Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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.

Ransomware protection is a coordinated set of controls that reduces the likelihood of compromise, detects and contains malicious activity, protects recovery infrastructure and restores operations when an attack succeeds. It spans identity security, vulnerability and patch management, endpoint protection, EDR or XDR, incident response, targeted rollback, immutable backup and disaster recovery. No single control covers the complete ransomware lifecycle.

EDR (endpoint detection and response) works by deploying sensors on protected endpoints to continuously collect selected behavioral telemetry, forwarding that telemetry to a centralized analytics layer, commonly cloud-hosted, that applies detection rules, behavioral analytics, machine learning and threat intelligence, and surfacing prioritized incidents in a console where analysts can investigate and respond.