Email DLP: Extending the AI Gateway's Protection to Enterprise Email

Your DLP pipeline is only as strong as the channels it covers. If the same 3-tier detection engine that catches a credit card number in an AI prompt does not catch it in an outbound email, the protection has a gap — and the gap is exactly where sensitive data will flow.

The Arbitex Gateway now applies its full DLP pipeline to enterprise email. Not a separate email scanner. Not a bolt-on integration. The same regex patterns with checksum validation, the same named entity recognition, and the same AI-powered contextual validator that inspect AI traffic now inspect email body content and attachments — with the same compliance templates, the same policy engine, and the same audit trail.

This post covers how we built it and why it matters for regulated enterprises.

Why Email DLP Belongs in the AI Gateway

Most organizations already have email DLP. It runs inside their email security gateway or their cloud provider’s built-in scanning. The question is whether it runs the same detection engine as their AI DLP — and the answer is almost always no.

That creates a consistency problem. Your AI gateway catches a patient record in a prompt using NER and contextual validation. Your email scanner uses a different engine with different patterns and different thresholds. The same data gets different treatment depending on which channel carries it. When a compliance auditor asks “is sensitive data protected across all outbound channels?”, the honest answer is “it depends on which scanner looked at it.”

A single DLP pipeline applied to every channel eliminates that inconsistency. One set of detection rules. One set of compliance templates. One policy engine. One audit log. The detection accuracy published for AI traffic is the same accuracy applied to email — because it is the same code path.

Architecture: Channel-Agnostic DLP

The email channel connects to the existing DLP pipeline through a Haraka MTA relay that sits in front of the organization’s mail flow. When an email arrives, the relay extracts the message body, walks the MIME tree for attachments, and sends everything to the platform’s internal DLP scan endpoint. The same endpoint that AI gateway traffic hits.

The scan endpoint does not know or care that the content came from email. It receives text, runs it through the 3-tier pipeline, and returns a risk assessment with entity detections and an enforcement action. The relay maps the DLP response to an email disposition: allow, tag with warning headers, quarantine, or reject at the SMTP level.

This channel-agnostic design means that improvements to the DLP pipeline — a new regex pattern, an improved validation model, an updated compliance template — automatically apply to email without any email-specific work.

Production Hardening

A DLP pipeline that scans email in a lab is a proof of concept. A DLP pipeline that scans email in production needs TLS, authentication, sender verification, and persistent state.

TLS and service authentication. The relay supports STARTTLS on port 587 and implicit TLS on port 465. Relay-to-backend communication is authenticated with a shared service secret — the internal DLP endpoint rejects unauthenticated scan requests when the secret is configured.

Sender verification. DKIM, SPF, and DMARC verification run before DLP scanning. The relay checks sender authentication and passes the results through to the scan metadata. A message that fails DMARC can be rejected before DLP even evaluates the content.

Persistent quarantine. Quarantined emails are stored in a database with full metadata — sender, recipients, subject, risk level, detected entities, and attachment findings. Quarantine survives service restarts. Administrators can review, release, or delete quarantined messages through the admin API. Released messages are re-delivered to the downstream mail server with audit headers that record who released the message and when.

Attachment Scanning

Email bodies are text. Attachments are where the sensitive data hides in practice — a spreadsheet of customer records, a PDF with financial projections, a document with patient information.

The email DLP pipeline extracts text from PDF, DOCX, XLSX, and CSV attachments, then runs the extracted content through the same 3-tier DLP pipeline as the message body. Each attachment gets its own scan result with entity detections and a risk level. The overall email disposition is determined by the highest risk across the body and all attachments — if any attachment triggers a quarantine action, the entire email is quarantined.

Encrypted and password-protected attachments are flagged as unscanned rather than silently skipped. Oversized attachments (above a configurable threshold) are logged and skipped. The scan response explicitly reports the status of every attachment: scanned, unscanned (with reason), or skipped.

Compliance Templates Across Channels

The compliance template system — pre-built policy configurations for HIPAA, PCI-DSS, GDPR, and SOX — was designed from the start to work across all channels. When an administrator applies a HIPAA template to an organization, it creates policy rules that fire on AI gateway traffic, email scans, direct API integrations, and sidecar deployments.

This is the key differentiator. A HIPAA template does not just protect email. It protects every channel where PHI might appear, using the same entity detectors, the same confidence thresholds, and the same enforcement actions. The compliance evidence is unified: one audit trail shows every detection across every channel, mapped to the same regulatory framework.

For organizations subject to multiple frameworks, templates are composable. An organization running both HIPAA and PCI-DSS activates both templates, and every scan — regardless of channel — evaluates against both frameworks in a single pass.

Multi-Tenant Policy and Controls

Enterprise deployments serve multiple organizations with different compliance requirements. The email DLP pipeline resolves tenant context from the recipient email domain, routes each scan through the organization’s specific policy chain, and applies per-org configuration.

Administrators can configure per-organization settings: which sender domains are allowed, the default quarantine policy (quarantine, reject, or tag), attachment size limits, risk threshold overrides, and rate limits. Rate limiting uses the same Redis-backed sliding window as the AI gateway, with a separate namespace to prevent email volume from affecting gateway quotas.

Every scan, detection, and enforcement action is tagged with the organization ID, sender, recipients, and attachment count. The audit trail is queryable by organization, sender domain, risk level, and time range.

Admin Visibility and Observability

The quarantine admin API provides filtering, pagination, and aggregation — quarantine volume over time, top triggered entity types, breakdown by risk level and action. Administrators can download the raw .eml file for forensic review.

Prometheus metrics track scan volume, scan duration, entity detections by type, quarantine depth, attachment scan counts by content type, and rate limit events. The same Grafana dashboards that monitor AI gateway DLP now include email channel panels — because the metrics share a common label structure.

The observability story is the same as the detection story: one pipeline, one set of metrics, one view of DLP activity across all channels.

What This Means for Regulated Industries

For organizations in healthcare, financial services, insurance, and government, email remains the primary channel for sensitive data transmission. AI governance gets the headlines, but email governance has been a compliance requirement for decades.

The Arbitex approach unifies both under a single detection engine. The DLP accuracy that protects AI prompts — the same pattern matching engine, the same NER stack, the same contextual validator — now protects email with identical coverage. Compliance teams get a single audit trail. Security teams get a single set of metrics. Policy administrators configure once and enforce everywhere.

No separate email DLP product. No detection parity gaps. No split audit trails.

For the DLP pipeline architecture, read the complete pipeline series. For detection accuracy, see how we measure DLP accuracy. For encryption of audit data, see BYOK encryption for audit logs.

Book a demo to see the unified DLP pipeline inspect your AI and email traffic.