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The reality of any new technology, security or otherwise, rarely lives up to its promise. Once you move past the bright sheen of the product brochures and top-level user interfaces, only the practicalities of implementing the product in the real world remain. This is especially true of newer technologies we have little prior experience with, where our product expectations are defined by marketing, the press, and the rare peer reference. It's only after these tools are tested in the real world, under full production conditions, that we really start learning how to either best implement them, or kick them back to the vendor for a little more polish (and a compelling business use).
Data loss prevention (DLP) is one of the most promising, and least understood, security technologies to emerge during the last few years. It dangles promises of ubiquitous content protection before our eyes, with shadows of complexity and costs glooming over its shoulder. As with everything, the reality is somewhere in-between. We've interviewed dozens of DLP users (including our own contacts, random volunteers and vendor references) to find out how DLP works in the trenches of the real world. The result is a collection of lessons learned and use cases to help you avoid common pitfalls while deriving maximum value.
Lesson 1: Users are confused by a confusing market
One of the more significant findings when researching this article was discovering extensive confusion as to
One large airline we spoke with is using a generic network sniffer/forensics tool with some basic keyword policies instead of a DLP solution. But this approach has severe flaws, with the security manager saying, "I'm not sure we can actually see everything going on." They are also looking to add USB port blocking, but more to protect against malicious software than to limit data loss. They do expect to look at DLP in 2010 or 2011.
Even though there are only around a dozen full-suite DLP solutions on the market, nearly every major (and many minor) security vendor claims some sort of DLP capability. We call those tools that offer some sort of content awareness--such as regular expressions--on single channel, such as email, "DLP as a feature." But many tools claiming DLP don't even offer that basic functionality. When standard encryption tools market themselves as DLP, it's no wonder customers are confused.
Egress filtering made easy
Data loss prevention technology is designed to mitigate the threat posed by data exfiltration on a network. Follow these three steps to lessen your risk:
ENSURE your DLP has access to any outbound connections that might originate from your transaction processing network, especially dedicated pipes that are not monitored by anything on the standard enterprise gateway
DON'T RESTRICT your DLP tool to only certain types of network traffic or only protocols running on standard ports. Attackers will use different combinations to move stolen data off your network.
COMBINE your DLP with a network proxy. This is crucial to properly manage egress filtering, enabling DLP to block as much as possible.
SET your DLP to alert when it detects encrypted files; this forces attackers to use non-standard encryption.
Read the full tip here: How
to use DLP to stop data exfiltration
Lesson 2: Full DLP solutions take more effort to deploy, but are more
effective and easier to manage
Although you can whack a nail with a big enough wrench, it won't ever work as well as a hammer, and can't touch the efficiency of a nail gun. DLP as a feature does have its place--particularly for clients on a budget, or with only basic data protection needs, but our interviews consistently showed higher satisfaction among those using dedicated DLP suites. Many of the clients using DLP features described it as a temporary measure until they were ready to consider full DLP. One user stated, "We are watching the marketplace closely, but don't want to be an early adopter."
The tradeoff is that dedicated DLP does take more effort to deploy than merely flipping on a feature switch in another product, but deployment requirements are fairly low. On average, a 5,000-person organization can deploy network monitoring with email filtering in a few hours or days, using one to three Full Time Equivalents. Additional network blocking (Web and FTP) usually requires integration with an existing Web gateway, and deployment complexity scales almost linearly based on the number of egress points. Content discovery (data-at-rest scanning) is more resource intensive since you need to manually add storage repositories to scan. Each repository may only take a few seconds to minutes to add, but you have to first identify them and obtain administrative credentials. Endpoint monitoring takes time to test the software on your standard images, then deploys exactly like any other endpoint tool.
However, full DLP solutions include much more efficient workflow for managing policy violations, especially if compliance, human resources, or legal will be involved. They also allow users to create a single data protection policy, and then apply it across multiple channels, rather than defining the information in multiple tools.
Lesson 3: Set the right expectations and workflow early
While deploying the technology is fairly straightforward, many organizations find they struggle more with setting the right expectations, defining workflow and building policies. We once had a client install one vendor's product and start monitoring using default policies without defining any incident management procedures or workflow. They stated: "We don't want to snoop on employees, so we don't worry about involving management or human resources," without realizing that most data leaks come from employees, with likely legal and HR implications.
A typical mistake is failing to define what types of data you want to protect, and how you want to protect it, before buying a tool (then being disappointed in the result). The other major pre-selection mistake is failing to engage business unit managers outside of security. One reference purchased an endpoint-only tool to prevent information leaks onto USB devices, only to find the tool shelved once sales management started receiving complaints.
When expectations are set properly, and the tool and policies deployed in a phased manner, DLP projects tend to go smoothly with minimal overhead. On average, a 10,000 employee organization with a handful of policies only requires 1-3 FTEs, usually split part-time under multiple employees, to manage policy violations. When basic policies are deployed, such as credit card protection, that same team may handle organizations up to 50,000 or more employees. On the other end, using poorly tuned or low threshold policies will require more incident managers, and one risk-averse organization purposely chose higher false positives for greater data visibility.
