JavaScript is a popular technique for activating static HTML. JavaScript has drawn more attention following the introduction of HTML5 Standard. In proportion to JavaScript's growing importance, attacks (ex. DDos, Information leak using its function) become more dangerous. Since these attacks do not create a trail, whether the JavaScript code is malicious or not must be decided. The real attack action is completed while the browser runs the JavaScript code. For these reasons, there is a need for a real-time classification and determination technique for malicious JavaScript. This paper proposes the Analysis Engine for detecting malicious JavaScript by adopting the requirements above. The analysis engine performs static analysis using signature-based detection and dynamic analysis using behavior-based detection. Static analysis can detect malicious JavaScript code, whereas dynamic analysis can detect the action of the JavaScript code.

Recent web-based cyber attacks are evolving into a new form of attacks such as private information theft and DDoS attack exploiting JavaScript within a web page. These attacks can be made just by accessing a web site without distribution of malicious codes and infection. Script-based cyber attacks are hard to detect with traditional security equipments such as Firewall and IPS because they inject malicious scripts in a response message for a normal web request. Furthermore, they are hard to trace because attacks such as DDoS can be made just by visiting a web page. Due to these reasons, it is expected that they could result in direct damages and great ripple effects. To cope with these issues, in this article, a proposal is made for techniques that are used to detect malicious scripts through real-time web content analysis and to automatically generate detection signatures for malicious JavaScript.