Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Privileged access has become significantly more complex over the last few years. Security teams are managing Windows and macOS devices, administrators rely on native tools to do their jobs, network infrastructure continues to expand, and operational technology environments are becoming increasingly interconnected. At the same time, manual approval processes and fragmented controls often create more friction than protection.

AI agents are no longer just answering queries or summarizing documents. They are booking meetings, pulling customer data, triggering workflows, and even making decisions across systems. And they don’t ask for permission every time. That’s where the real problem starts. Because once an AI agent is connected to your tools, APIs, and internal systems, the question isn’t what it can do, it’s what it should be allowed to do.

Data Loss Prevention (DLP) is all about keeping your business data safe from getting leaked, lost, or accessed without admin permission. It protects, identifies, analyzes, and blocks unauthorized data transfers within the network and through connected devices and outbound emails. DLP enforces company policies, preventing users from sharing confidential information. It further allows organizations to set USB restrictions to protect sensitive information at every stage of operations.

The notification of the Digital Personal Data Protection (DPDP) Rules, 2025, marks a major turning point in how businesses in India collect, use, and safeguard personal data in the digital ecosystem. Together with the Digital Personal Data Protection (DPDP) Act, 2023, these Rules create a rights-based, consent-driven framework that places citizens at the centre of data processing while still enabling responsible innovation and growth in the digital economy.

Picking the best endpoint security for business depends on your org's size, stack, and how much in-house security muscle you actually have. CrowdStrike Falcon leads on pure detection, Microsoft Defender wins on value for M365-heavy shops, miniOrange is the strongest choice for mid-market businesses that need identity-first device security without the enterprise price tag, and IBM MaaS360 covers the UEM-first crowd that needs mobile + BYOD sorted from a single console.

AI agents are increasingly accessing APIs, databases, SaaS applications, MCP servers, and other services without human intervention. As these autonomous systems become part of enterprise infrastructure, organizations need reliable ways to verify their identity before granting access to sensitive resources. Traditional authentication methods such as API keys and bearer tokens were designed for applications and users, not autonomous agents operating continuously across distributed environments.

As organizations expand across cloud platforms, SaaS applications, remote teams, and AI-driven systems, managing access becomes more challenging. Security teams must ensure users, applications, and automated workflows can access the resources they need without exposing sensitive data or critical systems. This is where the RBAC vs ABAC discussion becomes important.

As a fintech organization, you depend on multiple systems like AWS, Databricks, Snowflake, Power BI, Stripe Treasury, Identity Providers (IdP), developer tools, internal operational platforms, and many more. Managing access and access level across platforms is often disconnected and spread across emails, Slack approvals, tickets, and sometimes spreadsheets. Obviously, this is inefficient. There'll be delays in onboarding. But that's the least of your worries.

If you’ve deployed your first AI agent, then you must have given it access to your CRMs, ticketing systems, and your cloud storage. This AI agent is programmed to run 24/7, make decisions, call external APIs, and trigger actions (without a human in the loop). Now, answer these questions: If you cannot answer these questions, then you have an agentic AI identity issue. Traditional Identity and Access Management (IAM) was built for service accounts with static API keys and users with usernames.

Since the announcement of the Atlassian Data Center end-of-life, organizations have started planning their migration to the cloud. However, it’s not a simple copy-and-paste job. Over time, your Jira and Confluence instances accumulate years of attachments. These might include screenshots, log files, ZIP files, duplicate uploads, and other items nobody remembers uploading. You might not even realize these files exist until migration begins and the bloat starts causing delays.