach differs in that NTODefend is able to generate rules based on deeper intelligence about the input. This extra information comes from two key features in NTOSpider:
- NTOSpider‘s input population technology works to determine the intended legitimate data. For example, the input population technology will determine if the input only accepts numbers, or is intended for a phone number, email address, street address, etc.
- NTOSpider’s attacking engines detail specifics about the attacks that worked, with information such as usable characters and escape sequences.
By leveraging details about the attacks, NTODefend can generate more specific and aggressive rules to function as counter-measures to the attacks that the input was vulnerable to. This can include making rules that only allow numerical values, or maybe blocking single quotes but not double quotes, or allowing parenthesis but not dashes. NTODefend can also decide which canned filters to include to make sure the input is well protected.
The key point is that each rule is generated custom to the input AND custom to the ways it can be exploited.
After installing the virtual patches into the solution, NTODefend provides the ability to re-test all the inputs with both attack traffic and good traffic (modifiable database included with each data type NTOSpider can detect). It then generates a report to show which of the good request and bad requests got blocked. This provides users with the ability to quickly understand how effective the virtual patches were and hopefully alerts them to any virtual patches that could be blocking good traffic.
We do not claim that these generated virtual patches will always be 100% accurate to all situations, but we are confident that they will be useful and that we provide solutions for users to quickly deal with discovered vulnerabilities.
I welcome discussion and questions on this topic.
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