Network Security Fundamentals: Looking for Not Normal

To state the obvious (as I tend to do), we all have too much to protect. No one gets through their list every day, which means perhaps the most critical skill for any professional is the ability to prioritize. We’ve got to focus on the issues that present the most significant risk to the organization (whatever you mean by risk) and act accordingly. I have’t explicitly said it, but the key to network security fundamentals is figuring out how to prioritize. And to be clear, though I’m specifically talking about network security in this series, the tactics discussed can (and need to) be applied to all the other security domains. To recap how the fundamentals enable this prioritization, first we talked about implementing default deny on your perimeter. Next we discussed monitoring everything to provide a foundation of data for analysis. In the last post, correlation was presented to start analyzing that data. By the way, I agree with Adrian, who is annoyed with having to do correlation at all. But it is what it is, and maybe someday we’ll get all the context we need to make a decision based on log data, but we certainly can’t wait for that. So to the degree you do correlate, you need to do it effectively. Pattern Matching Going hand in hand with prioritization is the ability to match patterns. Most of the good security folks out there do this naturally, in terms of consuming a number of data points, understanding how they fit together, and then making a decision about what that means, how it will change things and what action is required. The patterns help you to understand what you need to focus on at any given time. The first fundamental step in matching patterns involves knowing your current state. Let’s call that the baseline. The baseline gives you perspective on what is happening in your environment. The good news is that a “monitor everything” approach gives you sufficient data to establish the baseline. Let’s just take a few examples of typical data types and what their baselines look like: Firewall Logs: You’ll see attacks in the firewall logs, so your baseline consists of the normal number/frequency of attacks, time distribution, and origin. So if all of a sudden you are attacked at a different time from a different place, or much more often than normal, it’s time to investigate. Network Flows: Network flows show network traffic dynamics on key segments, so your baseline tells you which devices communicate with which other devices – both internal and external to your network. So if you suddenly start seeing a lot of flow from an internal device (on a sensitive network) to an external FTP site, it could be trouble. Device Configurations: If a security device is compromised, there will usually be some type of configuration and/or policy change. The baseline in this case is the last known good configuration. If something changes, and it’s not authorized or in the change log, that’s a problem. Again, these examples are not meant to be exhaustive or comprehensive, just to give an idea about the types of data you are already collecting and what the baseline could look like. Next you set up the set of initial alerts to detect attacks that you deem important. Each management console for every device (or class of devices) gives you the ability to set alerts. There is leverage in aggregating all this data (see the correlation post), but it’s not necessary. Now I’ll get back to something discussed in the correlation post, and that’s the importance of planning your use cases before implementing your alerts. You need to rely on those thresholds to tell you when something is wrong. Over time, you tune the thresholds to refine how and when you get alerted. Don’t expect this tuning process to go quickly or easily. Getting this right really is an art, and you’ll need to iterate for a while to get there – think months, not days. You can’t look for everything, so the use cases need to cover the main data sources you collect and set appropriate alerts for when something is outside normal parameters. I call this looking for not normal, and yes it’s really anomaly detection. But most folks don’t think favorably of the term “anomaly detection”, so I use it sparingly. Learning from Mistakes You can learn something is wrong in a number of ways. Optimally, you get an alert from one of your management consoles. But that is not always the case. Perhaps your users tell you something is wrong. Or (worst case) a third party informs you of an issue. How you learn you’ve been pwned is less important than what you do once you are pwned. Once you jump into action, you’re looking at the logs, jumping into management consoles, and isolating the issues. How quickly you identify the root cause has everything to with the data you collect, and how effectively you analyze it. We’ll talk more about incident response later this year, but suffice it to say your only job is to contain the damage and remediate the problem. Once the crisis ends, it’s time to learn from experience. The key, in terms of “looking for not normal”, is to make sure it doesn’t happen again. The attackers do their jobs well and you will be compromised at some point. Make sure they don’t get you the same way twice. The old adage, “Fool me once, shame on you – fool me twice, shame on me,” is very true. So part of the post-mortem process is to define what happened, but also to look for that pattern again. Remember that attackers are fairly predictable. Like the direct marketers that fill your mailbox with crap every holiday season, if something works, they’ll keep doing it. Thus, when you see an attack, you’ll need to expect to see it again. Build another set of rules/policies to make sure that same attack is detected quickly and accurately. Yes, I know this is a black list mindset, and there are limitations to this approach since you

Read Post

New Release: Understanding and Selecting a Database Assessment Solution

The Securosis team is proud to announce the availability of our latest white paper: Understanding and Selecting a Database Assessment Solution. We’re very excited to get this one published – not just because we have been working on it for six months, but also because we feel that with a couple new vendors and a significant evolution in product function, the entire space needed a fresh examination. This is not the same old vulnerability assessment market of 2004 that revolved around fledgling DBA productivity tools! There are big changes in the products, but more importantly there are bigger changes in the buying requirements and users who have a vested interest in the scan results. Our main goal was to bridge the gap between technical and non-technical stakeholders. We worked hard to provide enough technical information for customers to differentiate between products, while giving non-DBA stakeholders – including audit, compliance, security, and operations groups – an understanding of what to look for in any RFI/proof-of-concept. We want to especially thank our sponsors, Application Security Inc. (AppSec), Imperva, and Qualys. Without them, we couldn’t produce free research like this. As with all our papers, the content was developed independently and completely out in the open using our Totally Transparent Research process. We also want to thank our readers for helping review all our public research, and Chris Pepper for editing the paper. This is version 1.0 of the document, and we will continue to update it (and acknowledge new contributions) over time, so keep coming with the comments if you think we’ve missed anything, or gotten something wrong. Share:

Read Post

Totally Transparent Research is the embodiment of how we work at Securosis. It’s our core operating philosophy, our research policy, and a specific process. We initially developed it to help maintain objectivity while producing licensed research, but its benefits extend to all aspects of our business.

