Failure Pattern
Data replication tools move sensitive data between systems without strong identity validation. Attackers compromise upstream nodes to poison or steal replicated data.
What We See in the Field
A compromised workload writes malicious or exfiltrated data that propagates across all replicas. Monitoring tools accept the changes because replication is trusted by design.
Underlying Causes
Blind trust in replication jobs
Shared service accounts
Lack of workload-bound identity
No verification of replication source
Replication pipelines built for convenience, not security
Trust-Native Network Resolution
DTL enforces identity on data replication flows. Only trusted workloads can initiate or receive replicated data. Compromised nodes fail identity validation.
Broken Trust Assumption
This failure pattern has played out repeatedly in real security incidents—not because of missing tools, but because of how trust is assigned.
In breaches such as SolarWinds, Capital One, Okta, and MOVEit, attackers did not bypass security controls. They operated through them, using valid identities, trusted credentials, signed code, and encrypted sessions. Security systems accepted these signals as proof of legitimacy, allowing malicious behavior to proceed.
The common thread across these incidents is structural: identity was assumed based on trust signals, not proven at the moment of execution.