Tag Archives: IOC

Indicators of Compromise (IOC’s)

indicators20 days have passed since my last post about how to do a live memory acquisition of a windows system for malware hunting and forensics purposes. In that article, I  explained the details on how to create a collector, collect the data, and import the data into Mandiant Redline. The second part will be about the investigation and how to look for threats using indicators of compromise (IOC). However, before part II , I would like to give a brief introduction to IOCs.

For those who never heard about indicators of compromise they are pieces of information that can be used to search and identify compromised systems . These pieces of information have been around since ages but the security industry is now using them in a more structural and consistent fashion . All types of companies are moving from the traditional way of handling security incidents. Wait for an alert to come in and then respond to it. The novel approach is to take proactive steps by hunting evil in order to defend their networks. In this new strategy the IOCs have a key role. When someone compromises a systems they leave evidence behind.  That evidence, artifact or remnant piece of information left by an intrusion can be used to identify the threat or the malicious actor. Examples of IOCs are IP addresses, domain names, URLs, email addresses, file hashes, HTTP user agents, registry keys, a service configuration change, a file is deleted, etc. With this information one could sweep the network/endpoints and look for indicators that the system might have been compromised. For more background about it you can read Lenny Zeltzer summary. Will Gragido from RSA explained it well in is 3 parts blog here, here and here. Mandiant also has this and this nice articles about it.

Now, different frameworks and taxonomy exist in the security industry in order to deal with IOCs. These frameworks are important in order to share information in a consistent, scalable, automated and repeatable way across different organizations. One initiative is the OpenIOC sponsored by Mandiant. OpenIOC uses an extensible XML schema that allows to describe the technical characteristics of an intrusion or malicious actor.  Another initiative is from the IETF Working Group who defined two standards. One for describing the observables of security incidents which is  The Incident Object Description Exchange Format (IODDEF) described in RFC 5070. The other is the Real-time Inter-network Defense (RID) described in RFC 6545 and is used to transport and exchange the IODEF  information. Other initiative is from MITRE that developed CyboX, STIX, and TAXII , all free for the community and with high granularity. In order to read more about these initiatives Chris Harrington from EMC Critical Incident Response Center has a nice presentation about it. Other resource is a very interesting study made last October by ENISA named Detect, SHARE, Protect – Solutions for Improving Threat Data Exchange among CERTs.

That being said, we can now start using these IOCs to defend our networks. One way is by gathering information from the investigations made by security researches or vendors with actionable intelligence. For example back in September 2013 the campaign “ICEFOG : A tale of cloak and three daggers” was released by Kaspersky. This report contains great technical details and significant amount of actionable information. Another example was the  NetTraveler campaign which has been disclosed in June 2013. This report describes a piece of malware was used to successfully compromise more than 350 high-profile victims across 40 countries. The report is well written and contained great technical details. On chapter 5 it presents a huge list of IOCs to help detect and eradicate this threat. Following that, Will Gibb from Mandiant converted the information from the NetTraveler report into the OpenIOC format.  With this IOCs one could import it into  Redline. Of course this was an effort made by a vendor to incentive the usage of his format but others could use any other standard or framework to collect this observable’s and turn them into actionable information.

On my next post I will show how to import IOCs in OpenIOC format into Redline and find Evil on my wife’s laptop!

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