{"id":35511,"date":"2020-06-13T17:45:06","date_gmt":"2020-06-13T17:45:06","guid":{"rendered":"http:\/\/396ada89-833d-44fd-83d6-46e4a665816b"},"modified":"2020-06-13T17:45:06","modified_gmt":"2020-06-13T17:45:06","slug":"lamphone-attack-lets-threat-actors-recover-conversations-from-your-light-bulb","status":"publish","type":"post","link":"https:\/\/www.threatshub.org\/blog\/lamphone-attack-lets-threat-actors-recover-conversations-from-your-light-bulb\/","title":{"rendered":"Lamphone attack lets threat actors recover conversations from your light bulb"},"content":{"rendered":"

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In a research paper published this week, academics detailed a novel method of recovering conversations and audio recordings by observing vibrations in a light bulb.<\/p>\n

The technique, which they named Lamphone, revolves around the principle that objects vibrate when soundwave hits their surface.<\/p>\n

When this happens in a light bulb, academics say the vibrations also create small flickers in light emissions. They say that by using powerful sensors, they can record the light variations and reverse-engineer the sound waves that hit the light bulb’s surface.<\/p>\n

But like any novel surveillance technique, Lamphone has its advantages and limitations.<\/p>\n

The most obvious is that attackers need a direct line of sight to the light bulb in a room or public space. Light bulbs protected by decorative covers or other constructs are safe from this attack, and so are conversations that take place in rooms without windows.<\/p>\n

However, once a line of sight to a light bulb is available, academics say an attacker can use tools like a telescope and an electro-optical sensor to record light variations in the light bulb from large distances and don’t necessarily have to be close to their targets.<\/p>\n

In experiments they carried out for their paper, they said they successfully recovered sound and conversations from 25 meters (82 feet) away.<\/p>\n

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“This range can be amplified with proper equipment (bigger telescope, 24\/32 bit ADC, etc.),” the research team said.<\/p>\n

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In their experiment, the research team said it was successful in recovering both human speech and room effects — such as music played in the background (see demo below for an example).<\/p>\n

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