After it first blipped on the cybersecurity radar in 2004, the KARMA attack has kept open network users on their toes. A variant of the evil twin attack, the KARMA attack launches a radio-based ambuscade to steal user data by exploiting the behaviour of wireless devices whose Wi-Fi protocols lack access point authentication. A KARMA attack is an improvement over an evil twin attack in that the former uses PNL to ascertain the SSID instead of guessing it.
What Is a KARMA Attack?
During a KARMA attack, the hackers trap an unsuspecting user in a fake Wi-Fi network controlled by them. This network puts your data at risk by directly connecting you to the hacker. In 2004, Dino Dai Zovi and Shaun Macaulay published a paper detailing how rogue access points could lure unwitting users into connecting to malicious networks. They observed hackers could lure users into connecting to a rogue network by allowing dubious access points to accept all probe requests. Especially at risk were devices that connected to wireless networks without authentication. They termed this KARMA attack.
How Does a KARMA Attack Work?
A KARMA attack is a man-in-the-middle attack that affects radio devices like laptops, phones, tablets, and Wi-Fi. Suppose you had previously connected to the Wi-Fi at a shop and your device memorized the network. So, the next time you turn on a wireless network, your device initiates an automatic probe request to connect. Now, if hackers are snooping around a network, their device receives the probe request. They stop the probe request packet, mimic the exact AP your device had earlier accessed, and send you a probe response. Your device then tries to connect to the network via the fraudulent AP. Once the KARMA device accepts the probe request for a particular SSID, it creates a fake Wi-Fi network for the target to connect.
Is KARMA Attack Still Relevant?
While improvements in cybersecurity have blunted KARMA attacks, they still pose grave challenges to unsuspecting users. It is device and OS agnostic, meaning any OS can become the target on an open network. Supposing a device comes in the radio range of a KARMA attack, it may join the KARMA network without authentication, putting your data at high risk. Here, the services of a cybersecurity firm like Packetlabs can come in handy. Packetlabs not only bolsters the security of your organizations' devices but also maintains proper cyber etiquette to ward off any threat.
Tips to Save Your Device from Radio Attacks like KARMA
Turn your firewall on as a safeguard against potential attacks. To enable it, go to the Control Panel, select System Security, and click on Windows Firewall.
Use a Virtual Private Network
Public networks are a hotbed of hackers and malicious attackers. Preventing your browser from retrieving the browsing history and storing previous data are some of the easiest ways to avoid radio-based attacks like KARMA.
Keep a Close Eye on Public Wi-Fi
It would help if you refrained from connecting to public Wi-Fi lacking trustworthy security credentials. Ensure your device has an antivirus as a preliminary safeguard against intrusions.
Restrict Saved Networks to a Specific BSSID
You can do this by using platforms like Linux NetworkManager, which ensures saved networks associate only with a specific BSSID or MAC address. This way, your device will never get auto-connected to a network without your authorization.
Use Strong Passphrases for Any Encryption-protected Network
Use strong passphrases to keep your network protected. This is useful when your NetworkManager has stored a network that is vulnerable to a KARMA attack. If it has a weak password, the hacker can quickly break in.
Disable Wi-Fi when not in use
Turn off your Wi-Fi when not in use to ensure the safety of your system.
The KARMA attack is a potent radio-based attack that is a threat even today. As hackers figure out newer ways to hack into systems to steal confidential information, you, too, must prepare for all events. To ensure the safety of your devices and data, get in touch with Packetlabs. We use industry-leading methodologies to identify hard-to-find vulnerabilities and weaknesses, which conventional testing may often miss.