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OpenSSF Welcomes New Members and Expands AI Security Resources

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Broadened AI security guidance, relationships, and research to help close the gap between AI-driven development and software security

SALT LAKE CITY, Nov. 9, 2026 /PRNewswire/ — The Open Source Security Foundation (OpenSSF), a cross-industry initiative of the Linux Foundation focused on sustainably securing open source software, today announced new membership growth, welcoming Beautiful Majestic Dolphin, DevGuard, and UElement Technologies to the foundation. The OpenSSF also notes new and expanded efforts to help organizations secure software in the age of AI, including membership with the Multi-Organization Secure AI Coordination (MOSAIC) for better AI security, a new guide to finding and fixing vulnerabilities using AI, and new research on AI’s impact on software security.

“Security must keep pace with this new software development lifecycle.”

AI is redefining the Software Development Life Cycle (SDLC). It impacts both the rate at which code is produced and how quickly vulnerabilities are discovered and reported – for attackers and defenders alike. With bugs easier to find and reporting windows shrinking under regulations like the EU Cyber Resilience Act (CRA), organizations need clear, practical guidance on using AI to secure software. OpenSSF continues to serve as a trusted, neutral hub for AI security education, collaboration, and open source software security.

“Security must keep pace with this new software development lifecycle,” said Laura Guazzelli, Security Architect for AI/ML/LLM/Agentic Systems at OpenSSF. “This new SDLC has collapsed the window between bug discovery and automated attack, exposing defenses that are unprepared for AI-driven threats and offensive campaigns. This is why we are focused on equipping developers with practical resources, from guidance on finding and fixing vulnerabilities with AI to new data on how AI is shaping software development.”

New OpenSSF members include Beautiful Majestic Dolphin, DevGuard, and UElement Technologies who join the Foundation as General Members. These organizations join a community of working groups, technical groups, and experts that are shaping the future of OpenSSF and software security. Their membership reinforces the long term sustainability of open source and the projects that are critical to modern infrastructure.

Q4 Foundation Achievements
In the fourth quarter of 2026, OpenSSF achieved the following milestones:

OpenSSF joins MOSAIC – Membership with MOSAIC allows OpenSSF and MOSAIC members to pool knowledge and resources for consistent standards and guidance on AI security. A major goal of the group is a standardized map of the participating initiatives, which includes aligning with other initiatives such as NIST SP 800-53 Control SC-42, building on existing frameworks, a general consensus on MOSAIC definitions, and more.State of AI Impact on Software Security and Cybersecurity 2026 report – The study, supported by OpenSSF, ActiveState and LF AI & Data Foundation, found a growing gap between the pace of AI-driven software development and organizations’ ability to secure the code being produced: 58% of surveyed teams ship code faster than security reviews can keep up, while 60% say AI coding assistants have increased the number of external packages in their codebases. This data underscores the importance of trusted, reliable guidance as AI deployment continues to grow.Secure AI Associate (SAIA) certification – OpenSSF and Linux Foundation Education are launching the Secure AI Associate (SAIA) certification. This new credential will provide learners with skills to find and fix security risks across the full AI/ML lifecycle, from training data to production pipelines. The certification launches in December 2026 and interested parties can sign up for exam availability notifications here.New guide to finding and fixing vulnerabilities using AI – The OpenSSF Best Practices and AI/ML working groups released Finding and Fixing Software Vulnerabilities Using AI: A Guide for Developers, a free guide for developers and security researchers on using AI to find and fix vulnerabilities before attackers can exploit them. Built on principles that outlast any single tool, it covers the full process, from preparing and sandboxing AI to validating, fixing, and preventing issues, and stresses that AI-generated patches should never be trusted without automated tests and human review. An online course (LFD126) is planned for the coming months.Case study: GitHub expands malware advisories across eight ecosystems – A new case study shows how GitHub integrated OpenSSF’s Malicious Packages data into its Advisory Database, expanding Dependabot malware alerts beyond npm to eight package ecosystems, including PyPI, Maven, RubyGems, NuGet, Go, crates.io, and PHP Composer. The community-driven repository now holds more than 238,000 malicious package reports, showing how shared, open data can help defenders keep pace with fast-moving supply chain attacks.Zarf 1.0 marks a major milestone for the OpenSSF – the release helps teams package and deploy software in environments disconnected from the internet. Version 1.0 strengthens package signing and verification workflows, improves configuration management, and establishes a foundation for long-term compatibility and community-driven development.

