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Email Verification for Sensitive Actions (MFA)

calendar icon   Release Date: March 24, 2026

MFA OTP email thumbnail

GitGuardian now enforces multi-factor authentication (MFA) via email verification for all users who sign in with email and password. After entering your credentials, you'll receive a verification code at your email address to confirm your identity.

Beyond login, verification is also required before performing sensitive actions in your workspace settings — such as configuring SSO, creating API tokens, managing integrations, or inviting members.

Who is affected?

  • Users who log in with email and password will be prompted for email verification at login and before sensitive actions.
  • Users who log in via SAML SSO or GitHub are not affected — MFA is handled by your identity provider.

For more details, see the MFA email verification documentation.


Enhancements

  • Bring Your Own Sources: The POST /v1/scan/create-incidents API now supports an optional location.url field, allowing you to link scanned documents back to their origin (e.g., a wiki page, ticket, or config file). When provided, this URL appears in incident details for easy navigation to the origin of the leak.
  • Authentication: Personal Access Tokens (PAT) and Service Account Tokens (SAT) now use an improved v2 format with gg_pat_ and gg_sat_ prefixes for better detection and security.

Fixes

  • Audit Logs:
    • Fixed an issue where the incorrect actor was displayed for certain audit log entries in the frontend.
    • Audit logs are now properly generated when creating Custom Sources via API using Personal Access Tokens.
  • Incidents: Fixed an issue in the bulk filter panel where the select-all checkbox showed "0 incidents" and failed to deselect incidents after selection.
  • API: Fixed a bug in the /v1/public-incidents/secrets/{id}/occurrences endpoint when retrieving occurrences for incidents discovered through Explore.
  • NHI Governance: Resolved timeout issues when collecting Microsoft Entra ID data for workspaces with large datasets.