Carbon Black Partners with IBM on Active Attack Remediation

Mike Vizard
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5 Essential Incident Response Checklists

Military service has been described as consisting of long periods of boredom punctuated by moments of sheer terror. The hope is that training will kick in at crucial moments to enable personnel to perform the right action at the right time in the face of all adversity.

Looking to make it simpler for IT security professionals to respond similarly in the face of a cybersecurity attack, Carbon Black has partnered with IBM to create an offering that promises to automatically remediate vulnerabilities once the vector of a particular attack is discovered.

Tom Barsi, senior vice president of business development for Carbon Black, says the two companies have tightly integrated endpoint protection software from Carbon Black with QRadar security analytics and Big Fix automated patch management software.

“The goal is to reduce the attack surface as quickly as possible,” says Barsi.

Under the terms of the alliance, Carbon Black is sharing security intelligence data with IBM, which in turn uses that information to advise IT security professionals where they have the most exposure as it pertains to a specific attack. Those IT professionals can then employ Big Fix to automatically deliver the patches in the most critically important order required.

Carbon Black and IBM are part of a much larger industry trend involving tighter coupling of endpoint security and automation to create a closed-loop approach to security that takes advantage of Big Data analytics. Those approaches not only promise to improve IT security, but they should also allow IT organizations to enable a IT security department to respond to an IT security attack with much greater alacrity.

Of course, none of this does much to prevent attacks from being launched in the first place. But by sharing data more proactively about those attacks, the amount of drama associated with responding to them should be considerably reduced, to the benefit of all concerned.


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