Beyond Attachments: How Email Becomes Your Biggest Data Exfiltration Vector

The Sophisticated Bypass of Modern Email Gateways

Your Microsoft 365 and Google Workspace security dashboards show green across all metrics. You've implemented data loss prevention policies, enabled advanced threat protection, and your team regularly audits security logs. Yet sensitive data continues to leave your organization through email channels.

Why? Because attackers and even non-malicious insiders aren't using the obvious exfiltration techniques your tools were built to detect.

The Evolving Attack Surface of Exchange Online and Gmail

Today's email exfiltration bypasses the attachment-focused controls of standard security configurations. Here's what we're seeing across enterprises in 2025:

1. Exfiltration of data via text within email body
   Sensitive data embedded directly within the email body isn't flagged by attachment scanners or legacy DLP. We've observed secrets and credentials, protected health information (PHI), personally identifiable information (PII), payment card information (PCI) and proprietary information copied directly into email bodies, completely bypassing attachment controls in both Exchange Online and Gmail.
   ‍
2. Exfiltration of confidential information via screenshots
   Employee screenshots of sensitive information converted to images sidestep text-based scanning. These images contain readable data but remain invisible to most DLP systems, which either miss the image entirely or lack the processing capability to extract and analyze the text they contain.
   ‍
3. Download-upload chains breaking visibility
   The moment an attachment is downloaded from Exchange Online or Gmail, it escapes your visibility. We're observing increasing instances where legitimate downloads are subsequently emailed to personal accounts or uploaded to risky domains and AI applications. This creates a perfect exfiltration pathway that evades most detection systems, as the connection between the original download and subsequent upload is rarely tracked.
   ‍
4. Insufficient encryption in external collaboration
   Despite clear policies requiring encryption for sensitive or confidential external sharing, employees frequently default to convenience over security. When collaborating with partners and vendors, sensitive data is routinely sent without proper encryption controls. Our analysis reveals that when employees are instructed to use secure sharing methods but encounter friction, almost all users revert to unprotected email rather than seeking IT or security team assistance.
   ‍
5. Multi-step exfiltration processes
   Sophisticated actors employ a sequence of seemingly innocuous emails that, when combined, constitute significant data disclosure. Each individual message passes security thresholds, but the collective content represents a major data breach.
   ‍
6. Link-based sharing abuse
   Rather than attaching files, users share links to documents stored in OneDrive, SharePoint, or Google Drive. Even with sharing restrictions, these links create persistent access paths that standard email security tools fail to adequately monitor or control.

Real-World Case Study: Nova Credit

Nova Credit operates in the fintech space, handling sensitive information as part of its core business. As a growing company, ensuring data security across their collaboration tools and endpoints became increasingly critical. Their previous email DLP solution suffered from poor accuracy:

“The other DLP solution we were using for email wasn't that great,” Adam Davis says. “It was like a blunt hammer. It wouldn't catch the things that Nightfall did catch. It was so inaccurate it became an annoyance, and users stopped paying attention to it.”

Implementing Nightfall AI allowed Nova Credit to replace ineffective, disruptive controls with a sophisticated, accurate, and efficient DLP program with tangible results:

• 80% of issues are automatically remediated by Nightfall
• 27+ hours saved monthly on manual investigation
• 36% improvement in data hygiene with Nightfall

The Missing Layer: Next-Generation Email Protection

The critical gap in today's email security cannot be addressed by incremental improvements to existing tools. What's required is a fundamentally different approach that combines advanced detection capabilities with comprehensive visibility:

1. Intent-based analysis: Legacy DLP and email gateways evaluate content without understanding context. Email DLP must distinguish between an employee legitimately sharing quarterly results with the board versus sending the same information to a competitor—even when the content itself is identical. This requires AI models trained to understand business context, recipient domains, and normal communication patterns.
   
