Chainguard Joins FINOS to Advance Secure Open Source in Financial Services

May 12, 2026
Chainguard has joined the Fintech Open Source Foundation (FINOS) as a Gold Member to help strengthen software supply chain security across the financial sector as AI increases development and security challenges.

Chainguard has joined FINOS, the financial services branch of the Linux Foundation, as a Gold Member, announced in a press release. The company will work with the FINOS community to improve software supply chain security and governance while promoting secure open source adoption in the financial industry.

The collaboration focuses on addressing risks introduced by AI in software development. Open source software supports many financial systems, from digital banking to AI infrastructure, but increasing automation and AI use have expanded the volume of code and vulnerabilities entering production environments. Chainguard will contribute its expertise in secure software delivery and open source maintenance to help financial institutions build more resilient systems.

FINOS stated that Chainguard’s involvement will help translate industry-wide security principles into practical open source projects and standards. Chainguard maintains and contributes to more than 100 open source projects, including Kubernetes, Sigstore, and Tekton, and operates programs such as EmeritOSS for maintaining mature open source projects and DriftlessAF for improving infrastructure consistency.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Finance AI Weekly, Cybersecurity AI Weekly or Daily AI Brief.

Also, consider following us on social media:

AI in Finance Cybersecurity AI AI Brief AI Brief (X)
Free newsletter

Cybersecurity AI Weekly

Weekly newsletter about AI in Cybersecurity.

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.