Network forensics is an important component of a successful security operations program. It is an important capability that provides a data of record for the incident responder and plays an important role in the daily security operations workflow. While the utility and importance of network forensics may be clear to the security professional, that value may be difficult to communicate to the business decision maker or executive. In this post, I’d like to discuss several business use cases for network forensics that may help communicate the value and business need for network forensics as an integral component of incident response.
When an organization discovers, or is notified of a breach, time becomes of the essence. The organization’s immediate focus becomes moving quickly from detection to containment. In order to make this move, the organization needs to answer a set of essential questions aimed at identifying the extent of the breach and the damage caused by it. This process is often called breach response and involves investigation, analysis, and forensics. Examples of some of the questions that will need to be answered are:
- How long has this activity been going on (i.e., when did the intrusion begin)?
- Is the activity still going on?
- How many systems were affected?
- What data was taken?
- Was any sensitive, proprietary, or confidential information taken?
These and other relevant questions are designed to focus the organization on rapidly identifying the extent of the damage, both for containment purposes, but also to address potential public relations, legal, and privacy concerns. For example, consider the case where a law enforcement agency approaches a business (of any size) and informs them that they have been breached and have been observed communicating with a known drop site. The organization will have many questions, including, among many others, those listed above. An accurate, cohesive, lossless data of record is required to properly answer all of the necessary questions. Further, it’s not sufficient merely collect the data, but rather, it must be easy to precisely, incisively, and rapidly extract that data for analysis and forensics.
On any network, there will be unusual or suspect activity from time to time. Sometimes, this unusual activity can be indicative of advanced threats and targeted activity. Many times, the threat actors are quite adept at keeping a low profile and executing actions on objectives subtly. For example, Advanced Persistent Threat (APT) actors may compromise an endpoint inside of an organization and slowly collect sensitive, proprietary, or confidential information to stage for subsequent exfiltration. While detecting this activity in an automated fashion would be ideal, this turns out to be very difficult in practice. As a result, if this activity is successfully detected within the organization (as opposed to via a third party), it is most often done so via hunting. Hunting is the activity through which skilled analysts use a variety of different analytical techniques to “slice and dice” the network traffic data in the “hunt” for this subtle malicious activity. The best analysts will want to issue targeted, precise, incisive queries designed to extract the proper forensics data rapidly, with minimal noise. This requires a network forensics capability that can rise to this challenge at enterprise network speeds and traffic volumes.
Metrics provide important data points to the decision maker and executive. As a recent example, let us consider the many new Top Level Domains (TLDs) that have become available for use. Attackers have already leveraged some of these TLDs for malicious purposes, and this activity will undoubtedly continue to increase. This example begs the question: If a TLD serves no legitimate business purpose and can only expose the organization to risk, should it be blocked proactively? I believe the answer to this question is yes. But how can we ensure that a TLD serves no business purpose? This is where the metrics and network knowledge become so crucial. Business decisions should be based on facts, and facts come from an accurate, precise data of record – the network forensics data. This is merely one example of the many business questions that can be answered with metrics driven by network forensics data. When business decision makers or executives need answers, it is best to be able to provide answers based on ground truth.
When leveraged properly, actionable intelligence can provide additional enrichment and maturity to a security operations program, as well as aid in the improved detection of intrusions. Leveraging intelligence properly involves many details, but one of the most important details is that a reliable data of record exists. After various Indicators of Compromise (IOCs) are received and vetted, they should be leveraged against a reliable data of record in order to maximize their value. There are two time-based aspects here – historical and ongoing. We can run IOCs against our historical data to check for evidence of intrusions present on the network from the past on through the current day. In addition to that, we should also monitor for evidence of intrusions on an ongoing basis and raise an event to the alert queue when we see that evidence. These are both productive activities, assuming that an accurate, cohesive, lossless data of record exists for us to run the IOCs against. Further, it is not merely enough to collect the data – we need to be able to rapidly and surgically extract the data through targeted, precise, and incisive queries. For example, an organization may receive a daily feed of malicious command and control domain names from one or more of its intelligence sources. That data needs to be run against a corresponding data of record to find instances of command and control activity present on the organization’s network indicating that some systems are compromised. A scalable network forensics solution, one that can both record all of the network data at high speed as well as make that data and meta-data available for analysis, is required in order to properly leverage intelligence.
Data from Domain Name System (DNS) queries and responses provide a wealth of insight into unusual or suspect activity that may be occurring on the network. For example, most users pointing their browsers at legitimate websites will request domain names that resolve to routable, public IP addresses. But what if a resource on the network repeatedly requests a domain name that resolves to private, non-routable IP address or one that has no resolution at all? Further, what if that domain name suddenly “comes alive” and begins resolving to a routable, public IP address and/or the resource begins exfiltrating data to that IP address? This is just one of many interesting applications of DNS query and response data. As interesting and crucial as this data is, many organizations struggle to maintain adequate visibility across their DNS infrastructure. There are many reasons why this is the case, but there is a solution. A network forensics platform collects layer 7 enriched meta-data for many application protocols, DNS among them. This provides an organization with a de facto DNS monitoring and passive DNS data collection system, without requiring the organization to invest in additional technology or hardware. It’s one of my favorite use cases for network forensics and likely one that will resonate with many readers. For smaller organizations, there is also the additional benefit of using using one network forensics technology for multiple purposes.
As the old saying goes, ask a stupid question, get a stupid answer. The modern attacker is intelligent and sophisticated. We would be naïve to think that we could identify a sly attacker’s subtle activity with dull, generic queries. If we want to find the intelligent attacker, we need to ask intelligent questions. Asking intelligent questions requires two fundamental components. The first required component is that the data be collected and its associated meta-data extracted and indexed for rapid search. The second required component is a robust query language that allows the analyst to ask incisive, targeted, precise, intelligent questions of the data. It’s likely not a surprise that a mature, scalable, powerful network forensics solution provides both of these required components. For example, say I am a mid-sized organization concerned by potential theft of intellectual property from my executives. With the right solution in place, I can precisely craft my alert logic so as to focus in on the specific employees, systems, data, and threats I am concerned with. In the absence of that capability, many organizations struggle to issue queries powerful enough to identify suspicious and malicious activity designed to behave subtly and fly under the radar.
There are many use cases for network forensics, but I’ve tried to list those that may help to reinforce the strong business need for network forensics. When the need arises to perform breach response or any of the other use cases listed above, the organization that has implemented a robust, scalable network forensics solution will fare better than the organization that has not. With the stakes so high these days, it would be a shame not to be prepared.