Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

There is no shortage of guidance available to MSPs on how they should secure customer environments. Security frameworks, industry standards, regulatory requirements and insurance obligations all provide recommendations on the controls organizations should have in place. Yet despite this abundance of guidance, cyber incidents remain common and continue to increase. At the same time, requirements are becoming more complex.

Email remains the primary entry point for cyberattacks, making effective email security more critical than ever. That’s why we’re especially proud that customers ranked Acronis Cyber Protect Cloud in the G2 Fall 2026 Cloud Email Security Grid Report. Because G2 rankings are based on verified customer reviews, this recognition reflects the experience of the organizations and service providers that rely on Acronis to protect their users, data and business communications every day.

Security teams rarely lack alerts. The harder problem is working out which ones belong to the same attack — and doing it quickly enough to stop the damage. An endpoint tool may flag suspicious activity on a device. An identity platform may record an unusual sign-in. An email security product may spot a malicious message. When those systems operate separately, each one shows only part of the incident.

Acronis Cyber Protect Cloud has once again earned the highest possible score in AV-TEST’s business Windows endpoint protection evaluation, achieving 18 out of 18 points in the May–June 2026 test. The latest result also extends a consistent record in AV-TEST’s business Windows evaluations. Acronis achieved the same 18/18 result in the February and April 2026 tests, making the May–June evaluation its third consecutive perfect overall score in 2026.

AI DLP (artificial intelligence data loss prevention) is a category of data protection that inspects the prompts and file uploads an employee sends to a generative AI tool, before that content reaches the model, which is what separates it from file-based or network-based DLP.

Shadow AI is the use of generative AI tools by employees without the knowledge, approval or oversight of an organization's IT or security teams.

To write an AI usage policy, define its scope, list approved and prohibited tools, name the data types banned from prompts, write clear rules, align to recognized frameworks and set enforcement. A written policy is the decision layer; pairing it with technical controls is what turns those decisions into protection.

Information technology and operational technology are increasingly connected, but they are not interchangeable. IT is built around information and business services; OT is built around physical processes, equipment and safe operation. That difference shapes their security priorities, asset lifecycles, maintenance practices, network architecture and recovery requirements.

AI productivity tools are creating a prompt-level data leakage problem: 77% of employees paste data into generative AI tools, and 82% of that activity comes from unmanaged accounts, according to the LayerX Enterprise AI and SaaS Data Security Report 2025. Every paste into ChatGPT, Copilot or another GenAI tool is a potential exposure of sensitive data that traditional file-focused controls were never built to see.

No combination of controls guarantees that ransomware actors will never gain access or cause any impact. What the 12 controls below do is reduce the attacker's opportunities, accelerate containment and preserve the ability to restore operations without relying on ransom payment. Think of ransomware resilience as a continuous lifecycle rather than a fixed sequence: govern and identify, harden and prevent, detect and contain, roll back and recover, and improve and patch.