Securosis

Research

Security Analytics Team of Rivals: A Glimpse into the Future

A lot of our research is conceptual, so we like to wrap up with a scenario. This helps make the ideas a bit more tangible, and provides context for you to apply it to your particular situation. To illuminate how the Security Analytics Team of Rivals can work, let’s consider a scenario involving a high-growth retailer who needs to maintain security while scaling operations which are stressed by that growth. So far our company, which we’ll call GrowthCo, has made technology a key competitive lever, especially around retail operations, to keep things lean and efficient. As scaling issues become more serious they realize their attack surface is growing, and may force shortcuts which exposure critical data. They has always invested heavily in technology, but less in people. So their staff is small, especially in security. In terms of security monitoring technologies in place, GrowthCo has had a SIEM for years (thanks, PCI-DSS!). They have very limited use cases in production, due to resource constraints. They do the minimum required to meet compliance requirements. To address staffing limitations, and the difficulty of finding qualified security professionals, they decided to co-source the SIEM with an MSSP a few quarters ago. The MSSP was to help expand use cases and take over first and second tier response. Unfortunately the co-sourcing relationship didn’t completely work out. GrowthCo doesn’t have the resources to manage the MSSP, who isn’t as self-sufficient as they portrayed themselves during the sales process. Sound familiar? The internal team has some concerns about their ability to get the SIEM to detect the attacks a high-profile retailer sees, so they also deployed a security analytics product for internal use. Their initial use case focused on advanced detection, but they want to add UBA (User Behavior Analysis) and insider threat use cases quickly. The challenge facing GrowthCo is to get its Team of Rivals – which includes the existing SIEM, the new security analytics product, the internal team, and the co-sourcing MSSP – all on the same page and pulling together on the same issues. Let’s consider a few typical use cases to see how this can work. Detecting Advanced Attacks GrowthCo’s first use case, detecting advanced attacks, kicks off when their security analytics product an alert. The alert points to an employee making uncharacteristic requests on internal IT resources. The internal team does a quick validation and determines that it seems legitimate. That user shouldn’t be probing the internal network, and their traffic has historically been restricted to a small set of (different) internal servers and a few SaaS applications. To better understand the situation, context from the SIEM can provide some insight into what the adversary is doing across the environment, and support further analysis into activity on devices and networks. This is a different approach to interacting with their service provider. Normally the MSSP gets the alert directly, has no idea what to do with it, and then sends it along to GrowthCo’s internal team to figure out. Alas, that typical interaction doesn’t reduce internal resource demand as intended. But giving the MSSP discrete assignments like this enables them to focus on what they are capable of, while saving the internal team a lot of time assembling context and supporting information for eventual incident response. Returning to our scenario: this time the MSSP identifies a number of privilege escalations, configuration changes, and activity on other devices. Their report details how the adversary gained presence and then moved internally, to compromise the device which ultimately triggered the SIEM alert. This scenario could just as easily have started with an alert from the SIEM, sent over from the MSSP (hopefully with some context) and then used as the basis for triage and deeper analysis, using the security analytics platform. The point is not to be territorial about where each alert comes from, but to use the available tools as effectively as possible. Hunting for Insiders Our next use case involves looking for potentially malicious activity by employees. This situation blurs the line between User Behavioral Analysis and Insider Threat Detection, which share technology and process. The security analytics product first associates devices in use with specific users, and then gathers device telemetry to provide a baseline of normal activity for each user. By comparing against baselines, the internal team can look for uncharacteristic (anomalous) activity across devices for each employee. If they find something the team can drill into user activity or pivot into the SIEM and use the broader data it aggregates to search and drill down into devices and system logs for more evidence of attacker activity. This kind of analysis tends to be hard on a SIEM, because the SIEM data model is keyed to devices, and SIEM wasn’t designed to performa a single analysis across multiple devices. That does not mean it is impossible, or that the SIEM vendors aren’t adding more flexible analysis, but SIEM tends to excel when rules can be defined in advance to correlate. This is an example of choosing the right tool for the right job. A SIEM can be very effective in mining aggregated security data when you know what to look for. Streamlining Audits Finally, you can also use the Team of Rivals to deal with the other class of ‘adversary’: an auditor. Instead of having an internal team spend a great deal of time mining security data and formatting reports, you could have an MSSP prepare initial reports using data collected in the SIEM, and have the internal team do some quick Q/A, optimizing your scarce security resources. Of course the service provider lacks the context of the internal team, but they can start with the deficiencies identified in the last audit, using SIEM reports to substantiate improvements. Once again, being a little creative and intelligently leveraging the various strengths of the extended security team, a particularly miserable effort such as compliance reporting can be alleviated by having the service provider do the heavy lifting, relieving load on the internal

Share:
Read Post
dinosaur-sidebar

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.