Combatting Mac OSX iOS Malware with Data Visualization
Remy Baumgarten explores combatting mac osx ios malware with data visualization at DEF CON 21, examining mobile-security and practical defenses.
Summary
Architecture and Background
Combatting Mac OSX/iOS Malware with Data Visualization REMY BAUMGARTEN SECURITY ENGINEER, ANRC-SERVICES Apple has successfully pushed both its mobile and desktop platforms into our homes, schools and work environments. With such a dominant push of its products into our everyday lives it comes as no surprise that both of Apple's operating systems, OSX and iOS should fall under attack by malware developers and network intruders. Numerous organizations and Enterprises who have implemented BYOD (bring your own device) company policies have seemingly neglected the security effort involved in protecting the network infrastructure from these potential insider threats.
Vulnerability Analysis
The complexity of analyzing Mach-O (Mach object file format) binaries and the rising prevalence of Mac-specific malware has created a real need for a new type of tool to assist in the analytic efforts required to rapidly identify malicious content. In this paper we will introduce Mach-O Viz, a Mach-O Interactive Data Visualization tool that lends itself to the role of aiding security engineers in quickly and efficiently identifying potentially malicious Mach-O files on the network, desktop and mobile devices of connected users. Remy Baumgarten (@anrctraining) is a security developer and researcher for ANRC, a fast growing market leader in computer security training and consulting.
Exploitation and Demonstrations
He is highly skilled in reverse engineering and malware analysis on various platforms including Windows, OSX, Linux and iOS. He is also a low level programmer on various platforms. Before joining ANRC Mr.
Remediation and Defensive Strategies
Baumgarten was a Technical Lead on the Malware Team and the mobile expert on iOS at Booz Allen Hamilton. In his spare time he enjoys delving into various architectures such as AVR, ARM and x86_64. LinkedIn: Materials:
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