When GPS Assumptions Fail: Lessons for Threat Modeling
Jan 22, 2026Introduction: A Threat Advisory That Demands More Than Awareness
A recent advisory from threat modeling expert firm Shostack + Associates on GPS spoofing and jamming has prompted many organizations to revisit their threat models. The guidance is simple. If your systems rely on GPS, it is time to reassess what that dependency means today.
GPS spoofing itself is not new, but its likelihood and impact have changed. Attacks are cheaper, more accessible, and no longer limited to narrow or specialized environments.
Part of the challenge is how deeply GPS is embedded across modern systems, often in non-obvious ways. Beyond navigation, GPS supports timing, coordination, and automation in everyday technologies such as phones, cars, wearables, and even earbuds.
This is what makes the advisory important. It is less about GPS as a technology and more about assumptions baked into system designs. Many threat models were built under the assumption that GPS could be trusted by default. The advisory makes clear that this trust can no longer be taken for granted and should be explicitly evaluated.
This post examines what the GPS spoofing advisory reveals about keeping threat models relevant. The focus is not on modeling every possible outcome, but on understanding which assumptions matter and how to update them as conditions change.
GPS Spoofing Isn’t New. The Assumptions Around It Are
GPS interference has been understood for years, particularly in military or highly controlled environments. In those contexts, spoofing and jamming were expected risks, and systems were often designed with that reality in mind.
What has changed is where and how GPS is used. As GPS became cheaper, more reliable, and widely available, it moved beyond specialized use cases and into everyday systems. Over time, it became common to treat GPS signals as accurate and trustworthy by default.
That assumption is now under pressure. The cost and complexity of GPS spoofing have dropped, while the potential impact has increased. Attacks that were once considered unlikely are now more feasible across civilian and commercial environments.
At the same time, GPS is no longer limited to navigation. Many systems depend on it for timing, coordination, and automated decision-making. When those dependencies expand, the consequences of inaccurate or manipulated signals increase as well.
The advisory highlights this shift. The threat itself is familiar, but the assumptions surrounding it are no longer aligned with how systems are built and used today. That gap between design assumptions and current reality is where risk emerges.
What the Advisory Requires: Explicit Identification
Many systems were designed assuming GPS signals could be trusted by default. The advisory makes clear that this trust should now be re-evaluated wherever GPS is used.
The guidance is not to redesign systems or attempt to model every possible GPS failure. That approach would quickly make threat models too large and too difficult to maintain.
Instead, the practical step is to revisit existing threat models and identify where GPS is actually used. In many cases, this dependency is implicit or undocumented, which makes it easy to overlook when conditions change.
Making GPS usage explicit enables teams to update threat models without expanding their scope. Capturing this information as attributes and, where appropriate, associating it with product identifiers such as CPE IDs helps teams prepare for future scenarios even if no mitigations are added immediately.
This approach keeps threat models focused and usable while ensuring that key assumptions can be revisited as the threat landscape evolves.
Why GPS Spoofing Is a Threat Modeling Problem
The GPS spoofing advisory applies broadly across industries and technologies. It is not tied to a specific vendor, product, or vulnerability that can be addressed with a patch.
There is no single CVE that resolves GPS spoofing risk. The issue is not a software defect, but a design-time dependency on a signal that may be inaccurate or manipulated.
GPS spoofing affects core security properties such as trust, integrity, and availability. These concerns are architectural in nature and influence how systems behave long before code is deployed.
Because of this, GPS spoofing cannot be fully addressed through scanning, monitoring, or detection alone. Those controls operate after design decisions have already been made.
Threat modeling is the process of defining and examining dependencies and trust assumptions. That makes it the appropriate place to assess GPS-related risks and understand their potential impact across the system.
Speed Comes From Structure, Not Scramble
When advisories like this are published, some teams can quickly determine which systems are affected. Others are forced to manually rediscover dependencies by opening models one by one and piecing information together.
The difference is structure. Teams that consistently capture and reuse key attributes can identify GPS-dependent components much faster than teams relying on diagrams or informal documentation.
Organized threat models enable teams to search across systems from a single location. Instead of reviewing every model individually, teams can focus on what matters.
This kind of structure turns advisories into focused reviews rather than fire drills. Speed comes from preparation built into the modeling process, not from reacting under pressure.
GPS Spoofing Is a Pattern, Not a One-Off
GPS spoofing is one example of a broader pattern. Many systems rely on external signals that are assumed to be accurate and available by default.