   
2. Data lineage: Effective email DLP requires full contextual understanding of data movement across your entire environment. This means tracing sensitive information from its origin (document creation) through any transformations (download, edit, share) to its ultimate destination (email attachment to personal domain etc). Without this visibility of data movement connecting SaaS & AI apps, endpoints, browsers, and email systems, exfiltration attempts remain hidden in the noise.
   
   
3. AI and computer vision models for content classification: Modern exfiltration techniques deliberately bypass text-based analysis. Advanced protection requires AI-powered computer vision models that can identify PII, PCI, PHI, API keys, and intellectual property embedded in screenshots, images, and complex document formats—all while understanding the full communicative context of the email.
   
   
4. Comprehensive file support: Standard email security scans a limited range of file types, creating blindspots exploited by sophisticated actors. Today's environment demands support for OCR (to extract text from images), complex archive formats, and 150+ file types that might contain sensitive information—without introducing delays that contribute to friction.
   
   
5. Holistic coverage: Email exfiltration is just one vector in a broader data loss prevention program. Leading organizations are implementing solutions that unify Data Detection & Response capabilities with Data Exfiltration Prevention across all channels—Email, SaaS & AI apps, endpoints and browsers.
   
   
6. Enterprise-grade performance: Protection cannot come at the cost of business velocity. Modern solutions must scale to process hundreds of thousands of emails at millisecond latency with zero perceptible impact on employee productivity—ensuring security becomes an enabler rather than an obstacle.
   
   
7. Contextual policy enforcement: Blanket policies create either excessive false positives or dangerous security gaps. Next-generation email DLP enables AI-powered policies that adjust based on specific users, groups, recipient domains, and communication types—allowing precise control through actions ranging from blocking and quarantine to automated encryption and real-time user coaching.
   
   
8. Automation: Email DLP doesn't exist in isolation. Today's environments demand solutions that integrate seamlessly with your broader security ecosystem through APIs, alert platforms (Slack/Teams/Jira/Webhooks), and automated workflows—transforming siloed email coverage to an integral part of your DLP program.
   
   

Questions Every CISO Should Ask About Email DLP

To evaluate your current email DLP capabilities, challenge your security team with these critical questions:

On visibility and data lineage:

• Do you have complete visibility into the journey of sensitive data from creation to upload of sensitive data?
• Can you trace when a document was downloaded from cloud storage and subsequently emailed externally?
• Can your system differentiate between legitimate sending of sensitive data to an external domain versus the same data for malicious purposes?

On detection capabilities:

• Can your system identify sensitive information embedded in screenshots and images?
• Does your protection extend to complex file types including archives, design files, and specialized formats?
• Can your system do that consistently across all content types at 90% or higher precision?

On operational impact:

• What performance impact does your email DLP create for end users?
• Can your solution scale to handle peak email volumes without introducing latency?
• How often do legitimate business communications get incorrectly flagged, requiring security team intervention?

On response capabilities:

• Can your system automatically apply the appropriate level of remediation to block, quarantine, encrypt or more based on content sensitivity and context?
• Are users guided with clear explanations when their actions are risky?
• How quickly can your team investigate and remediate potential email exfiltration incidents?

On integration:

• Does your email security solution integrate with your broader security ecosystem?
• Can alerts and incidents be automatically routed to the appropriate response channels?

The Path Forward: Moving Beyond Traditional Controls

Addressing modern email DLP requires a purpose-built approach that augments existing  Microsoft and Google native security capabilities. This approach must:

• Leverage AI to understand the context and intent of communications
• Provide complete visibility into data movement across all channels
• Detect sensitive content regardless of content type
• Scale to enterprise requirements without impacting productivity
• Enable flexible, risk-appropriate responses based on real-time analysis
• Integrate seamlessly with your broader security infrastructure

Your existing investment in Microsoft 365 and Google Workspace security provides an essential foundation. But in today's evolving landscape, that foundation requires an intelligent overlay specifically designed to address sophisticated email exfiltration techniques that native controls simply cannot detect.

Nightfall AI provides advanced protection against sensitive data exposure and data exfiltration prevention for Microsoft 365 and Google Workspace environments. Contact us to schedule a demo.