Linear DLP & DSPM

Discover, classify & remediate sensitive data in Linear issues, comments & attachments with Strac.

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Linear DLP & DSPM

Strac Linear DLP flow — Linear scanned by Strac DLP, sensitive data redacted before exposure

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✨ TL;DR: Strac Linear DLP

Linear is the issue tracker where fast-moving software and support teams work all day — which is exactly why regulated data (customer PII, PHI, PCI card data, API keys, secrets, and source code) ends up in issues, comments, and attachments.
Strac Linear DLP connects to Linear in minutes via API (agentless), scans existing and new issues, and classifies sensitive data with machine learning plus validated detectors — including OCR on image and document attachments.
Remediation is built in: redact, mask, or alert the moment sensitive data appears — not just a report. Authorized users can still retrieve the original from the secure Strac vault.
Every detection and action is audit-logged, giving you evidence for SOC 2, HIPAA, PCI DSS, and GDPR.
See the flow below, and watch the redaction demo further down.

Strac Linear DLP flow — Linear issues, comments, and attachments scanned by Strac DLP; PII, PHI, PCI, and secrets redacted before exposure; SOC 2, HIPAA, PCI, and GDPR ready — Strac Linear DLP: discover, classify, and remediate sensitive data across Linear issues, comments, and attachments — agentless, in about ten minutes.

Why Sensitive Data Ends Up in Linear

Linear is built for speed, and speed is exactly how regulated data lands in a project tracker. The same ease of collaboration that makes Linear great — quick issues, threaded comments, drag-and-drop attachments — also makes it a place sensitive data accumulates without anyone deciding it should. A few patterns show up in almost every workspace:

Engineers pasting secrets to reproduce a bug. A .env snippet, a database URL, an AWS access key, or an OAuth token dropped into an issue so a teammate can reproduce the problem — and then left there indefinitely.
Support escalations carrying customer PII. When a ticket is escalated from your help desk into an engineering issue, the customer’s full record often comes with it: name, email, sometimes an SSN, a date of birth, or a card number pasted straight into the description.
Attachments nobody inspects. Crash logs, exported CSVs, and screenshots attached to an issue routinely contain PII or credentials — and because they are files, traditional controls never look inside them.
Broad access and easy export. Linear is designed for the whole team to see and move work quickly. That openness is a feature, but it means anything sensitive in an issue is visible far beyond the person who put it there.

None of this belongs in an issue tracker, and by default none of it is inspected. That is the gap Strac Linear DLP closes.

✨ Where Strac Finds & Redacts Sensitive Data in Linear

Strac inspects every place data lives in Linear and remediates in context, so the issue keeps working while the regulated values are removed:

Issue descriptions & titles — pasted logs, stack traces with tokens, and customer details in a repro.
Comments & threads — the back-and-forth where a teammate drops a credential or a customer email to move a ticket forward.
Attachments — crash logs, CSVs, PDFs, and screenshots that Strac reads with OCR and document parsing, so sensitive data hidden inside a file is found, not waved through.

A Linear issue with customer name, email, SSN, card number, and an AWS key each redacted by Strac, plus an attachment scanned by OCR and a remediated, audit-logged status — Strac detects and redacts PII, SSNs, card numbers, and secrets inside a Linear issue — and runs OCR on attachments — then audit-logs every action.

How Strac Linear DLP Works

Connect Linear to Strac with OAuth in about ten minutes — no agents and no proxies. From there Strac runs three jobs continuously:

Discover. Strac scans your existing Linear issues, descriptions, comments, and attachments and then monitors new activity in real time, across your entire workspace.
Classify. A blend of machine-learning models and validated detectors identifies PII, PHI, PCI card data, credentials and API keys, and source code — with OCR on images (PNG, JPEG, screenshots) and deep parsing of PDFs and documents. Detection is content-based, so a screenshot of a dashboard or a .env file is caught regardless of how it is labeled.
Remediate. Strac applies your configured action per data type and policy — redact, mask, or alert. Redacted values are replaced with safe placeholders, and authorized users can still retrieve the original through the secure Strac vault. Every action is written to an audit record: user, issue, data classes detected, and remediation applied.