When those assumptions change, risk emerges across the design. GPS is the signal in focus today, but the same pattern applies to other dependencies that systems implicitly trust.
Similar issues appear with time synchronization services, cloud metadata, and AI inputs. In each case, the signal itself may be familiar, but the way it is relied upon has evolved.
As systems become more interconnected and automated, these dependencies play a larger role in decision-making. When they fail or are manipulated, the impact extends beyond a single component.
The lesson is not about GPS alone. Threat models need to account for how assumptions about external inputs can change over time, not just for individual attack techniques that are known today.
Where Proactive Modeling Begins
Responding to an advisory like this does not require modeling every possible GPS failure. It also does not mean expanding threat models beyond what teams can realistically maintain.
At the same time, teams do not want to rediscover the same dependencies every time assumptions change. Capturing a small amount of structured information up front helps avoid that cycle.
Attributes are one way to do this. Recording GPS usage makes that dependency visible and easier to revisit when conditions change.
In some cases, teams may also associate product identifiers such as CPE IDs. These identifiers are not required to respond to this advisory, but they can help when risks evolve, priorities change, or multiple issues intersect.
The goal is preparation, not over-modeling. By capturing the right information early, threat models stay focused while remaining adaptable to future scenarios.
What to Do Now
In response to the GPS spoofing advisory, IriusRisk and ThreatModeler customers can take the following steps:
Quickly identify the impact and capture GPS usage
In IriusRisk:
Identify all models containing GPS components
In IriusRisk, simply run this script to return all impacted threat models/projects containing components representing GPS. It provides information on where the match is found (name only, description only, or name and description) so you can navigate the output more easily. Instructions for installation/usage are included in the project readme.md.
Capture GPS usage
IriusRisk users can use tags in their instance to assign GPS usage or considerations on a component level.
In ThreatModeler:
Identify all models containing GPS components
In ThreatModeler, navigate to the threat framework and search for “GPS” in the component library. This will identify threat models where GPS-related functionality may already be present.
From there, use ThreatModeler’s dynamic search capability to quickly add and address GPS-related attacks within your threat models.
Capture GPS usage as an attribute
As threat models are reviewed or updated, assign GPS reliance as an attribute on relevant components. This makes GPS usage explicit within the model and ensures it can be searched, reviewed, and revisited as assumptions change.
If GPS is introduced as part of a broader system or service, use the CPE dictionary as an attribute to help you navigate and understand known vulnerabilities.
Methodically improve coverage as part of ongoing model maintenance
Review models for missed GPS dependencies
As part of regular threat model updates, review architectures to ensure there are no additional GPS dependencies that were not initially captured. This can be addressed incrementally as systems evolve.
Pro tip: Prepare for future advisories
Where appropriate, associate product identifiers such as CPE IDs with components. While not required for this advisory, doing so can make it easier to identify affected components when new vulnerabilities or advisories emerge.
When Should Threat Models Be Updated?
Threat models should be updated when the assumptions on which they are based change. Advisories like this one are a clear signal that a previously trusted dependency may no longer behave as expected.
GPS spoofing is not unique in this regard. It is simply a visible example of a broader pattern. As systems evolve and threats change, assumptions about trust, availability, and accuracy can become outdated. When that happens, threat models need to be revisited so they continue to reflect reality.
Teams that treat advisories as triggers to review and update threat models are better positioned to respond calmly and effectively. Rather than scrambling after issues emerge, they use these moments to validate assumptions, adjust models where needed, and keep their understanding of risk current.
This is what distinguishes threat modeling as an ongoing practice from a one-time exercise.
Advisories Test the Maturity of Your Threat Modeling Practice
Threat advisories do more than call attention to new risks. They reveal how well an organization’s threat models adapt to changing conditions.
Reading an advisory is easy. Acting on it requires models that clearly capture assumptions and dependencies so they can be revisited without starting from scratch.
GPS spoofing is the trigger in this case, but it is not the lesson. The lesson is whether threat models are treated as static artifacts or as living representations of how systems are designed and trusted.
When advisories like this are published, they provide a natural opportunity to revisit and update threat models. Doing so helps ensure that design-time assumptions remain aligned with the realities of today’s threat landscape.
Learn More
If you’d like to understand how ThreatModeler helps teams revisit assumptions, identify critical dependencies, and keep threat models current as conditions change, visit our contact our team to start a conversation.