Abstract: A technique to detect script-based attacks. In this approach, behavioral analysis is performed against a traceable data structure, preferably in the form of a call flow graph (CFG) that is generated at an instrumented end user client browser. The CFG comprises a set of runtime script execution data points and one or more associated event chains that include the execution data points and their relative ordering. It is generated in a client browser in association with an interaction with a page, and it represents a context-based record of that specific interaction. By collecting similar CFGs from other such interactions with that page, the system identifies execution flow anomalies that represent malicious JavaScript attack(s). These attacks can then be mitigated, e.g., by updating the page or access policy associated with the page such that the attack cannot be successfully executed against other users interacting with the page.

Abstract: A method and system of detecting script-based attacks. In this approach, behavioral analysis is performed against a traceable data structure, preferably in the form of a call flow graph (CFG) that is generated at an instrumented end user client browser. The CFG comprises a set of runtime JavaScript execution data points and one or more associated event chains that include the execution data points and their relative ordering. It is generated in a client browser in association with an interaction with a page, and it represents a context-based record of that specific interaction. By collecting similar CFGs from other such interactions with that page, the system identifies execution flow anomalies that represent malicious JavaScript attack(s). These attacks can then be mitigated, e.g., by updating the page or access policy associated with the page such that the attack cannot be successfully executed against other users interacting with the page.

Abstract: A method and system of detecting script-based attacks. In this approach, behavioral analysis is performed against a traceable data structure, preferably in the form of a call flow graph (CFG) that is generated at an instrumented end user client browser. The CFG comprises a set of runtime JavaScript execution data points and one or more associated event chains that include the execution data points and their relative ordering. It is generated in a client browser in association with an interaction with a page, and it represents a context-based record of that specific interaction. By collecting similar CFGs from other such interactions with that page, the system identifies execution flow anomalies that represent malicious JavaScript attack(s). These attacks can then be mitigated, e.g., by updating the page or access policy associated with the page such that the attack cannot be successfully executed against other users interacting with the page.

Abstract: A system and method for bypassing 3rd party request-blocking, comprising: at least one system server running a server application; at least one asset serving system communicating with said system server over the internet; a system application running on an application server, said application server communicating over the internet with said system server; at least one publisher's content server communicating over the internet with said system application; and a plurality of user communication devices communicating over the Internet with the system application, said server application configured to continuously create and update a block bypass package comprising scripts comprising secured formations for said at least one publisher's web pages, said system application configured to inject said scripts into said at least one publisher's web pages and to selectively redirect asset requests from said plurality of user communication devices' browsers to said at least one system server or to said at least one publis