Most teams buy detection on a single number. The datasheet says “millisecond detection,” the proof-of-concept fires the instant a test payload lands, and the box gets checked. Then a real AI agent incident runs in production, and the postmortem shows the attack completed its objective well before anyone contained it, even though the alert, technically, fired in milliseconds. The number was real. It just measured the wrong thing.

archTIS and Mattermost are pleased to announce a collaboration to deliver policy-enforced, data-centric security to secure operational collaboration for Defence Ministries, NATO Allies, and coalition partners worldwide. The collaboration combines Mattermost’s secure, mission-critical command-and-control surface with archTIS Trusted Data Integration (TDI) platform, to enable secure collaboration using dynamic policy orchestration via Attribute-Based Access Control (ABAC).

Agentic AI is rewriting the rules of enterprise risk, operating across distributed systems at a speed and scale that most security architectures weren’t designed to handle.

The first time a security team needs an AI agent audit trail is usually 72 hours after the agent has already done something it shouldn’t have. Detection fires. Someone pulls every relevant log from the SIEM (Kubernetes audit, container runtime, cloud audit) and three hours in realizes the events that actually matter were never written. Which prompt triggered the tool call. Which parameters the agent passed. Which output left the cluster.

Most organizations can't answer three basic auditor questions simultaneously: where PII lives, who can access it, and how it's protected. One-off scans and manual classification go stale as data volumes grow. A repeatable, eight-step PII protection program from initial discovery through ongoing governance is what separates a defensible compliance posture from a snapshot that collapses under scrutiny.

Building a resilient CI/CD pipeline means protecting every piece of data that makes your code run. Your environment variables, secret tokens, and configuration files demand the exact same security as your core repositories. Traditional backup protocols leave these assets completely vulnerable to silent manipulation. If ransomware subtly modifies your archived backup, executing a restore will deploy the corrupted files straight into production.

Every AI-SPM tool runs posture and detection with a single arrow: runtime evidence flowing back to rank posture findings. The load-bearing direction runs the opposite way, and almost nothing runs it — posture flowing forward to tell the detection layer what an attack even looks like.

This report examines the disaster recovery (DR) readiness across the Acronis Cyber Protect Cloud platform, managing thousands of DR deployments across dozens of data centers worldwide. The analysis focuses on Q1 2026 (January – March) and reveals a clear gap between having DR configured and being truly ready for a disaster.