Lesson 4: Poor identity management hinders good DLP
One of the largest obstacles to a successful DLP deployment is poor identity management, especially in content discovery deployments. If you locate a file with sensitive data in an unapproved location, a poor directory infrastructure may make it nearly impossible to identify the file's owner. Without being able to identify the owner, protecting the file could break a legitimate business process. One health care organization reported that it might take it days to track down a single file's owner. Even though the DLP solution scans their infrastructure relatively quickly, the manual delays of tracking down users and managers (due to a haphazard Active Directory deployment) has dragged out their project by many months.
In another case, we received a report of an organization that almost fired the wrong employee when the IP address was tied back to the wrong user, due to a contractor improperly connecting their system.
Lesson 5: False positives are a manageable concern
The single most common worry over deploying DLP is the time required to manage false positives. The assumption is that policies based on keywords or generic 16-digit (credit card) numbers will constantly trigger false positives. But in real world deployments, users find false positives to be minimal as long as the right content analysis technique is used and policies are properly tuned.
For structured data, such as credit card and account numbers, most DLP tools have a range of advanced techniques to limit false positives. You can choose to only protect numbers from an internal database (instead of a generic expression), or set thresholds that alert only for multiple violations in a single document. For unstructured data, such as documents, DLP solutions use techniques such as partial document matching to alert only if a portion of a protected document (usually a few sentences) is found, as opposed to keywords.
One large financial institution reported much fewer false positives once they built DLP policies on their live databases. This same institution also highlighted the importance of real false positives vs. "false" false positives. "False" false positive happen when you alert on a real credit card number, but it isn't one you care about (such as an employee on Amazon). A mid-sized credit union reported that while they see some false positives, the vast majority are ones they want to see and evaluate.
Lesson 6: Progressive deployments are most effective
Nearly every organization we talked with reported deploying DLP in stages; starting with one component and policy, then slowly expanding. This allowed them to better understand the new technology, tune internal workflows and processes and optimize policies.
Initial deployments tend to start as either network-centric or discovery-centric. With a network-centric deployment the organization starts with basic network monitoring, and then typically expands into email. Some organizations continue to expand into other network blocking, via gateway integration. In a discovery-centric deployment the organization starts with data-at-rest scanning, usually on servers and storage repositories, and then grows into endpoint scanning. This initial phase usually lasts one to two years (defined by budget cycles), then expands into the opposing channel or endpoint enforcement. We didn't find many DLP endpoint-centric initial deployments, perhaps because many organizations start with USB port blocking and encryption on the endpoint before moving into DLP.
In all cases, organizations report finding it better to start with a narrow set of policies and then expanding once incident types and volumes are better understood. On average, DLP managers said it takes about three to six months to tune a new policy, depending on its complexity. Simple policies, such as protecting a single collection of documents, require very little tuning, but more complex policies take time to refine. The general rule is to deploy any policy in monitoring mode and tune it to meet business objectives before moving into active enforcement/blocking. User notification, education, and disciplinary action during the monitoring phase materially lower violation counts and prepare the organization for potential business process impact.
Lesson 7: Endpoint DLP is still more limited than network or
In network and discovery deployments, the DLP solution runs on high-powered, dedicated hardware. On the endpoint, the DLP agent must share resources with all the other cruft we load onto enterprise desktops and laptops. Thus, endpoint tools are more limited as to the type and number of policies they can run. Woe be on the DLP manager that attempts to load a policy containing the hashes for the entire customer database onto the sales team's laptop.
Not that endpoint DLP is unmanageable or too limited to be useful. Some tools communicate back to the central DLP server for content analysis when the system is on the same network. Since, in that situation, all email and network traffic are already monitored by the central server, only limited kinds of activities (like writes to USB drives) need to be offloaded. This also works well for endpoint discovery, where the local agent coordinates with the server for minimal impact. A few tools even support adaptive policies--where a smaller policy, such as a less-accurate regular expression, is only used when the endpoint can't see the DLP server. Yes, there will be more false positives, but remote activity can still be monitored and enforced.
Most DLP suite vendors started focusing more on the endpoint in 2008, but overall we see far less consistency across the different products than we do for network and discovery.
Lesson 8: Content discovery is hot
A security manager for a group of casinos reported they decided to start with content discovery over network monitoring. "We want a full solution, but the largest benefit will be in discovery. We just want to know where everything is. It's breach avoidance."
When interviewing independent references, fully half of them stated they started with, or are considering, data at rest scanning before network monitoring. Of this group, reducing PCI compliance costs and risk is the single biggest driver. Using DLP content discovery, they can inventory their environment for sensitive data to protect, reduce audit costs, and cut down on unneeded data exposure. Reduced audit costs alone, over time, can sometimes offset the total cost of the DLP tool.
Across all of our interviews two key trends emerged. DLP is clearly a viable option for real-world data protection, and many see it forming the core of their data protection initiatives. It can identify where your data is located, where it's moving, and how it's being used. On the other hand, few organizations are deploying DLP to its full capabilities, and products aren't the magical panacea often presented in sales meetings.
About the author:
Rich Mogull is the founder of consultancy Securosis. Send comments on this article to email@example.com.
This was first published in April 2009