Systems | Development | Analytics | API | Testing

With the relative newness of the iPaaS (Integration Platform as a Service) vertical, no single platform has emerged as the de facto choice for enterprises. This can present a challenge if you're trying to choose among the large pool of solutions available – especially when certain solutions labeled "iPaaS" serve very different use-cases.

Hybrid AI systems need secure ways to manage user identities across cloud and on-premises environments. Identity passthrough ensures that AI systems operate under the permissions of the actual user, not a shared service account. This approach reduces risks tied to credential theft, improves auditability, and supports compliance with regulations like GDPR and HIPAA. Key methods for identity passthrough include: Quick Takeaway: For organizations prioritizing simplicity, PHS is a good starting point.

APIs are bits of software that act as interpreters for two different programs. They'll connect to each service via endpoints and relay messages back and forth, doing the work of software integration for you. DreamFactory is a secure, self-hosted enterprise data access platform that provides governed API access to any data source, connecting enterprise applications and on-prem LLMs with role-based access and identity passthrough. But how does this actually look in the real world?

The Model Context Protocol (MCP) is quickly becoming the standard for how large language models connect to enterprise data. As adoption accelerates, engineering teams face a foundational decision: build a custom MCP server from scratch, or adopt an AI data gateway that ships with MCP support, security, and governance out of the box. Both paths have real tradeoffs. This post breaks them down so you can make the right call for your stack, your team, and your risk profile.

Audit logs are essential for making AI systems accountable, reliable, and compliant with regulations. They act as a record-keeping system, documenting every critical interaction within an AI system, such as user prompts, model decisions, and policy enforcement. Here's why they are crucial: Audit logs are not just a legal requirement - they are a key part of managing AI systems effectively and minimizing risks.

APIs are transforming how AI interacts with enterprise data. Instead of directly connecting AI to databases like MySQL, PostgreSQL, or MongoDB - which can lead to security risks, schema complexities, and high maintenance - APIs act as a secure middle layer. This approach simplifies data access, reduces risks, and ensures seamless integration with multiple databases.

On March 31, Axios—the most widely used HTTP client in the JavaScript ecosystem, with approximately 100 million weekly npm downloads and a presence in roughly 80% of cloud environments—was compromised via a hijacked maintainer account. Two malicious versions (1.14.1 and 0.30.4) delivered a cross-platform remote access trojan (RAT) that harvested credentials, SSH keys, cloud tokens, and API secrets from every machine where they were installed.

On March 31, an attacker hijacked the npm account of Axios’s primary maintainer and published two malicious versions of the most popular HTTP client library in the JavaScript ecosystem. The backdoored packages—axios@1.14.1 and axios@0.30.4—injected a trojanized dependency that delivered cross-platform remote access trojans to macOS, Windows, and Linux machines within seconds of installation.

Between March 19 and March 31, five major open-source projects were compromised in rapid succession: Aqua Security’s Trivy vulnerability scanner, Checkmarx’s AST GitHub Actions, the LiteLLM AI proxy on PyPI, the Telnyx communications library, and Axios—the most downloaded HTTP client in the npm registry. Collectively, these projects serve hundreds of millions of installations across virtually every enterprise software environment on earth.