Systems | Development | Analytics | API | Testing

Securely Connecting Internal Services to WSO2 Bijira with Tailscale

Enterprises often host their backend services within private internal networks, whether in on-premises data centers or restricted cloud environments. This setup is essential for protecting sensitive data, meeting compliance requirements, and reducing exposure to external threats. But it also introduces a major hurdle: how do you let external consumers and partners access the right APIs without opening unnecessary doors into your private infrastructure?

Strengthen Security With TLS 1.3 for Confluent Cloud Clusters

Security standards continue to evolve, and organizations need infrastructure that evolves along with them. TLS 1.3 brings stronger encryption to streaming infrastructure for data in transit while ensuring alignment with strict security and compliance requirements. We’re excited to announce that TLS 1.3 is currently available as an opt-in feature on Confluent Cloud Dedicated clusters and all other Confluent Cloud APIs, including Stream Governance, Metrics, and Control Plane.

Best Penetration Testing Companies in the U.S.(2025 Guide)

‍ Cyberattacks aren’t slowing down; they’re only getting smarter. With AI-driven cyber threats on the rise, organizations can no longer rely on reactive defenses. Proactive security measures like penetration testing have shifted from a “nice-to-have” to an absolute necessity for safeguarding business-critical applications, sensitive data, and brand reputation.

Static Data Masking for Snowflake Tutorial with Perforce Delphix

Learn how Delphix simplifies data masking for Snowflake to protect sensitive data while maintaining its usability for analytics and AI. This demo explains why masking is critical for security and compliance, especially when managing large-scale data in the cloud.

Simulating Multi-Agent Workflows to Find Hidden API Vulnerabilities

API gateways are often viewed as the centralized entry point for client HTTP requests in a distributed system. They act as intermediaries between clients and backend services, managing API request routing, load balancing, rate limiting, access control, and traffic shaping across multiple backend services. This API management is vital for many services and products, but many organizations can put too much stock in it.

Configuring Data Loss Prevention

Redacting PII (DLP): Speedscale can be configured to redact personally identifiable (PII) or other sensitive information (PII) from traffic via it's data loss prevention (DLP) features. This redaction happens before data leaves your network, preventing the Speedscale service from seeing the data at all. However, the overall shape or structure of the data is retained in order to facilitate useful testing against systems.

MCP Tutorial: Build a Secure REST API & Dashboard in 5 Minutes | DreamFactory + Claude

In this 5-minute demo, we use DreamFactory’s MCP server with Claude Code and Claude Desktop to: This isn’t AI writing SQL. This is AI orchestrating secure APIs—fast, safe, and auditable. DreamFactory MCP is the secure API gateway that turns databases into AI-ready endpoints—with RBAC, parameterization, and audit logging built-in.

API Management as a Central Security Hub

While many organizations mistakenly believe a single tool can solve all their API security woes, the truth is far more complex. This blog post will dismantle the myth of the "silver bullet" and demonstrate how a comprehensive, defense-in-depth strategy, centered around a robust API management platform, is essential for truly securing your API ecosystem.

How to Choose a UK Pen Testing Company (A Practical Buyer's Guide)

Choosing a penetration testing partner in the UK means inviting specialists to probe systems that support customers, revenue, and reputation. The right choice delivers clear risk reduction and developer-ready fixes. The wrong pentesting company hands you a PDF that gathers dust or even causes damage to your systems. This guide explains how to shortlist well, with a focus on scope, assurance, methodology, reporting, team quality, data handling, pricing, timelines, and the extras that matter in UK public and regulated sectors.

Zero-Trust for LLMs: Applying Security Principles to AI Systems

Zero-trust security ensures you verify every interaction, whether it’s a user, system, or API, before granting access. For large language models (LLMs), this approach is vital to prevent data breaches and maintain control over sensitive information. Here’s how zero-trust principles apply to LLMs: Identity Verification: Use multi-factor authentication (MFA) for users and secure API keys for systems. Regularly review and update permissions.