Supporting Quotes

“Scanning tells you what went wrong. Knowing where your software came from tells you whether it should have been trusted at all. ActiveState builds open source from verified source so that secure is the default, and joining the OpenSSF is a natural next step in making that true for everyone who builds on open source.”
– Abby Kearns, CEO, ActiveState

“We think that you should be able to determine why things happen. Who, what, when, where, and how? Those questions can all easily be understood, but why is one of the hardest parts of cybersecurity. That’s why we made GoRapide open source, under an MIT license. We know why we build for our customers, but ultimately we can’t know every reason why someone might ask, ‘Why?’ For us, joining the Open Source Security Foundation made sense because open source is integral to our company mission.”
– Shane Morris, CEO, Beautiful Majestic Dolphin

“We built open-source DevGuard to make secure software development the default, not the exception. We already use OpenSSF projects and data to help our users secure their entire software development lifecycle, so joining the OpenSSF feels like a natural step. We’re proud to become part of the community shaping the future of open-source security and look forward to giving back.”
– Tim Bastin, CTO, DevGuard – L3montree GmbH

“Open source is the common ground the world’s digital economy is built on and India is now one of its largest builders. Keeping that ground secure isn’t one company’s or one country’s job; it belongs to all of us. UElement joins OpenSSF to help make it trustworthy today and quantum-safe tomorrow, so the systems people depend on, from banks to public infrastructure, can be built in the open and trusted everywhere.”
– Chaitanya Vijay Ghate, Co-founder & CEO, UElement Technologies

Events and Gatherings
OpenSSF members are gathering this week in Salt Lake City at Open Source SecurityCon North America and onsite at KubeCon + CloudNativeCon North America (November 9-12). Those interested in joining OpenSSF at events in 2027 should mark their calendars for Open Source SecurityCon Europe, which is planned for March 15, 2027.

Additional Resources

View the complete list of OpenSSF membersContribute efforts to one or more of the active OpenSSF working groups and projectsSign up for the OpenSSF newsletter to receive updates on upcoming events, resources, and community news.

About the OpenSSF
The Open Source Security Foundation (OpenSSF) is a cross-industry organization at the Linux Foundation that brings together the industry’s most important open source security initiatives and the individuals and companies that support them. The OpenSSF is committed to collaboration and working both upstream and with existing communities to advance open source security for all. For more information, please visit us at openssf.org.

About the Linux Foundation 
The Linux Foundation is the world’s leading home for collaboration on open source software, hardware, standards, and data. Linux Foundation projects, including Linux, Kubernetes, Model Context Protocol (MCP), OpenChain, OpenSearch, OpenSSF, OpenStack, PyTorch, Ray, RISC-V, SPDX and Zephyr, provide the foundation for global infrastructure. The Linux Foundation is focused on leveraging best practices and addressing the needs of contributors, users, and solution providers to create sustainable models for open collaboration. For more information, please visit us at linuxfoundation.org.

The Linux Foundation has registered trademarks and uses trademarks. For a list of trademarks of The Linux Foundation, please see its trademark usage page: www.linuxfoundation.org/trademark-usage. Linux is a registered trademark of Linus Torvalds.

Media Contact
Grace Lucier
The Linux Foundation
pr@linuxfoundation.org 

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Beghou Expands Pune Office, Strengthening Data, Analytics, and AI Capabilities

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The expanded office brings together multidisciplinary teams to solve increasingly complex life sciences commercialization challenges 

PUNE, India, Nov. 11, 2026 /PRNewswire/ — Beghou, a life sciences commercialization consulting and technology company, today announced the expansion of its Pune office. Opened on October 7 to foster cross-team collaboration, the new space reflects Beghou’s growing global delivery and innovation model. The Pune office is home to consulting and product teams with expertise spanning analytics, data engineering, technology, and AI. Beghou has also expanded its offices in Hyderabad and Bengaluru this year as its workforce continues to scale. The larger Pune space makes room for that growth, along with expanded leadership opportunities, specialist capabilities, and global client exposure for teams based there. 

“There’s a real sense of momentum at Beghou right now, and it’s exciting to see that reflected in our global expansion. We’re growing across markets, expanding the capabilities we bring to clients, and investing in the people and technology behind that work,” said Adrienne Lovink, CEO, Beghou. 

Commercialization challenges rarely sit within a single discipline, and Beghou’s model is built around that reality. Teams work together to move from identifying a business question to designing, building, and implementing the solution. The new office gives them dedicated space to collaborate, share knowledge, and learn from one another. 

“It is incredibly fulfilling to see the growth of our India organization and the world-class talent and capabilities we have built over the years. I see this growth as a stepping stone to something much bigger – not just scaling, but driving innovation, developing differentiated offerings, and solving increasingly complex commercialization challenges for our clients. Our new office reflects this ambition, bringing together diverse expertise and creating more opportunities for our teams to collaborate, innovate, and build meaningful solutions,” said Sonam Dubey, India Head, Beghou. 

