Juice jacking

Juice jacking is a form of cyber attack that takes advantage of the near ubiquity of public USB charging points, particularly in airports, coffee shops, and other public locations. It is a type of phishing attack that uses a hidden hardware and/or software device to gain access to a user’s mobile device, often without their knowledge. This malicious activity generally involves installing malware on the device, allowing hackers to steal data, drain the device’s battery, and potentially even gain access to the user’s bank accounts.

The danger of juice jacking is that it is difficult to detect. The malicious device can be hidden in the USB port itself, and can be programmed to mimic an official charging point. Additionally, the malicious device may be connected to internet enabled devices in order to monitor, download, and steal data from the device.

To protect against juice jacking, users should avoid using public USB charging points wherever possible, instead using an officially endorsed wall outlet. Public USB charging points should only be used if users have sufficient antivirus protection installed on their device. If antivirus protection is not possible, users should avoid logging into any sensitive accounts. Additionally, users should always exercise caution when plugging their mobile device into any unknown USB port and should always check for signs of tampering before connecting their device to unfamiliar ports. If there is an alternate form of power available, such as an AC outlet, users should make use of it, especially if accessing sensitive information.

In addition, enterprises should carefully monitor public USB charging devices and should roll out security awareness campaigns to educate employees about potential threats posed by malicious attacks such as juice jacking. Companies should also strive to use secure charging units that require authentication before allowing a user to charge their device, helping to reduce the risk of an unauthorised third-party gaining access to the user’s data.