The First 90 Days.

When you take a new position, what is it you will do in the first 90 days? What do you want to learn? What do you wish to accomplish? Is it enough to plan a course of action or do you immediately need to fix something? “What is your plan for your first 90 days?” is a common interview question for executives. The candidate’s answer tells the prospective employer a few things about the person’s grasp of the challenges ahead, how they operate typically, the efficiency of their approach, and how well their expectations align. Most candidates are under no illusion about taking a new role. In the best case they are filling a gap in a growing company, but more often than not they are there to fix something broken. The question cements in the mind of the candidate what is expected of them stepping in the door. And more than any other point during your tenure with a company, your first 90 days sets your boss’ and coworkers’ impressions of your effectiveness.

Never in my career has fixing security been in my top 3 challenges for the first 90 days. It’s always been quality of service, failed process, a broken, product or a dysfunctional development team. I have never been a CISO or security officer so in the context of security, I don’t really know how I would answer the question “What would my first 90 days look like?” If you are a security practitioner, how would you answer the question? Or perhaps it is more interesting to ask non-security professionals what their 90-day plan for security is? What challenges could you hope to accomplish? Do you think you could come up with a security program in that amount of time? I am interested in your thoughts on this subject. Is research on the establishment of a security program interesting to you? Let us know what you think.

On to the Friday Summary:

Webcasts, Podcasts, Outside Writing, and Conferences

Favorite Securosis Posts

Other Securosis Posts

Favorite Outside Posts

  • Rich: Amrit’s post on Gartner, and working for Gartner. For the record, analysts are very well insulated from financial considerations that could affect research. That said, people who pay to speak to analysts get more time with them, and that can subtly affect opinions.
  • Adrian: My favorite post was also Amrit’s, both for his honest quadrant diagram and for the commentary. To be honest, I felt for ZL as Gartner has the power to cut a company’s sales in half, but I agree with their assessments more than I disagree. My favorite tweet was from @securityincite: “@rmogull Would someone please give Rich some work to do? He’s loitering in shopping malls now. Next he’ll be upgrading to Windows Mobile”.
  • Mortman: @RSnakes on a Plane. (Mort sent this in Monday, he was so convinced).
  • Meier: Two out of five at risk from Wi-Fi Hijacking – Interesting that Talk Talk (the ISP in the UK) is taking this stance to protect end users from heavy-handed plans to tackle Internet piracy by Lord Mandelson.
  • Chris Pepper: Time Warner Cable Exposes 65,000 Customer Routers to Remote Hacks.

Top News and Posts

Blog Comment of the Week

This week’s best comment comes from Erik Swan (a Splunk employee -Adrian) in response to Splunk and Unstructured Data:

Thanks for mentioning Splunk, and your post brings up interesting points.

We recommend that people dump “everything” into splunk and just keep it. I’d go further and say that i’d bet that far less than 1% of that data is ever looked-at/reported on/etc. As you point out, its likely harder and more risky to remove data than keep it. This clearly changes when you talk about multiple T per day ( average large system these days ), where even for a wealthy company, the IO required is very expensive and not sure the data has value/risk. My gut is that data generation growth is clearly outpacing the size/price curve per GB, and will likely do so until massively more scaleable and cost effective media is available.

For the time being, keeping everything is likely the best starting point.

At the same time, we have seen models that look a lot like email spam filtering, where “uninteresting” data is routed to different instances that have shorter retention policies. Summarization is used to capture and compress the data hopefully with no information loss. Not a great practice for compliance, but for trouble shooting and analytics can work. Longer term its an interesting area for research and something that due to the size of data we deal with needs to be solved.

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