The Open Source Security Foundation (OpenSSF) marked a strong presence at two cornerstone cybersecurity events, Black Hat USA 2025 and DEF CON 33, engaging with security leaders, showcasing our initiatives, and fostering collaboration to advance open source security.
The AI wave is here, and it’s only getting bigger. According to a recent report from McKinsey, “over the next three years, 92 percent of companies plan to increase their AI investments.” As this AI wave washes over almost every industry and is integrated deeply and extensively into critical and non-critical operations, it ushers in…
The Open Source Security Foundation (OpenSSF) serves as the global hub for collaborative work on securing the software supply chain. Whether you’re an open-source maintainer, a security engineer, a student, or someone passionate about public digital infrastructure, OpenSSF invites you to participate. There are no gatekeepers, no matter where you work. This community is open,…
By Sarah Evans and Andrey Shorov The world of technology is constantly evolving, and with the rise of Artificial Intelligence (AI) and Machine Learning (ML), the demand for robust security...
August 2025 marks five years since the official formation of the Open Source Security Foundation (OpenSSF). Born out of a critical need to secure the software supply chains and open...
Earlier this summer, Eman Abu Ishgair had the privilege of attending the Open Source Summit North America 2025 in Denver — one of the largest gatherings of open source contributors, maintainers, researchers, and advocates. Even more exciting: I participated as a speaker, volunteer, and a new community member during the OpenSSF Community Day, the co-located…
Welcome to the July 2025 edition of the OpenSSF Newsletter! Here’s a roundup of the latest developments, key events, and upcoming opportunities in the Open Source Security community. TL;DR: Call...
As machine learning (ML) evolves at lightning speed, so do the threats. The rise of large models like LLMs has accelerated innovation—but also introduced serious vulnerabilities. Data poisoning, model tampering, and unverifiable origins are not theoretical—they’re real risks that impact the entire ML supply chain.