Real-Time Alerts When Sensitive Data Hits a Linear Ticket

Want to know the moment an account number, a password, an SSN, or a card number lands in a Linear issue or comment? Strac watches Linear in real time and fires an alert the instant sensitive data is added — the same way it works for Slack, Jira, and your other SaaS apps. You choose exactly which data types trigger it — account numbers, passwords, API keys, SSNs, card numbers, PHI — and where the alert goes: Slack, email, or your SIEM. Set it to alert-only, or have Strac automatically redact the value and log the event, so security hears about the risky ticket without reading every issue.

Want to stop sensitive data before it is ever posted? Pair the Linear integration with Strac Browser DLP, which inspects and blocks or redacts sensitive data at the point of paste — before it reaches Linear at all.

Sensitive Data Types Strac Detects in Linear

Out of the box, Strac Linear DLP detects and remediates a broad catalog of sensitive data, and lets you add custom detectors for org-specific data classes:

PII — names, emails, phone numbers, SSNs, dates of birth, driver’s licenses, passport numbers, addresses.
PCI — credit and debit card numbers (Luhn-validated), CVV, bank account details.
PHI — health and medical information for HIPAA-regulated teams.
Secrets & source code — AWS/GCP/Azure keys, OAuth tokens, JWTs, SSH and private keys, and code snippets.

For the full list Strac identifies and masks automatically, see the catalog of sensitive data elements.

🎥 See Strac DLP Redaction in Action

Watch how Strac detects and redacts sensitive data in real time across your SaaS apps — the same engine that protects your Linear workspace:

Linear DLP for Compliance & Audit

Because every detection and remediation is logged, Strac gives you the evidence trail auditors expect for SOC 2, HIPAA, PCI DSS, and GDPR. Granular access controls ensure only authorized users can view sensitive values, and reporting shows exactly what was found and fixed across your Linear workspace — so compliance, risk, and security teams can prove control instead of hoping nothing leaked.

✨ Using Linear with AI Agents? Add MCP DLP

This page covers the data your team puts into Linear directly. If you also connect Linear to AI agents — Claude, Cursor, Copilot, or a custom agent — through the Model Context Protocol (MCP), that is a separate data path: the agent reads issues, comments, and attachments straight into a model’s context, with no human paste to intercept. Strac Linear MCP DLP redacts sensitive data on that path before the model ever sees it. Most teams need both — SaaS DLP for what people put into Linear, and MCP DLP for what agents pull out.

Strac Linear MCP DLP — AI agents (Claude, Cursor, ChatGPT) read Linear through the MCP DLP gateway; PII, PHI, PCI, and secrets are redacted from every tool call before the model sees them — Strac Linear MCP DLP: every MCP tool call from an AI agent is inspected and sensitive data redacted before it reaches the model context.

🌶️ Spicy FAQs for Linear DLP

Doesn’t Linear’s own permissions handle this? Permissions decide who can open an issue — they do nothing about the SSN or API key sitting inside it. Everyone with access still sees the raw data, and exports carry it straight out. DLP works on the content, not just the door.

Won’t redaction break the issue for the engineer working it? No. Strac removes only the regulated element and leaves the rest of the issue intact; the placeholder shows what was there, and an authorized user can retrieve the original from the vault when there’s a legitimate need.

Everyone says they detect secrets — what’s different? Two things: Strac reads inside attachments with OCR and document parsing (where crash logs and screenshots hide credentials), and it pairs ML with validated detectors so a real AWS key gets caught while a random string doesn’t flood you with false positives.

Is this just for AI agents reading Linear? No — this page is about your team’s day-to-day Linear usage. If you also connect Linear to Claude, Cursor, or Copilot, see the Linear MCP DLP section above.

Using Linear with Claude, Cursor, or custom AI agents? See Linear MCP DLP for how Strac protects sensitive data on the Model Context Protocol path. Explore related coverage: Jira DLP, Asana DLP, and the broader SaaS DLP platform.

