Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

When someone registers for an online service or healthcare portal, logs into an eCommerce store, or uses a streaming platform, the first interaction usually involves identity and authentication. For businesses, this moment is critical because it connects security, customer experience, and trust.

For many organizations, Grafana is a central operational system. Engineers use it to investigate issues, analyze logs, review infrastructure metrics, and query production-connected databases. But while dashboards are visible, the real sensitivity lies in the underlying data sources Grafana connects to. These data sources often include systems such as logs stored in Elasticsearch or OpenSearch, SQL databases like PostgreSQL or MySQL, and Amazon CloudWatch metrics.

Earlier this year, AWS experienced a 13-hour outage that was reportedly linked to one of its own internal AI coding tools. Apparently, their Kiro agentic coding tool thought that there was an issue with the code in the environment, and that the best way to fix it was to simply burn it to the ground.

PAM solutions in 2026 must cover non-human identities, enforce zero standing privilege, and deploy in days rather than quarters. Legacy vault-centric tools leave standing accounts in place between rotations, giving attackers persistent targets across service accounts and machine workloads. Evaluating modern PAM requires testing JIT access depth, AD/Entra ID integration, and real-world deployment timelines against your hybrid environment.

In 2026, threat intelligence isn’t just about tracking malware families or IP reputation. It’s about catching the earliest signals of identity abuse: stolen credentials, suspicious logins, token misuse, and privilege escalation attempts that move fast through cloud and SaaS environments. Credential abuse remains a key initial access vector, accounting for 70% of breaches. In response, modern threat intelligence tools are prioritizing identity signals.

This week, we released our 2026 State of Agentic AI Risk Report, a global survey of 250 senior cybersecurity leaders examining how enterprises are approaching agentic AI as it moves closer to production. The findings point to a clear reality. While AI agents are advancing quickly, security leaders are deliberately slowing adoption. In fact, 98% of respondents say security and data concerns have already slowed deployments, added scrutiny, or reduced the scope of agentic AI initiatives.

A handful of services quietly redeploy. No one directly manages the traditional network perimeter. But somewhere along the way, an API key ends up in the wrong place. The reality of modern cloud security is that new identities are created fast, and permissions are granted broadly to keep things moving. Over time, these permissions collect unused rights and drift away from least privilege.