Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

It’s fall, the leaves are starting to turn, school is back in session, but that also means our bi-annual workflow competition You Did WHAT With Tines?! (YDWWT) is here for the Fall 2025 season! This competition challenges our community of builders - from customers to partners - to bring forth their most impressive workflows, in the hopes to be recognized among the best of the best.

Few security practices carry as much weight as patch management. Consider the cautionary tale of Travelex. In early 2020, the British currency exchange was hit by a ransomware attack that spread quickly across its network, locking staff out of their systems. Reports suggest the company paid millions to restore access and prevent sensitive data from being sold; an outcome that underscores how a single gap in patching can cascade into a business-wide crisis.

Every IT team is under pressure to “do more with AI.” A new tool promises smarter workflows, a new agent claims to replace manual tasks. But if you’re managing service requests, availability SLAs, patch cycles, infrastructure capacity, and application performance every day, you know the truth: AI doesn’t automatically reduce complexity on its own.

Managed detection and response (MDR) providers faceskyrocketing demand and rising stakes. The MDR market is projected to grow to $11.8 billion by 2029 (up from $4.1 billion in 2024), a 23.5% compound annual growth rate driven by the intensifying landscape of advanced threats and sophisticated attacks, as well as ongoing cybersecurity talent shortages.

Businesses everywhere are moving fast to adopt AI. Yet many initiatives are fragmented, siloed, difficult to scale, and lacking adequate governance. New research from Forrester Consulting, commissioned by Tines, surveyed more than 400 IT leaders in North America and Europe on the challenges of scaling AI and the role IT can play. The findings show that while governance, security, and cross-functional alignment are top priorities, they’re also some of the biggest barriers.

Did you hear the news? You can now build MCP Servers on Tines! Connect Tines stories to your LLM ecosystem in seconds using a new action template, enabling secure Model Context Protocol (MCP) server deployment. We also enhanced our AI usage reporting, allowing you to track AI adoption and manage costs more efficiently with better visibility into detailed AI reporting, including.

The cybersecurity lifecycle is the foundation of how security teams protect, detect, and recover from threats. From asset discovery to post-incident recovery, the lifecycle defines the processes organizations rely on to safeguard data and systems. But here’s the challenge: While the lifecycle provides a roadmap, operationalizing it in modern SOCs is messy. Disconnected tools, alert fatigue, and endless manual tasks slow down response times and create gaps that attackers exploit.

At the RSAC Conference this year, it seemed that every cybersecurity company had suddenly become an agentic AI company. According to such vendors, AI agents were the solution to every security problem keeping CISOs up at night. The audience, however, was understandably skeptical. Concerns over vendor promises fell into two camps. The first camp: companies that took whatever AI capabilities they had and slapped the word ‘agentic’ on them (aka ‘agent-washing’). Or even worse.

Financial services and insurance companies live under some of the toughest compliance rules in the world. Regulations keep multiplying. Cyber threats keep evolving. And the penalties for getting it wrong range from multi-million-dollar fines to reputational damage that takes years to recover. The problem? Too many GRC programs are still manual, reactive, and siloed. Outdated tools and processes force teams to spend countless hours chasing evidence and preparing for point-in-time audits.