Are there apps to check for hidden cameras / audio recorders (surveillance)?

Hello,

in today’s world, unfortunately it has become more common to place hidden cameras, audio recorders or other forms of spying surveillance devices in private locations without consensus and/or knowledge.

As techniques get more mature and affordable for everyone, it becomes hard to detect such attacks on surveillance.

Example locations: hotels, hostels, public toilets
Example person groups: spying voyeurs, neighbors, stalkers

Probably the most prominent tracking device are Apple AirTags. Fortunately, there are existing apps on F-Droid which can be used for detection (like AirGuard).

Hence I would be curious: Do corresponding counter-surveillance apps for F-Droid exist to detect other spying devices than AirTags? Which hardware requirements are needed (electro-magnetic sensors)?

Or can’t mobile devices provide sufficient protection with currently used sensors and an extra device would be needed?

Curious about the answers,
Thanks!

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The going recommendation for a cheap “bug detector” is the CC308. eBay has them for around $15.

The “camera detection” feature it has is quite useless.
The RF detection does work if you tune it right for the environment and take your time.

It also has value add bonus features! Such as a high-tech compass and SOS mode. lol

There are some articles about researcher using the TOF-sensors of smartphones to detect infra-red reflections of a hidden camera lense.

See for example this article:
https://california18.com/these-researchers-have-developed-an-app-to-locate-hidden-cameras-spying-on-you/1722682021/

The software will first help the user to position himself well in relation to the objects to be analyzed, because the LSRR effect is only manifested if we are sufficiently close and if the angle of reflection of the infrared rays does not exceed 20 °.
Then the user will have to slightly shift his device several times in a row, so that the application can take different measures. These are then processed by filters and a convolutional neural network, in order to eliminate false positives.

According to the article the researcher plan to release the source code, but it is unclear for which platform (Android or iOS) they have implemented their app.

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