How do attackers use Location Tracking?

How attackers turn location data into a tracking tool

Location tracking becomes useful to attackers when they can convert routine telemetry into a timeline of movement, presence, or routine. That may come from device permissions, account sharing, carrier-related visibility, app telemetry, or cloud accounts that aggregate a user’s activity. The security issue is not just “where is someone now”, but how location data can expose patterns, safe places, travel habits, and likely future availability.

Attackers rarely need perfect precision to get value from this data. Even coarse or intermittent signals can reveal commuting routes, office attendance, travel windows, or when a device is likely unattended. That is enough to support stalking, targeting, social engineering, burglary timing, or the sequencing of a follow-on compromise.

What attackers actually do with the information

Once location is visible, attackers can use it to profile a victim’s routine and separate useful signals from noise. For example, repeated presence at a home address can identify a private residence, while regular weekday absences can reveal when a business site is least occupied. In some cases, location data also helps attackers correlate multiple identities, devices, or accounts belonging to the same person.

Location data is especially valuable when combined with other observations such as calendar events, ride-hailing receipts, check-ins, delivery notifications, or photos with embedded metadata. The practical effect is that attackers can move from simple observation to prediction, which raises the likelihood of successful physical-world harm or digital compromise.

Where location data is obtained through accounts or connected services, the NIST Privacy Framework is a useful lens for understanding how data collection, sharing, and downstream use create privacy risk. If the same tracking path depends on mobile or cloud authentication, defenders should also tighten the access path with NIST Cybersecurity Framework 2.0 and apply strong identity controls such as NIST SP 800-63 Digital Identity Guidelines where accounts expose sensitive telemetry.

How defenders reduce exposure without breaking legitimate use

The first control is to shrink the number of places where location is collected, stored, or shared. That means reviewing app permissions, disabling unnecessary background access, and checking whether family, workplace, or social-sharing features are exposing location more broadly than intended. The second control is to monitor the accounts and services that can read location data, because compromise of a cloud account or shared device can be enough to expose movement patterns even when the handset itself is not lost.

For organisations, location data should be treated as sensitive telemetry, not convenience data. Access should be limited to the smallest set of applications and services that genuinely need it, and audit logs should show who accessed it, when, and from where. If a service can query location continuously without a clear business need, that is usually a design problem, not an acceptable feature.

Defenders who manage mobile or endpoint access at scale should align their controls with NIST SP 800-53 Rev 5 Security and Privacy Controls, especially where access control, auditing, and configuration management govern telemetry exposure. When an environment relies heavily on mobile and app-based permissions, OWASP API Security Top 10 is also relevant because location APIs, if poorly protected, can become a direct data-exposure path.

Risk and Threat Considerations

Location tracking is risky because it links digital access to physical safety. The main concern is not only surveillance, but the attacker’s ability to infer when someone is at home, travelling, alone, or distracted. That can enable stalking, coercion, theft, targeted phishing, or a more precise follow-on intrusion against the victim’s accounts and devices.

Failure mechanism: Excessive location permissions, overshared account settings, or compromised apps and services expose enough movement data to reveal routines and physical presence. Attackers then combine that data with other signals to predict where the victim will be and when.

Impact: The resulting exposure can support physical targeting, account takeover planning, social engineering, or repeated monitoring over time, especially when the same data source is reused across multiple apps or services.

Practitioner Guidance

What to verify: Confirm which apps, accounts, and devices can access live or historical location data, then check whether each access path is still needed. If a service can infer location from multiple sources, review them together rather than treating permissions as isolated settings.

Decision rule: If the data can reveal home, work, travel, or routine patterns, treat it as sensitive even when the location feed is imprecise. If the app does not need continuous access, prefer one-time or while-in-use access over always-on access.

Common mistake: Teams often focus on map visibility and ignore account-level sharing, telemetry aggregation, and metadata leakage. The practical exposure usually comes from the combination of sources, not a single permission screen.

Practitioner takeaway: The goal is to reduce both location precision and location persistence, because attackers get the most value when they can observe patterns over time rather than a single point in time.

Related resources from NHI Mgmt Group

• Why do virtual machines increase fraud risk when attackers use them to hide identity and location?
• How do attackers use match legitimate name or location?
• Why do passwords remain dangerous when attackers use AI to find vulnerabilities?
• How should security teams reduce fraud when attackers use deepfakes and synthetic identities?