Dark Reading is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

Operational Security //

Risk Management

6/1/2018
08:05 AM
Simon Marshall
Simon Marshall
Simon Marshall
50%
50%

Vulnerability Remediation: Best Practice or Best Guess?

A new study from Kenna Security and the Cyentia Institute finds that even the most well-thought-out vulnerability remediation strategy is no better than a good guess. However, machine learning could lead to better results.

If you don't want to hear (structured) criticism of your vulnerability remediation strategy, close your ears now. Because chances are, enterprise security teams are doing no better statistically than random chance.

That's the startling finding of a new study from the Cyentia Institute and Kenna Security, a San Francisco-based predictive cyber risk firm. The two analyzed five years' worth of historical vulnerability data from 15 sources, and found that current remediation approaches to prioritizing and resolving vulnerabilities are about as effective -- even sometimes less effective -- than tackling issues in a random order.

It's not that remediation techs are doing a bad job once they've identified an issue, it's that deciding what order to tackle them is leaving enterprises open to damage from unpatched exploits further down the checklist.

"Effective remediation depends on quickly determining which vulnerabilities warrant action and which of those have highest priority, but prioritization remains one of the biggest challenges in vulnerability management," Kenna CEO Karim Toubba said.

"Businesses can no longer afford to react to cyber threats, as the research shows that most common remediation strategies are about as effective as rolling dice," Toubba added.

Predictive, not reactive
The concept of handling vulnerabilities remains unchanged: identify and remediate as rapidly as possible against an increasing number and velocity of threats. What's new is a change in posture that seeks to become predictive, rather than reactive. In past years, IT security has used analog tuning to try and identify and prioritize remediation, but this approach is now outmoded.

"Fast forward to 2018, and risk-based intelligent vulnerability management platforms now consume terabytes of configuration data, asset data, vulnerability data and threat intelligence to create a fine-grained analysis of which systems really need immediate patching against current threats," said Jon Oltsik, a senior principal analyst with the Enterprise Strategy Group.

Now there's a drive to move beyond real-time assessment of data into forecasting risks before an attack is possible. But of course, that's not easy.

Enterprises have an average of between 18 million and 24 million vulnerabilities across 60,000 assets, according to Cyentia. Every day of the year, they're faced with handling about 40 new vulnerabilities, and last year saw this number peak -- double that of 2016 -- and tracking to further grow this year.

The challenge is increased because most published vulnerabilities aren't used by attackers -- about 75% of known vulnerabilities never have an exploit developed for them, and then only 2% are ever used in an attack. As enterprises try to sort the wheat from the chaff, they're pressured because about half of new vulnerabilities are published within two weeks, effectively giving companies only ten working days to find them.


Now entering its fifth year, the 2020 Vision Executive Summit is an exclusive meeting of global CSP executives focused on navigating the disruptive forces at work in telecom today. Join us in Lisbon on December 4-6 to meet with fellow experts as we define the future of next-gen communications and how to make it profitable.

Essentially, this requires as wide a data input funnel as possible, filtered by a risk scoring model that provides results that increase the probability that a vulnerability will be exploited.

And the key to all of this seems to be machine learning.

Which vulnerabilities are hot?
"We use Machine Learning to comb through all the vulnerabilities previously released to figure out exactly what about a vulnerability makes it likely that an attacker would write an exploit for it," Michael Roytman, Kenna's chief data scientist, told SecurityNow. "We consider around 100,000 variables in doing so, and once we have a good idea of what those factors are, we make a best guess for every new vulnerability as it comes out."

He takes a leaf out of Charles Darwin's On the Origin of Species, constantly evolving the platform to adapt to new vulnerabilities which continuously pop up in the order of several million every 24 hours. Rather than using all of these inputs as training data for the platform -- meaning a risk the platform would never properly mature -- Roytman employs the concept of the survival of the fittest.

The performance of the current model is measured against a potential new one, using recent historical data. Whichever performs the best is taken forward for the next 24 hours. The "genetic origin" of today's model was created from selecting the best of 400 such initial models by giving each thousands of passes over an initial data set.

"We made every mistake imaginable, but as long as we understood how the algorithms worked, and as long as we kept a cool head and measured performance using sound statistical testing, we kept making steps in the right direction," he explained.

Related posts:

— Simon Marshall, Technology Journalist, special to Security Now

Comment  | 
Print  | 
More Insights
Comments
Newest First  |  Oldest First  |  Threaded View
COVID-19: Latest Security News & Commentary
Dark Reading Staff 9/21/2020
Hacking Yourself: Marie Moe and Pacemaker Security
Gary McGraw Ph.D., Co-founder Berryville Institute of Machine Learning,  9/21/2020
Startup Aims to Map and Track All the IT and Security Things
Kelly Jackson Higgins, Executive Editor at Dark Reading,  9/22/2020
Register for Dark Reading Newsletters
White Papers
Video
Cartoon
Current Issue
Special Report: Computing's New Normal
This special report examines how IT security organizations have adapted to the "new normal" of computing and what the long-term effects will be. Read it and get a unique set of perspectives on issues ranging from new threats & vulnerabilities as a result of remote working to how enterprise security strategy will be affected long term.
Flash Poll
How IT Security Organizations are Attacking the Cybersecurity Problem
How IT Security Organizations are Attacking the Cybersecurity Problem
The COVID-19 pandemic turned the world -- and enterprise computing -- on end. Here's a look at how cybersecurity teams are retrenching their defense strategies, rebuilding their teams, and selecting new technologies to stop the oncoming rise of online attacks.
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2020-25596
PUBLISHED: 2020-09-23
An issue was discovered in Xen through 4.14.x. x86 PV guest kernels can experience denial of service via SYSENTER. The SYSENTER instruction leaves various state sanitization activities to software. One of Xen's sanitization paths injects a #GP fault, and incorrectly delivers it twice to the guest. T...
CVE-2020-25597
PUBLISHED: 2020-09-23
An issue was discovered in Xen through 4.14.x. There is mishandling of the constraint that once-valid event channels may not turn invalid. Logic in the handling of event channel operations in Xen assumes that an event channel, once valid, will not become invalid over the life time of a guest. Howeve...
CVE-2020-25598
PUBLISHED: 2020-09-23
An issue was discovered in Xen 4.14.x. There is a missing unlock in the XENMEM_acquire_resource error path. The RCU (Read, Copy, Update) mechanism is a synchronisation primitive. A buggy error path in the XENMEM_acquire_resource exits without releasing an RCU reference, which is conceptually similar...
CVE-2020-25599
PUBLISHED: 2020-09-23
An issue was discovered in Xen through 4.14.x. There are evtchn_reset() race conditions. Uses of EVTCHNOP_reset (potentially by a guest on itself) or XEN_DOMCTL_soft_reset (by itself covered by XSA-77) can lead to the violation of various internal assumptions. This may lead to out of bounds memory a...
CVE-2020-25600
PUBLISHED: 2020-09-23
An issue was discovered in Xen through 4.14.x. Out of bounds event channels are available to 32-bit x86 domains. The so called 2-level event channel model imposes different limits on the number of usable event channels for 32-bit x86 domains vs 64-bit or Arm (either bitness) ones. 32-bit x86 domains...