Introduction
Scraping emails from Office 365 can power analytics, compliance, lead capture, and workflow automation. But doing it the wrong way leads to throttling, data gaps, broken jobs, or even compliance violations. The following 12 mistakes appear frequently in real-world projects and migrations, along with actionable tips to build a secure, reliable, and maintainable pipeline.

1. Treating Office 365 like IMAP-only
   Relying solely on legacy IMAP against outlook.office365.com is brittle, incomplete, and harder to secure. IMAP often misses rich metadata, suffers from provider policy changes, and isn’t optimized for modern Microsoft 365 tenants. Prefer Microsoft Graph (with mailbox permissions) or Exchange Web Services (for older estates) because they provide richer properties, fine-grained filters, delta sync, and better tenant-aligned security controls.

2. Using basic auth or app passwords
   Basic auth was deprecated for most Exchange Online protocols, and app passwords bypass conditional access and modern security controls. Always use OAuth 2.0 with Azure AD app registrations, least-privilege scopes, and conditional access. This improves security, observability, and long-term compatibility.

3. Over-permissioning the app
   Granting wide scopes like full_access_as_user or application-wide mailbox access is risky and often unnecessary. Map the exact need first: read-only versus read-write, single mailbox vs. selected mailboxes, mailbox settings vs. message content. Then request the minimal Graph scopes (e.g., Mail. Read for delegated, or application scopes restricted via app access policies) to reduce blast radius and simplify security reviews.

4. Ignoring throttling and mailbox limits
   Microsoft 365 enforces service protection limits. If scraping logic floods endpoints, requests will be throttled or delayed, and jobs will fail sporadically. Implement exponential backoff, respect Retry-After headers, budget request rates, and batch operations. For large tenants, parallelize carefully across mailboxes with global rate control and per-mailbox caps.

5. Skipping delta queries and change tracking
   Pulling every message on each run wastes API calls and time and increases throttling risk. Leverage Graph delta queries or change tracking to fetch only what changed since the last checkpoint. Persist watermarks per mailbox and per folder to achieve incremental sync at scale.

6. Forgetting folder-specific nuances
   Teams often scrape only the Inbox and miss critical messages in subfolders, Archive, or Shared Mailboxes. Enumerate folders and their hierarchies, and include system folders like Junk Email and Recoverable Items when the use case demands it. Maintain a folder map and re-scan periodically because users and automation rules change folder destinations.

7. Mishandling shared and resource mailboxes
   Shared mailboxes, group mailboxes, and resource mailboxes have unique permission and access patterns. Plan app access policies to constrain application permissions to specific mailboxes. For delegated flows, ensure the signed-in principal has explicit rights to the target mailbox. Test each mailbox type—user, shared, group—to confirm consistent behavior.

8. Not normalizing message identities
   Message IDs, InternetMessageId, ETag, and changeKeys all serve different purposes. Failing to normalize leads to duplicate processing or missed updates. Establish a canonical key strategy (e.g., mailboxId + messageId) and track versioning fields to detect updates, moves, and soft-deletes. Store hash digests of relevant fields to quickly detect content changes.

9. Parsing only the body and ignoring headers
   Valuable context lives in headers: Received chains, DKIM/DMARC results, X-MS-Exchange attributes, and spam verdicts. Overlooking headers reduces accuracy in analytics, threading, or fraud detection. Capture a safe subset of headers, normalize them, and make them queryable for downstream use cases.

10. Disregarding MIME and attachments complexity
    Email content can be multipart, with inline images, calendar items, S/MIME-encrypted parts, or nested attachments. Naive body scrapers miss text or mishandle base64 payloads and content types. Use robust MIME parsers, preserve content-type metadata, and store attachments with content hashes, size, and disposition. For encryption, plan for key management or skip decryption where policy forbids it.

11. Storing sensitive data without governance
    Emails may contain PII, financial data, or credentials. Copying content into ungoverned data stores or logs can create shadow risk. Apply data minimization: store only the fields needed. Classify, encrypt at rest and in transit, mask or tokenize sensitive fields, and enforce role-based access controls. Align retention with legal and compliance policies (eDiscovery, litigation hold, retention labels).

12. No observability, idempotency, or recovery
    Scrapers often run silently until something breaks. Without metrics, structured logs, and dead-letter queues, troubleshooting is painful. Implement:

• Metrics: requests per second, success/error rates, throttle events, per-mailbox lag.

• Idempotency: ensure a message processed twice doesn’t create duplicates.

• Checkpointing: per mailbox, per folder, with durable storage.

• Retry strategy: exponential backoff with jitter; poison message isolation.

• Runbooks: clear operational playbooks for failures and rehydration.

Security and Compliance Essentials

• Least privilege: Match scopes to use case; restrict application access to approved mailboxes via app access policies.

• Conditional access: Enforce device, network, and risk-based policies for delegated flows.

• Auditing: Enable mailbox auditing and log API usage for compliance and incident response.

• Data residency and retention: Keep scraped data in compliant regions and honor retention/hold requirements.

Performance and Scalability Tips

• Prefer server-side filters and select clauses to reduce payload. For example, request only the fields needed for indexing or routing.

• Use delta queries, paging, and batching to minimize round-trip.

• Partition workloads by mailbox and time windows; avoid “all mailboxes at once” spikes.

• Cache folder maps and schema to cut redundant calls.

Testing Checklist Before Production

• Test with realistic mailbox sizes, varied folder structures, and problematic content (HTML-heavy, attachments, calendar invites).

• Verify throttling behavior with controlled bursts and ensure graceful degradation.

• Validate permissions through a security review and least-privilege enforcement.

• Confirm end-to-end lineage: message enters tenant, scraper ingests once, downstream systems receive normalized records, and observability captures the full path.

Conclusion
Scraping emails in Office 365 is not just about pulling messages—it’s about doing so securely, efficiently, and compliantly. By embracing modern auth, least-privilege scopes, delta-based synchronization, robust MIME handling, and strong observability, teams can avoid the most common pitfalls and deliver a resilient pipeline that scales with the business.