Built for teams who handle sensitive data
Data Anonymizer is built by MagicByte Consulting. We created it to make safe sharing of logs, exports, diagnostics, and support bundles practical in real enterprise environments.
Help teams collaborate without spreading identifiers, secrets, and customer data across tools and inboxes.
Designed to run locally or on-prem, including restricted and air-gapped environments.
Engineers with hands-on experience in data engineering, infrastructure, and security.
Why anonymization matters
Incidents, support cases, and engineering collaboration require sharing artifacts quickly. Anonymization helps reduce risk without blocking progress.
Logs and exports can contain tokens, emails, account IDs, IP addresses, hostnames, and internal URLs. Even when intent is good, copying raw data into tickets and chat tools increases blast radius.
“Security vs. usability” is a false tradeoff. The goal is to remove sensitive values while preserving structure, formats, and the relationships engineers need to reproduce and fix issues.
Sharing sensitive artifacts is risky — and often painful
Most teams default to manual redaction and ad-hoc scripts. That’s slow, inconsistent, and hard to trust.
Humans miss things under time pressure, and different people redact differently. That creates uncertainty and review overhead.
Many organizations cannot upload raw logs or diagnostics to third-party services due to policy, regulation, or customer commitments.
Real data comes as folders and archives with mixed formats. You need consistent handling across files while preserving structure.
A pragmatic, offline-first anonymization workflow
Data Anonymizer is designed for enterprise constraints: local operation, predictable outputs, and workflow-friendly delivery.
- • File and folder inputs, including support bundles.
- • Preserves structure in output archives.
- • Configurable rules to match your data model.
- • Offline-first operation for restricted networks.
- • Wheel and Docker delivery for reproducible runs.
- • Optional preview and profiling modes to validate results (Pro).
The team behind Data Anonymizer
MagicByte Consulting builds and operates data-heavy systems. Data Anonymizer comes from repeated, real-world needs across support, engineering, and security workflows.
Pipelines, storage, and data-quality workflows where sensitive fields are easy to leak if not handled deliberately.
Production constraints: packaging, deployment, observability, and reliable execution in controlled environments.
Practical threat awareness: secrets hygiene, least-privilege access, and controls that match how teams actually work.
Make safe data sharing the standard
We want anonymization to be the default step before sensitive artifacts leave their original boundary — without turning every share into a bespoke security project.
We can help evaluate fit, review constraints, and propose an approach that works in your environment.