Complex Application Attack Quantification, Testing, Detection and Prevention
An apparatus and method for cyber risk quantification calculated from the likelihood of a cyber-attack on the target enterprise and/or cyber ecosystem based on its security posture. The cyber-attack likelihood can be derived as a probability-based time-to-event (TTE) measure using survivor function analysis. The likelihood probability measure can also be passed to cyber risk frameworks to determine financial impacts of the cyber-attacks. Embodiments of the present invention also relate to an apparatus and method (1) to identify and validate application attack surfaces and protect web applications against business logic-based attacks, sensitive data leakage and privilege escalation attacks; and/or (2) that protects web applications against business logic-based attacks, sensitive data leakage and privilege escalation attacks. This can include implementing an intelligent learning loop using artificial intelligence that creates an ontology-based knowledge base from application request and response sequences. Stochastic probabilistic measures are preferably applied to a knowledge base for predicting malicious user actions in real time.
1 . A method for providing intelligent web application security comprising:
creating a comprehensive application attack surface by providing a feedback learning loop configured to implement an intelligent interceptor module and a data capture module, the feedback learning loop enhancing an application knowledge base in real time;
configuring the intelligent interceptor module to capture synchronous and asynchronous HTTP requests and response sequences within a target application resulting from user actions in real time and passing them to a data processing module, wherein synchronous HTTP requests and response sequences comprise traditional GET and POST HTTP requests between a client and a server where each response from the server entirely replaces a currently displayed web page that belongs to the target application on a client side and wherein asynchronous HTTP requests and responses comprise HTTP request, response sequences using technologies that modify a Document Object Model state of a target web page that belongs to the target application without having to reload Hie target web page completely;
tle data processing module creating structured content hierarchy from captured unstructured HTTP {S) data and passing it to a knowledge module;
tle knowledge module creating a concept hierarchy from the structured content, hierarchy, the knowledge module further generating target application's ontology from the concept hierarchy and storing it in a knowledge base; and
an intelligent scanner creating offensive ontology-based payloads while testing tile target application for complex web application attacks.