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How to Detect Zero Day Attacks with an Analytics-Driven SIEM

While a great deal of damage is done to enterprise systems with known security exploits attacking unpatched or unattended systems, security professionals are most wary of zero day attacks.  These attacks work through previously unknown vulnerabilities, and there is no ready fix that addresses them.  Attackers are coming up with new ways to exploit systems every day, so the unknown is a very real threat to enterprise systems and networks.

These attacks can do a wide variety of things, depending on their focus.  They might elevate a user’s privileges so that more data can be found and stolen, or they could find a way into a running application or data lake to infect other systems.  There is no hard and fast guidance on how to recognize and deal with zero day attacks.

What is the target of the Next Zero Day Attack?

Security analysts have no idea what the next zero day attack will be targeting.  It’s not possible to even guess what unknown vulnerability will be the next one taken advantage of.  It could be a vulnerability to a known commercial application, an attack on custom enterprise software, a data lake exploit, or a common open source library.

They may not even be aware of an attack until their organization is compromised.  And they may have to wait days or even weeks for a fix to the vulnerability.  In other words, analysts and administrators have to remain vigilant not just for immediate attacks to the networks, but also for ongoing attacks until a solution becomes available and is tested.

While zero day attacks aren’t particularly common, they represent an unknown that security analysts have to understand and plan for.  Yet it’s a challenge to plan for an attack that you don’t know the nature of, and the type of damage it might do.  Many organizations are helpless in identifying and remediating a zero day attack.

It’s important to note that the attacker isn’t necessarily the discoverer of the zero day vulnerability.  It could be found by anyone, including legitimate and honest engineers and researchers who seek to give IT professionals new information about potential security holes in their software.  However, that still doesn’t mean that an attacker can’t develop and use an exploit before the vendor can issue a fix.  So wherever information about a zero day attack comes from, security analysts need to know about it in order to know what to look for.  And know when a fix becomes available.

What Is the Solution to Zero Day Attacks?

There is no hard and fast answer to addressing zero day attacks.  It is important to keep up with the latest security literature and news, because something may be published on a vulnerability without there being a fix at the moment.  Even if you can’t fix the issue, you can at least understand more about any attack.

A part of the problem is that the application vendor has no incentive, and plenty of disincentives, to publicize a zero day vulnerability immediately.  The vendor may well decide to wait until a fix is available.  So those who need that information may not get it before an attack occurs.  A zero day attack can come out of the blue, without any indication of what is being attacked and how.

That’s why zero day attacks require vigilance by all stakeholders in enterprise security.  Firewalls and anti-malware software are staples on any enterprise network.  But the problem with these tools is that they don’t help a great deal in identifying an attack never before seen.  Firewalls protect against unusual attempts to enter the network from outside, while anti-malware looks for specific signature indicating known malware in emails and on Web pages.

Monitoring the network and its traffic 24/7 is a given, even though it’s not clear what you’re looking for.  It’s likely to be something out of the ordinary, something that is not a normal run-of-the-mill network activity.

Finding those anomalies is like looking for needles in a haystack.  You don’t know what the attack is targeting or how it is targeting it.  And you’re looking at a great deal of data that may or may not be meaningful in the context of an attack.  Data that is not correlated by time series, system, or user may not be relevant to a real attack on the network.

Using an Analytics-Driven SIEM to Identify Zero Day Attacks

This is where a good machine learning-based Analytics-Driven SIEM comes in – like Gurucul’s.  SIEM solutions enable security analysts to observe the networks, systems, and applications from data generated by transactions.  The SIEM identifies transactions that appear out of the ordinary, and flags them for further investigation.

Using an Analytics-Driven SIEM, you analyze system and network logs and other data to identify potential attacks.  Further, thanks to machine learning (ML) algorithms, an advanced, modern SIEM is able to identify and learn patterns in the time series data.  This enables the SIEM to focus on only those abnormalities that may be an attack.

Because it is looking at all transaction data, however, it means that there are likely a number of false positives.  If security analysts have to chase down false positives, it takes away from their ability to find and remediate real zero day attacks.  But an Analytics-Driven SIEM using ML-based models can more easily eliminate false positives using security behavior analysis.

Firewalls and anti-malware remain necessary, but are not nearly sufficient to protect an organization from a zero day attack.  Traditional security tools, supplemented by an Analytics-Driven SIEM provide just the ticket to zero out those zero day attacks.

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