Hackers excel at creating fake emails that it's nearly impossible for end-users to tell the difference between a real email and a fraudulent email these days.
INKY's clear differentiator is that we are able to look at an email much like a human does. The criminal wants you to believe that the email is from a brand or person you trust, so INKY has built models that essentially mimic what a human sees when they receive an email. We can tell whom an email is supposed to be from and confirm it’s the actual sender. We use brand forgery detection, user profiling, and social network mapping techniques to monitor emails.
As an email passes through INKY Phish Fence the message is rendered in a headless chrome browser and meticulously analyzed. Header and Source IP Reputations are checked, WHOIS / Valid Sender Domains are analyzed, DKIM, DMARC, and SPF records are analyzed
See INKY in action.Where INKY is more effective than other solutions, is in the next-generation computer vision models that are built into the technology. Not only does she look at all the standard stuff email security solutions are supposed to look at, she also:
Checks the logos in the body of messages and compares them to the company’s actual logo on their website.
Looks at the images to ensure the image is the right color, font, shape, and size.
Evaluates the weight of the image whether the links connect to an authenticated website associated with the brand.
Traditional Security Email Gateways (SEGs) can’t compare to INKY’s level of phish detection because they rely upon old-school Bayesian filtering rules and out of date messaging blacklists/RBLs. As a result, INKY catches all phishing emails after they have made it through other email security programs.
Download this report that highlights how many phishing emails are slipping through the legacy SEGs:
Download the report.Detect brand-indicative and scam-indicative images using computer vision models.
Find brand-indicative and scam-indicative text using approximate matching.
Determine the apparent brand using color palette, layout features, prominent text, and more.
Pinpoint zero-font and other forms or hidden text.
Identify Unicode homographs, typos, and other text cloaking.