Going beyond Open Source Research, and a far cry from the traditional syndicated research model, we think it’s the best way to produce independent, objective, quality research.

Here’s how it works:

  • Content is developed ‘live’ on the blog. Primary research is generally released in pieces, as a series of posts, so we can digest and integrate feedback, making the end results much stronger than traditional “ivory tower” research.
  • Comments are enabled for posts. All comments are kept except for spam, personal insults of a clearly inflammatory nature, and completely off-topic content that distracts from the discussion. We welcome comments critical of the work, even if somewhat insulting to the authors. Really.
  • Anyone can comment, and no registration is required. Vendors or consultants with a relevant product or offering must properly identify themselves. While their comments won’t be deleted, the writer/moderator will “call out”, identify, and possibly ridicule vendors who fail to do so.
  • Vendors considering licensing the content are welcome to provide feedback, but it must be posted in the comments - just like everyone else. There is no back channel influence on the research findings or posts.
    Analysts must reply to comments and defend the research position, or agree to modify the content.
  • At the end of the post series, the analyst compiles the posts into a paper, presentation, or other delivery vehicle. Public comments/input factors into the research, where appropriate.
  • If the research is distributed as a paper, significant commenters/contributors are acknowledged in the opening of the report. If they did not post their real names, handles used for comments are listed. Commenters do not retain any rights to the report, but their contributions will be recognized.
  • All primary research will be released under a Creative Commons license. The current license is Non-Commercial, Attribution. The analyst, at their discretion, may add a Derivative Works or Share Alike condition.
  • Securosis primary research does not discuss specific vendors or specific products/offerings, unless used to provide context, contrast or to make a point (which is very very rare).
    Although quotes from published primary research (and published primary research only) may be used in press releases, said quotes may never mention a specific vendor, even if the vendor is mentioned in the source report. Securosis must approve any quote to appear in any vendor marketing collateral.
  • Final primary research will be posted on the blog with open comments.
  • Research will be updated periodically to reflect market realities, based on the discretion of the primary analyst. Updated research will be dated and given a version number.
    For research that cannot be developed using this model, such as complex principles or models that are unsuited for a series of blog posts, the content will be chunked up and posted at or before release of the paper to solicit public feedback, and provide an open venue for comments and criticisms.
  • In rare cases Securosis may write papers outside of the primary research agenda, but only if the end result can be non-biased and valuable to the user community to supplement industry-wide efforts or advances. A “Radically Transparent Research” process will be followed in developing these papers, where absolutely all materials are public at all stages of development, including communications (email, call notes).
    Only the free primary research released on our site can be licensed. We will not accept licensing fees on research we charge users to access.
  • All licensed research will be clearly labeled with the licensees. No licensed research will be released without indicating the sources of licensing fees. Again, there will be no back channel influence. We’re open and transparent about our revenue sources.

In essence, we develop all of our research out in the open, and not only seek public comments, but keep those comments indefinitely as a record of the research creation process. If you believe we are biased or not doing our homework, you can call us out on it and it will be there in the record. Our philosophy involves cracking open the research process, and using our readers to eliminate bias and enhance the quality of the work.

On the back end, here’s how we handle this approach with licensees:

  • Licensees may propose paper topics. The topic may be accepted if it is consistent with the Securosis research agenda and goals, but only if it can be covered without bias and will be valuable to the end user community.
  • Analysts produce research according to their own research agendas, and may offer licensing under the same objectivity requirements.
  • The potential licensee will be provided an outline of our research positions and the potential research product so they can determine if it is likely to meet their objectives.
  • Once the licensee agrees, development of the primary research content begins, following the Totally Transparent Research process as outlined above. At this point, there is no money exchanged.
  • Upon completion of the paper, the licensee will receive a release candidate to determine whether the final result still meets their needs.
  • If the content does not meet their needs, the licensee is not required to pay, and the research will be released without licensing or with alternate licensees.
  • Licensees may host and reuse the content for the length of the license (typically one year). This includes placing the content behind a registration process, posting on white paper networks, or translation into other languages. The research will always be hosted at Securosis for free without registration.

Here is the language we currently place in our research project agreements:

Content will be created independently of LICENSEE with no obligations for payment. Once content is complete, LICENSEE will have a 3 day review period to determine if the content meets corporate objectives. If the content is unsuitable, LICENSEE will not be obligated for any payment and Securosis is free to distribute the whitepaper without branding or with alternate licensees, and will not complete any associated webcasts for the declining LICENSEE. Content licensing, webcasts and payment are contingent on the content being acceptable to LICENSEE. This maintains objectivity while limiting the risk to LICENSEE. Securosis maintains all rights to the content and to include Securosis branding in addition to any licensee branding.

Even this process itself is open to criticism. If you have questions or comments, you can email us or comment on the blog.