Jul 2013, SANS Digital Forensics and Incident Response Summit 2013
https://www.sans.org/event-downloads/30107/agenda.pdf
Incident response against malware infection generally takes long time for
memory forensics, disk forensics and malware analysis. It's desirable to
find and identify malware at an early stage performing memory forensics,
but it requires expert knowledge about malware.
In this session, I show "volatile IOCs (Indicators of Compromise)" to
detect some famous malware (e.g., ZeuS, SpyEye, Poison Ivy) from physical
memory images. By using the IOCs, everyone can pinpoint the type of malware
without disk forensics and malware analysis. Audiences can also grasp the
techniques of fast malware triage.
Specifically, I explain how to define volatile IOCs using OpenIOC, that is
an extensible XML schema for describing technical characteristics of known
threats. Some IOCs are already available on the Internet, but most of them
are difficult to reuse and need non-volatile information such as file hash
values and file names. Volatile IOCs introduced in this session can
identify malware including its variants based on only volatile evidences
like header signatures of data structures, deobfuscated strings and a sign
of code injection in memory space.