How the model works and how to use it effectively

How to Implement the Zero Trust Model

10/07/2024

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The Zero Trust Maturity Model operates on a simple principle: never trust, always verify. Instead of assuming that everything inside of the network is safe and trustworthy, the Zero Trust Model treats every user, device, and connection as potentially untrustworthy, even if they are already inside the network.

When used properly, it works to prevent unauthorized users and data breaches, but many organizations are not using this model appropriately.

How does the Zero Trust Model work?

Here’s how it works: In order for any system or process to interact with another or be granted access to protected data, it is required that this system or process demonstrate proof of authentication to validate who they say they are, as well as the scope of operations they are authorized to perform. This process is called making a “trust decision.”

To make a good trust decision, you should use information that is the most accurate and authentic combined with the conditions and context of operations. This includes things like credentials, processes, network connections, and whether the behaviors observed are typical or unusual.

Why Organizations Using the Model Are Still Vulnerable

Many organizations rely too much on one piece of information: the client’s IP address, which is like the digital “home address” of a device on the internet. A common mistake is to use an IP address to establish a device’s geographic location or an actor’s history and reputation.

The problem is that depending heavily on IP addresses or related information can lead to mistakes. Here’s why:

  • IP addresses can be spoofed: Hackers can make it look like they’re coming from a trusted IP address, even when they’re not.
  • IP addresses can change: A legitimate user might get assigned a different IP address unexpectedly, causing the system to treat them as suspicious.
  • Geolocation isn’t always accurate: It might place a user in the wrong location, leading to incorrect assumptions about their trustworthiness.

Similarly, relying too much on reputation services or external intelligence sources, which provide information about the trustworthiness of an IP address or domain, can be risky. These sources aren’t always up-to-date or accurate, and they can sometimes block legitimate users or allow malicious ones.

How to use the Zero Trust Model effectively

To use the Zero Trust Model effectively, you have to focus on what is actually happening in the network, rather than on things that can easily be faked or manipulated, like IP addresses, reputation scores, or location data. Instead, high fidelity detections rely on patterns and data points across time intervals, combined with a deep understanding of how bad actors operate, and the techniques and strategies they use. This is the purpose of the Zero Trust Model—to not trust anything that is “claimed” and only trust observed actions and conditions.

For example, using a Zero Trust Model in a network environment would not place heavy importance on collecting and analyzing details you might find in a sign-in log. Things like account names, infrastructure names, and location derivatives do not meet the level of trust required, can be manipulated by attackers, and therefore, are not the most reliable indicators for making security decisions.

Instead, the model should focus on what the user or system is actually doing, by looking conditions, operational context, and observed interactions over time. This could be assessing what files are being processed, how the different systems are communicating, the assigned permissions and privileges, and then analyzing whether these actions are typical or stand out as unusual.

When using a Zero Trust Model in your network, the resounding message is that actions speak louder than data points. If someone is behaving in a suspicious way, that’s a red flag, no matter what their IP address is.

Contact us for more information on how to effectively implement a Zero Trust Model in your organization.