Post-breach data control

Works alongside your security stack

PastWipe complements IAM, EDR, DLP, SIEM/SOAR, key management and incident response. It adds post-breach data control without replacing them.

PastWipe™ complements existing security tools. It does not replace them. Prevention, detection and response remain essential. PastWipe adds control over how selected protected data may be used after it moves, and reduces its usable value outside approved conditions.

How PastWipe relates to your existing controls

Existing control What it does What PastWipe adds
Identity and access management (IAM) Authenticates users and grants access Uses identity signals to re-check whether a specific use is still authorised at the point of use
Endpoint detection and response (EDR) / device management Detects threats and reports device posture Uses device context as a condition for releasing protected content
Data loss prevention (DLP) Detects and blocks data leaving approved channels Addresses the copy that has already left, in supported workflows
SIEM / SOAR Collects events and runs response playbooks Supplies evidence records of control decisions to your monitoring and response workflows
Key management (KMS / HSM) Protects cryptographic keys Works with organisation-controlled keys
Incident response / DFIR Contains, investigates and recovers Adds a post-breach control stage and evidence for review
Encryption Protects confidentiality while keys and access stay controlled Asks whether data should still be usable when conditions are no longer trusted

Integration patterns

  • Identity: integration with enterprise identity providers for identity signals.
  • Monitoring: evidence records and control events streamed to SIEM/SOAR.
  • Storage and applications: connectors for selected storage, databases and applications.
  • APIs and SDKs: for embedding policy checks into applications.

What integration depth means for results

Enforcement depends on integration depth, supported applications, connectivity, device trust and identity signals. A controlled evaluation defines the data class, workflow and signals in advance, so that results can be measured.

Deployment and operating model · Scope a controlled evaluation