Credential phishing attack with Figma abuse and vendor compromise

Living Off Trusted Service (LOTS) attacks are spreading across SaaS offerings, now leveraging design tools like Figma and Canva. In a recent attack, a bad actor used a linked Figma file to deliver a credential phishing payload. Using design tools like Figma in LOTS attacks is especially effective because they are commonly used in business, are rarely blocked, look like regular work, and bypass link scanning because the payload is multistage.

The attack starts with the target receiving a message from a compromised vendor email account. The target’s email address is BCC’d and the sender’s address is also the main recipient, indicating this has likely been sent to multiple targets at once. The message lets the target know that there is a link to a request for quote (RFQ) on OneDrive within the linked Figma file.

If the target clicks the link, they’re taken to a Figma file with a Click Here To View | Download Documents link that is supposed to take them to the RFQ on OneDrive that’s referenced in the email.

Clicking that link takes the target to a fake Microsoft login screen (hosted at csoaitv[.]org) that harvests credentials.

Detection signals

Sublime's AI-powered detection engine prevented this attack. Some of the top signals for this attack were:

  • Sender as recipient: The email shows the sender’s address as the recipient, a classic self-sender pattern often used in phishing attacks.
  • Reference to multiple sharing platforms: The confusion created by referencing multiple file sharing platforms (DropSend, OneDrive, Figma) is a deliberate social engineering tactic.
  • Free file host: Figma offers a free plan that could be used to deliver malicious payloads.
  • Suspicious subject: The urgency in the subject line combined with grammatical errors are typical phishing indicators.

ASA, Sublime’s Autonomous Security Analyst, flagged this email as malicious. Here is ASA’s analysis summary:

Stay secure against LOTS attacks

LOTS attacks are gaining popularity because they let bad actors hide behind friendly domains. That’s why the most effective email security platforms are adaptive, using AI and machine learning to shine a spotlight on seemingly minor discrepancies.

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About the Author

About the Authors

Author headshot

Sam Scholten

Detection

Sam is the Head of Detection at Sublime. Prior to Sublime, he was a Staff Email Security Researcher at Proofpoint where he developed a business email compromise (BEC) taxonomy and formulated key detection methodologies and rules.

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