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Sharepoint DLP Use Cases

Practical Scenario

A hospital’s billing and administrative teams use SharePoint Online to store patient invoices, medical reports, and insurance forms. While collaborating with external insurance providers, a staff member accidentally updates the permissions on a SharePoint document library to “Anyone with the link,” exposing potentially thousands of patient files containing PHI.

How Strac's Sharepoint DLP Helps

Continuous Data Discovery: Strac automatically scans existing and newly uploaded documents, identifying PHI (e.g., medical record numbers, Social Security Numbers).
Classification & Labeling: Once identified, files are labeled (e.g., “HIPAA Sensitive”), ensuring that administrators know which documents require the highest level of protection.
Visibility into Access: Strac provides real-time insight into who has access to these sensitive documents. Administrators can instantly see if unauthorized users or broad groups have viewing rights.
Revoke Public Links: If a file is publicly accessible, Strac immediately revokes those links and restores restricted access.
Alerts & Quarantines: When someone attempts to share PHI externally, Strac can alert admins, quarantine the file for review, or completely block the action.
Audit-Ready Reports: All actions are logged, enabling quick incident response and demonstrating HIPAA compliance for audits.

Practical Scenario

A mid-sized investment firm uses SharePoint to collaborate on various client files, including:

Credit card statements (subject to PCI-DSS)
ID documents (Driver’s Licenses, Passports, etc.) used for KYC (Know Your Customer) verification
Banking information such as account and routing numbers

An associate accidentally shares a SharePoint folder containing these files with a newly onboarded client who does not require access to all confidential documents. This folder is also accessible to several internal teams outside the immediate project, creating multiple potential exposure points.

How Strac's Sharepoint DLP Helps

Comprehensive Data Discovery: Strac scans both existing and newly uploaded documents in SharePoint for sensitive information such as credit card numbers, bank account details, and ID documents (Driver’s License, Passport formats).
Classification & Automated Labeling: Once identified, Strac applies meaningful labels (e.g., “PCI-DSS Sensitive,” “PII – ID Documents,” “Banking Info”) to ensure these files stand out and are subject to stricter security rules.
Visibility into Access: Strac provides an immediate view of who currently has access to these sensitive files. This allows admins to spot situations where external clients or internal teams unnecessarily have permissions.
Public Access Revocation: If a labeled document (e.g., containing card data or ID scans) is found to be publicly shared or too broadly accessible, Strac automatically revokes these links or permissions, aligning access with the principle of least privilege.
Alerts, Quarantines, and Blocks: When a user attempts to share a labeled document with outside domains—or with an entire department—Strac alerts administrators or quarantines/blocks the file share, depending on policy settings.
In cases where the share is intentional but needs review, admins can approve or deny the request within Strac’s dashboard.
Audit & Compliance: Every sharing event, label assignment, and access revocation is logged, creating a detailed audit trail. This helps demonstrate compliance with PCI-DSS, KYC, AML, and other regulatory requirements.
Automatic reporting simplifies any regulatory or internal compliance audit, reducing the administrative burden on security and compliance teams.

Practical Scenario

A software company keeps source code, product roadmaps, and design specs in SharePoint. Several teams—including external contractors—use the same SharePoint site. A developer accidentally grants a large group, including some non-disclosure–exempt contractors, access to a folder containing patent-pending code.

How Strac's Sharepoint DLP Helps

Holistic File Scanning: Strac inspects documents, PDFs, and archives for code snippets, system designs, and proprietary business terms to detect potential IP.
Intelligent Labeling: Documents identified as containing IP or trade secrets are automatically classified (e.g., “Proprietary IP”), reinforcing the need for restricted sharing.
Real-Time Access Insights: With Strac, administrators can instantly see who has access to IP-tagged files, enabling them to remove unauthorized users or reduce permission scopes.
Immediate Link Removal: If a contractor or external partner is mistakenly granted access to IP, Strac revokes public or unauthorized sharing before the files can be downloaded.
Alerts & Blocking: Strac’s policies can be configured to alert security teams or block external sharing attempts for files containing proprietary content.
Incident Response & Auditing: Detailed logs of every share request, label change, and access revocation aid in quick incident resolution and help prove due diligence if legal issues arise.