Category: Tidbits

Enterprise Java applications do not often break due to business logic. The reason they break is that dependency ecosystems evolve all the time. Manual maintenance in most large systems consists of hundreds of third-party libraries, and small upgrades occur regularly as a result of security patches, code corrections, or vendor advice. The problem is not

AI-assisted development is accelerating software delivery — but it also amplifies a question many teams still ignore: what happens to your sensitive data when you use AI tools? API keys, customer PII, internal business logic, production logs — once shared with third-party AI services, you may lose control over where that data is stored, who

Introduction: Modern Directories Meet Legacy Constraints As organisations strengthen security and centralise identity management, IBM MQ administrators increasingly integrate with enterprise LDAP directories such as Microsoft Active Directory or OpenLDAP. This enables authentication using corporate credentials and authorisation through LDAP users or their group membership, instead of relying on local OS users. However, on Windows

Beyond being a cliché, “artificial intelligence” and its associated automation technologies have driven major developments in security, signifying that important changes have occurred in this field. In the field of cybersecurity, artificial intelligence refers to systems that acquire data, trace patterns, and forecast trends. Typically, this application is performed using machine learning, neural networks, or

GitOps has a fundamental tension: everything should be in Git, but secrets shouldn’t be in Git. You need database passwords, API keys, and tokens to deploy applications, but committing them to a repository is a security incident waiting to happen. This post covers how to solve this with Infisical and External Secrets Operator (ESO) –

The Gap Nobody Is Talking About The Model Context Protocol (MCP) is quickly becoming the de facto standard between AI agents and the tools they use. The adoption is growing rapidly – from coding assistants to enterprise automation platforms, MCP servers are replacing custom API integrations everywhere. As a result of the MCP’s rapid growth, the security community

While working with Data Analytics Systems, it is crucial to understand what is happening with the data, who can see specific data, which data we already have in the system, and which should be ingested. This is a typical business challenge that most companies face after implementing a new data analytics solution. That article observes

Several structural shifts have changed how source code security is approached. Software teams now deploy continuously, build on cloud-native architectures, and often depend on third-party and open-source components. As a result, security vulnerabilities propagate faster and across wider blast radii. Security expectations have shifted as well. Customers assess vendors not only on features but also on how

Let me tell you about the TLS termination system I built. We needed to support custom domains at scale, which meant HAProxy handling thousands of certificates and terminating TLS for high-traffic services. The old playbook was simple: decrypt at the load balancer, send HTTP to your app servers, call it a day. But that plaintext

Why IAM Alone Is No Longer Sufficient for Cloud Security Organizations now process and move data differently because of modern, cloud-native platforms. Workloads such as Spark jobs, Kafka streams, Snowflake queries, and ML pipelines run continuously in short-lived environments. IAM systems are still important, but they were primarily built to secure the control plane and