Fog Reveal: How Our Apps Turn Into a Surveillance Network
How everyday apps can add up to a commercial surveillance network — and why "anonymized" location data is often less anonymous than it first appears.
We take our smartphones practically everywhere: to work, to the doctor, to friends, to protests, on vacation. Often we don't really know how many digital traces we leave along the way. Numerous apps and digital services can record where a device is, when it's there, and which place it visits next — individual location points can add up to a movement profile, and a movement profile can add up to a behavioral profile.
This is exactly where the debate around Fog Reveal begins: an analytics tool developed by Fog Data Science that makes commercially available location data from mobile devices usable for investigative and analytical purposes. The controversy lies not only in the software itself, but above all in where this data actually comes from: entirely ordinary apps on entirely ordinary smartphones.
This article explains what Fog Reveal is, how individual location points add up to a movement profile, why that can become especially sensitive around certain places and personal relationships — and what you can actually do to give away less location data.
What is Fog Reveal?
A smartphone goes almost everywhere with most people — to work, home, the doctor, to friends, to protests, on vacation. Out of many individual location points, something more meaningful than a single place can emerge: a movement profile. And a movement profile can, in turn, give rise to a behavioral profile. This is exactly where the debate around Fog Reveal begins.
Fog Reveal is an analytics platform developed by Fog Data Science that makes commercially available location data from mobile devices usable for investigative and analytical purposes. Fog itself describes Reveal as a tool that lets qualified organizations examine device location data, analyze historical movement, detect recurring places of stay, and establish geographic relationships between devices.
One distinction matters here: Fog Reveal is not the same as a classic cell-site simulator (colloquially often called a "Stingray"), which captures devices in its vicinity via radio technology. Fog Reveal works fundamentally differently — it's built on already-existing commercial data. So the key question isn't "does Fog tap my smartphone directly?" but rather: who collected my location data in the first place, and who did they pass it on to?
From location points to a movement profile ("pattern of life")
A single location point seems harmless. One coordinate alone says little. But a sequence like "Monday 8:03am → place A, 8:47am → place B, 5:12pm → place C, 10:41pm → place D" already tells a story — and if that pattern repeats over weeks or months, a so-called pattern of life emerges: a recurring movement and behavioral pattern.
A sufficiently extensive profile may reveal where someone lives and works, when they sleep, which routes they regularly travel, which people are frequently at the same place at the same time, and which places they visit repeatedly. In its legal analysis, the University of Richmond explicitly names sensitive locations such as protests, houses of worship, and healthcare facilities as examples of what such data can reveal. The software doesn't need to know that someone is a member of a particular organization — it may be enough that a device regularly shows up at a corresponding place.
Sensitive places, relationships, and the "chilling effect"
Things get especially sensitive when location data can reveal visits to places such as healthcare facilities, counseling centers, religious institutions, or protests. A single visit says little; repeated visits, however, can enable inferences nobody consciously disclosed. Relationships between devices can also become visible: if two devices regularly turn up together at the same places, that can — with appropriate caution about interpretation — suggest a statistically notable connection. That's particularly sensitive for relationships meant to stay confidential, such as between journalists and their sources.
This possibility can produce a so-called chilling effect: people change their behavior because they fear being observed or logged — for example by avoiding a protest or skipping a counseling appointment. The EFF and the University of Richmond both point exactly to this problem. Location privacy is therefore not just a matter of private secrets, but also a matter of press freedom, freedom of assembly, and freedom of movement.
Why a VPN doesn't protect you
An obvious thought is: "I delete my advertising ID or use a VPN, so I'm invisible." That falls short. Beyond the advertising identifier, other data sources exist — IP address, account IDs, cookies, device information, and above all the position data an app itself collects through its own location permission.
A VPN can change the IP address visible to certain internet services. But it doesn't stop an app you've granted location access from continuing to collect its GPS or fused location data through its own permissions. GPS simply isn't the same as IP geolocation: a VPN changes the visible IP address, not the device's actual GPS coordinates. The provider Private Internet Access makes exactly this point explicitly in its own write-up on Fog Reveal — a VPN alone does not protect against an analytics platform built on advertising IDs and app-collected location data.
Practical protection: what you can actually do
Full invisibility is unrealistic — but noticeably reducing how much data you give away is an achievable goal. A few concrete levers:
- Delete apps you no longer use — an uninstalled app can't generate any new data.
- Review location permissions per app and set them to "never" or "only while using" instead of "always."
- Turn off background location when an app doesn't need it for its actual function.
- Limit or reset your Advertising ID / IDFA (settings differ by iOS/Android version).
- Use your OS's app-tracking controls deliberately instead of tapping "Allow" by default.
- For especially sensitive apps, check the privacy policy for "location," "advertising partners," and "data sharing."
- Do a regular check — say, once a quarter — of apps and permissions, instead of setting them once and forgetting them.
- Treat a VPN and tracker blockers as a complement against IP and web tracking, not a substitute for controlling app permissions.
Conclusion: the surveillance economy starts with the app
Fog Reveal as a single product matters less than what it represents: an example of what becomes possible when an already-existing commercial data economy is made accessible for investigative or other purposes. A government doesn't need to build such a surveillance infrastructure itself — it can be enough to buy access to data that apps, SDKs, ad networks, and data brokers have already generated.
That leads to an uncomfortable but important conclusion: data minimization protects not just against how a dataset is used today, but against future uses too — nobody today can be certain which agencies or companies will gain access to a particular dataset years from now, or which data sources will be combinable by then. You don't need to be under active surveillance to lose your privacy — it can be enough for sufficient location data about you to accumulate over the years. That's why privacy protection doesn't start with an analytics platform like Fog Reveal — it starts with the question of what permission you grant to the next app in the first place.
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To see how digital surveillance can also be avoided in private communication, read our article Chat Control & End-to-End Encryption.