The attackers carefully crafted the email and attachment to bypass detection and trick victims into interacting with the malicious content.
The attached PDF file is disguised as an official DocuSign document, complete with branding and calls to action. It plays a critical role in luring the victim into clicking the embedded link.
Once the victim interacts with the PDF, the campaign shifts into its second phase: a series of redirections designed to maintain credibility and evade detection.
The PDF link directs victims to a JotForm-hosted page. This page, designed to mimic a DocuSign e-signature request, capitalizes on the trust associated with JotForm's legitimate domain.
From JotForm, victims are led to another link embedded in the fake e-signature page. This obfuscates the true intent of the attack, delaying suspicion.
The final phishing page includes an hCaptcha challenge to create an illusion of authenticity and block automated analysis. Once the hCaptcha is solved, victims are prompted to enter their corporate credentials, enabling the attackers to harvest sensitive information.
Figure: NACE semantic based approach
This email was flagged as malicious by InceptionCyber’s Neural Analysis and Correlation Engine (NACE) semantic and thematic analysis aided to identify the intent of an email. Contextual relationship between the features from email headers, file attachments aided to classify the email as a Phishing attempt.
The analysis of the SMTP features extracted following features from email:
The SPF record may exist but is misconfigured or missing the correct sender IPs or might not be accessible due to DNS resolution problems at the time of sending. Around 10-15% of emails globally fall under the “no SPF” category.
The single-page PDF attachment triggered several critical features for correlation, including:
The comprehensive feature extraction and the contextual relationships between intent, SMTP headers, and file attributes enabled NACE to classify the attachment as phishing without relying on the landing phishing URL. The approach taken by NACE differs from traditional technologies that rely on payload inspection or final landing URL analysis for decision-making
At the time of writing the blog only 3 out of 96 Anti-Virus vendors are classifying this URL as phishing.
Figure: VirusTotal detection for URL
This campaign demonstrates a sophisticated approach by blending social engineering with the abuse of legitimate platforms. Key observations include:
This DocuSign-themed phishing campaign underscores the increasing sophistication of attackers in abusing legitimate services to bypass security measures. By creating a convincing facade, leveraging platforms like JotForm, and employing multi-step redirections, the attackers effectively exploited corporate users' trust.
Traditional technologies like signature-based detection, sandboxing, and machine learning/deep learning rely on examining malicious payloads, which often remain hidden during analysis due to evasion techniques. This allows multi-stage, evasive, AI or threat actor generated malicious attachments and call-to-action URLs to reach endpoints. NACE leverages the semantic and thematic structures embedded in emails, to understand the intent and uses that as feature set, rather than relying solely on the malicious payload, which is the root cause of evasion of the current technologies.