Sensitive data discovery
Find possible SSNs, ITINs, payment cards, bank details, credentials, private keys, health information and more. Add custom detection rules. Confidence levels and masked evidence keep findings in context.
Find sensitive data. Understand who can access it.
Put governance into practice, without a software license bill.
Follow the path from discovery to informed access decisions.
Scan Windows SMB shares by file contents, not just filenames. Find potential sensitive information in documents, mail archives, compressed files and scanned pages.
Connect share permissions, NTFS rights and Active Directory memberships to understand who can reach your data and why. Nested groups, loops and unresolved identities stay visible.
Let data owners review access from a frozen snapshot. Capture their decisions, create tasks for IT, and use a later scan to verify that permission changes have actually happened.
Purpose built for Windows file shares
and on premises Active Directory.
Find possible SSNs, ITINs, payment cards, bank details, credentials, private keys, health information and more. Add custom detection rules. Confidence levels and masked evidence keep findings in context.
Read share and NTFS permissions alongside Active Directory groups. Trace nested memberships and individual access paths, with unresolved accounts and incomplete answers clearly flagged.
Explore exposure maps, prioritize findings with risk triage, and identify stale or duplicate data. Connect findings to compliance standards with evidence reports.
Assign data owners and run campaigns from frozen snapshots. Record keep, remove, investigate or exception decisions. Create IT tasks and verify external changes with the next scan.
Read Windows Security logs for deletions, permission changes and refused access. Flag unusual behavior against learned activity patterns. Requires the appropriate Windows audit configuration.
Bring together held information for a subject access request. Track progress, review system health, and export CSV or printable reports backed by an append only audit log with a hash chain.
Microsoft Office / PDF / Email / PST & OST / ZIP, 7z & RAR / Images with local OCR
Encrypted, corrupt and unsupported files are reported as coverage gaps.OpenSource DataScope reads files, permissions and directory information. It does not change your source files, permissions or Active Directory. Your team stays in control of remediation.
Explore the architecture ↗Visibility into sensitive data, with control kept inside your network.
OpenSource DataScope operates entirely inside your network at runtime. It does not contact outside hosts, depend on a cloud service, or send telemetry. Content scanning and OCR happen locally.
The scanner reads source files, share permissions, NTFS permissions and Active Directory. It does not rewrite source contents or change permissions or directory memberships. Your administrators carry out remediation.
Windows authentication and application roles control access. Data owners review their assigned resources. Masked evidence, confidence levels and an append only audit log support accountable decisions.
Everything you need to take the next step.
Yes. OpenSource DataScope is available under the Apache License 2.0. There is no software license charge. You provide and operate the infrastructure.
The documented target is Windows Server 2019, 2022 or 2025 in an Active Directory domain, with PostgreSQL 16 or 17. It scans SMB shares on Windows Server 2016 or later within the same domain. Read the platform and sizing guide for requirements and validation status.
This project focuses on on premises Windows file shares and Active Directory. Microsoft 365, NAS appliances, Azure Files and multiple domain or forest environments are outside the current scope.
Start in a lab. The repository documents automated testing and remaining Windows domain lab checks. Review the acceptance status before relying on it. Sensitive data findings are possible matches, and compliance reports provide evidence rather than certification.
Contribute code, improve documentation, or share feedback from a lab with synthetic data. Start with the contribution guide. Report vulnerabilities privately using the repository’s security guidance.
Set up a lab, explore the source, and see what your data can tell you.