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This framework based on modules and libraries that can be used all together in different combos to get exactly what researcher/tester needs.

The malware landscape is characterised by its rapid and constant evolution.

Using this technique we found over 10 previously unknown vulnerabilities in popular WAFs such as Mod-Security, PHPIDS and Expose allowing us to mount SQL Injection and XSS attacks bypassing the firewalls.

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CANToolz is an open-source framework for working with CAN bus.

In this presentation we will demonstrate use-cases and examples of black-box analyses of CAN network and ECU devices.

Given such a model, we show how to construct, either manually or automatically, a grammar describing the set of possible attacks which are then tested against the obtained model for the firewall.

Moreover, if our system fails to find an attack, a regular expression model of the firewall is generated for further analysis.

Our deep learning system has high precision (99.96%) and high recall (88%).

Web Applications Firewalls (WAFs) are fundamental building blocks of modern application security.

For example, the PCI standard for organizations handling credit card transactions dictates that any application facing the internet should be either protected by a WAF or successfully pass a code review process.

Nevertheless, despite their popularity and importance, auditing web application firewalls remains a challenging and complex task.

We build a deep learning system for Android anti-malware.

We select high-quality app features data with only a little size, and use innovative normalization preprocessing, unique activation function and advanced multilayer artificial neural network to recognize the unknown malware variants and defense zero-day attacks.

This talk will introduce our work on AI based Antivirus using deep learning.

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