Trusted Systems Are Not Safe
Even the systems built to protect you can become the weakest link.
CVE 2026 22769 in Dell RecoverPoint for Virtual Machines shows exactly why. A platform designed for backup and disaster recovery allowed attackers to gain root-level access and maintain persistent control for over a year, deploying backdoors like Brickstorm and Grimbolt. Organizations relied on this trusted system to safeguard critical data, but that trust was exploited.
Attackers do not just encrypt files. They target centralized authority and orchestration. Once they control the system that manages backups, they can:
This is not a flaw in a single vendor, it is a fundamental weakness of centralized architectures. Multi-region backups, high availability clusters, and even hybrid deployments all rely on a single control plane. When that control plane is compromised, redundancy and replication do little to stop the attack.
Why Traditional Recovery Fails
Centralized systems concentrate both authority and risk. Recovery plans often assume the orchestration platform will remain intact. Attackers exploit that assumption. In long dwell time attacks, they test privileges, manipulate policies, and quietly prepare the environment so that when encryption begins, recovery is already compromised.
Even compliance driven retention cannot stop this if the control layer itself is the attack surface.
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Data-Centric Resilience with Myota
Myota assumes systems will be compromised. Its Shard and Spread™ architecture shards and distributes encrypted, post-quantum protected data across independent storage locations.
Even if a trusted system is breached tomorrow, the data remains secure and recoverable.
The Truth About Trust
Vulnerabilities will always exist. Trusted platforms can always be weaponized. Relying on a system to protect itself is a gamble. The question is simple: can your data survive when the systems around it fail?
With Myota, it can.
“Trust the architecture, not the platform” is an important distinction. Security failures often come from assuming the platform itself will remain trustworthy indefinitely. In practice, every system eventually fails, becomes compromised, or drifts from its original assumptions. Architectures that assume failure and preserve integrity at the data layer—through distribution, immutability, and verifiable state—tend to be much more resilient over time. The real challenge is not preventing every failure. It is designing systems where failure does not destroy trust in the data.
Centralized trust is always convenient... until it’s breached. Recovery systems with root authority become single points of systemic failure. Resilience really starts when data protection no longer depends on the integrity of the platform meant to defend it.