6 Common Phishing Detection Evasion Techniques Solved By VISUA

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Cybersecurity platforms are in an arms race with bad actors who will use every trick possible to avoid detection. Here are the six most common detection evasion techniques and how Visual-AI can help to detect the undetectable.

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Fake websites used to last days or hours, but bad actors switched gears to use short-life and single use URLs. After all, you can’t blacklist a website that only lasts minutes or less.

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Bad actors will add noise to the code of an email or website to confuse and overwhelm detection systems. They’ll even take key imagery, split it into many small parts, and reassemble it using CSS or JavaScript.

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Using genuine links and reply-to’s in fake emails or sites are also great for fooling detection systems.

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You can’t detect what you can’t see, so bad actors will convert trigger words, sentences, a form or entire page into graphics to make it invisible to detection systems.

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Bad actors will also use obfuscated JavaScript and web assembly to dynamically generate content and block HTML parsers.

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Another great way to confuse users and detection systems alike is to drive victims to genuine sites, but trigger a fake form to open in a window above the legitimate form.

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Visual-AI provides a new way to detect and block phishing emails and websites.

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Visual-AI sees all content with human eyes, but at machine speed, so it’s fast and bad actors can’t avoid it.

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It delivers super effective phishing detection in three simple steps.

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Step one, render the web page or email, save it as a flattened image and send it to our engine for processing.

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Step two, high risk elements or attributes are identified and flagged.

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Step three, a risk score is calculated and passed with the identified anomalies back to the master fishing detection system for final actions. And all this happens in real time.

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You too could harness the power, speed and accuracy of Visual-AI in your fishing detection platform test it today, and see how Visual-AI could enhance your platform.