Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI tools have become a workplace staple, but their unsanctioned use has given rise to shadow AI. It refers to the untracked usage of any AI tools or applications without approval or overview of the information technology (IT) or security team. This is substantiated by the Verizon 2026 Data Breach Investigations Report (DBIR) which shows how rapidly the shadow AI trend is growing.

Most “AI SOC” demos out there can look great. The polished dashboard, the confident verdict, the slide that says “autonomous.” A demo is built to show the platform at its best, on clean data, in a controlled environment, answering a question the vendor already knew was coming. The differences only show up after you’ve signed, when the platform meets your real stack, alert volume, and compliance requirements.

AI agents and LLMs are already building, analyzing, and deploying code across your software development lifecycle. As software supply chains become increasingly AI-driven, proactive security and access controls are your only path to success. To effectively govern authentication and permissions without sacrificing development speed, you must update your access management strategies.

Security teams are under constant pressure to move faster without giving up control, but in many organizations, access requests, approvals and credential workflows still live outside secure systems. They happen in chat messages, ticket comments or manual processes in tools like Slack, Teams, Jira or ServiceNow, increasing risk, reducing visibility and slowing response times.

AI agents can reason through tasks, call tools, and adapt their next steps based on intermediate results. That flexibility is useful for building agentic applications, but it also creates security risk at runtime: A prompt injection attempt can change the agent’s instructions, a malicious request can try to exfiltrate sensitive data, and an unsafe tool call can lead to an action that the application owner did not intend.

AWS has become a default infrastructure platform for many organizations. It offers scale, flexibility and a broad service portfolio. However, for managed service providers (MSPs) and cloud providers, AWS pricing can be difficult to explain, forecast and package profitably. One of the most important cost factors is AWS data transfer cost. Internet egress, or data leaving AWS for the public internet, is the most familiar example.

Accelerating security solutions for small businesses‍ Tagore offers strategic services to small businesses. A partnership that can scale‍ Tagore prioritized finding a managed compliance partner with an established product, dedicated support team, and rapid release rate. Standing out from competitors‍ Tagore's partnership with Vanta enhances its strategic focus and deepens client value, creating differentiation in a competitive market.

A fully managed, end-to-end CrowdStrike deployment delivered at enterprise scale by Kroll A global quick-service restaurant brand needed to establish consistent, enterprise-grade protection and centralized visibility to quickly strengthen its security posture. It had to move fast without disrupting global operations or overburdening a lean IT team.

For years, VPNs have been the standard for securing remote access. But today's hybrid work environments, cloud applications, and evolving cyber threats have exposed the limitations of a security model built on implicit trust. Once a user authenticates through a traditional VPN, they often gain broad access to the corporate network. If those credentials are compromised, attackers can move laterally, access sensitive resources, and escalate an attack. Zero Trust takes a different approach.

AI is becoming part of almost everything: customer support, security operations, software development, research, analytics, internal workflows, and, most importantly, drafting emails. AI is increasingly embedded in real business processes, and that creates new risks, not to mention the level of unprecedented access mainly of these platforms to our data. Token torching (a type of Denial-of-Wallet (DoW) attack) is one emerging AI risk.