Lately, a handful of friends and colleagues told me they received an email that claiming that a malicious hacker had installed malware on their computer through a porn site. The email showed one of the recipient’s passwords and explained that the hacker has access to the recipient’s webcam and has a log of all of their keystrokes. Then the hacker gives the recipient two choices:
Ignore the email and a video of the recipient, visiting the porn site will be sent to all of the recipient’s contacts.
Or, pay a ransom in bitcoin, and the hacker will delete the video.
This email scam that has been a popular phishing attack in 2018. As cybersecurity reporter, Brian Krebs, blogged about back in July, “Here’s a clever new twist on an old email scam that could serve to make the con far more believable.”
If you happen to receive one of these emails…
Phishing attacks have long been an effective way for attackers to trick people into divulging sensitive information or infecting a system with malware. Malware can give an attacker remote access to protected systems and networks, encrypt a user’s data and charge a ransom to decrypt the data, or use that system as part of an attack against other systems.
In March of 2017, Google stated that its machine learning models now can detect and stop spam and phishing with 99.9% accuracy. However, this is a cat and mouse game that has been played for years by the spammers/phishers on one side and the spam filter developers on the other side. Once the defenses get better against the latest spam attack methods, the spammers change their tactics to bypass the filters.
Below is an example of a fairly obvious spam email
Phishing is the use of social engineering to obtain personal information for the purposes of identity theft. Phishing typically comes in the form of an email, disguised to look as if it was sent by a trusted source, and requesting personal information or authentication credentials.
As the tools to detect phishing become more effective, the phishing attacks themselves are becoming increasingly advanced and more difficult to identify.
This paper will show how a recent phishing attack from October 31, 2012, is representative of the type of attack that is not detected by spam filters and is likely to trick many recipients.