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Security In Context

Bringing you news and commentary on solutions and strategies for protecting your critical IT infrastructure.

Who is To Blame When An Insider Breach Occurs?

Post by Peter McCalister February 6, 2012

As I’ve waded through the hundreds of published insider breaches from just the last two years, what was a clear recurring theme was that of the vagaries of human nature. Not meaning to wax poetic, but it was always an individual who misused their own, or some other insider’s, privileged access authorizations to IT systems to their own devices and/or gains.

That begs two questions:

What sets these people on their path to misuse of privilege?
Are they personally responsible or is the organization’s lack of controls partially responsible as well?

As I have pointed out many times—at the intersection of people, processes, and technology that make up the engine of modern business—it’s human nature that is the weakest link. And, all too often, it’s the tendency of almost the entire IT industry—vendors, analysts, and press—to ignore this.

Put another way, you can’t rely on everyone being a saint or competent all of the time. It’s not just malicious malcontents intent on destroying the system who can cause havoc, but also the negligent, misinformed, and down-right nosey who can compromise sensitive data. In all cases, it’s more often than not the case that such people have way too much privilege access— admin rights on the desktop, root password on the server—for the role they are required to play.

Indeed, when technology is to blame, it’s not always the technology company’s use; it’s the failure to recognize the importance of technology, such as privileged identity management (PIM) systems, which can restrain over-privileged users without hampering productivity, which is at fault. With increasing costs arising from data breaches, including cleanup costs, as well as customer churn due to diminished trust, it makes sense not to rely on trust alone when it comes to employee and third-party access to sensitive data.

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