The office is also a key hub for Beghou’s AI and product innovation, with teams working to embed AI in the solutions clients use across planning, analysis, and execution. They are also helping to develop new products that pair Beghou’s commercialization expertise with modern data capabilities. 

“We are at an exciting point in Beghou’s journey. I see this office as a melting pot of deep commercial expertise, technology, product thinking, and AI, the capabilities that will shape our next phase of growth. The opportunity is to combine those strengths to build differentiated solutions that solve real client problems and scale our impact,” said Abhigya Jain, Partner, Beghou. 

About Beghou 

Beghou drives commercialization that works for life sciences. For over 30 years, Beghou has been a long-term consulting and technology partner to more than 250 life sciences clients. We connect the dots between strategy, data, technology, and teams, helping clients accelerate launches, deepen customer engagement, and advance patient access. Whether a company is pre-commercial and building from scratch or refining an existing commercial strategy, Beghou provides fresh ideas and pragmatic, technology-enabled solutions to help organizations adapt and thrive in an increasingly complex environment. 

We build enduring partnerships by remaining engaged and accountable beyond project delivery to help ensure solutions take hold and deliver results. Combining strategic thinking, technical expertise, and hands-on execution, we help clients achieve faster outcomes and lasting impact. 

Find out more at www.beghou.com.

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TIER IV unveils end-to-end autonomous driving adaptable to map information and sensor configurations

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Multiple open-source AI models are available with Autoware

TOKYO, Nov. 11, 2026 /PRNewswire/ — TIER IV, the pioneering force behind Autoware, open-source software for autonomous driving, today announced the development and open-source release of multiple end-to-end (E2E) autonomous driving AI models that support different system requirements, including map information and sensor configurations. The models offer flexible options ranging from camera-only configurations to those incorporating LiDAR, radar and high-definition (HD) maps, enabling developers to select AI models suited to their performance requirements. Through Autoware, TIER IV provides a development environment for optimizing these models and integrating them into vehicle systems, helping automakers and technology partners develop and deploy their own autonomous driving stack.

Overview of the Autoware 2.0 Architecture

TIER IV is leading the development of Autoware 2.0, the next-generation architecture of Autoware. Autoware 2.0 is a scalable and adaptable architecture that flexibly combines AI models with conventional rule-based technologies. By supporting different AI models and sensor configurations, it enables autonomous driving systems to be built for a range of applications and system requirements. The E2E autonomous driving AI models announced today are concrete technological outcomes designed to leverage this architecture.

NVIDIA Alpamayo 2 Edge

As part of its collaboration with NVIDIA announced in March 2026 , TIER IV has been evaluating the performance of NVIDIA Alpamayo, a vision-language-action (VLA) foundation model, and integrating it with Autoware. The latest model, Alpamayo 2 Edge, is an E2E autonomous driving AI model that takes only camera images as input and uses reasoning to generate driving trajectories. With 2 billion parameters, compared with 34 billion in Alpamayo 2 Super, it is substantially smaller and offers promise for practical deployment in vehicles. TIER IV is currently optimizing the model and adapting it to real vehicles, while having completed its integration with Autoware.

GitHub (source code): https://github.com/autowarefoundation/alpamayo-autowareHugging Face (AI model): https://huggingface.co/nvidia/Alpamayo2-Edge

AutoE2E

AutoE2E, whose development is led by the Autoware Foundation (AWF) and TIER IV, is an E2E autonomous driving AI model capable of running on computing platforms beyond NVIDIA hardware. It adopts a Fast–Slow architecture combining a Reactive Model for real-time driving decisions, a World Model for predicting future changes in the surrounding environment, and a Reasoning Model that supports driving decisions. It can accommodate configurations ranging from cameras alone to those incorporating LiDAR and radar sensor data. With 79.9 million parameters, it is lighter than Alpamayo 2 Edge. The Reactive Model has been released, while development of the World Model and Reasoning Model continues, alongside consideration of commercialization for robotaxi applications. Integration of the Reactive Model with Autoware has been achieved.

GitHub (source code): https://github.com/autowarefoundation/auto_e2eHugging Face (AI model): https://huggingface.co/AutowareFoundation/auto_e2e

METEOR

Developed independently by TIER IV, METEOR is a lightweight, multitask E2E autonomous driving AI model primarily intended for privately owned passenger vehicles. Built on a convolutional neural network (CNN) architecture, it uses a bird’s-eye-view (BEV) representation to perform everything from perception of the surrounding environment to driving trajectory generation within a single neural network, without relying on high-definition maps. It supports configurations using images from one to eight cameras and can also incorporate LiDAR and radar sensor data. With 16 million parameters, it is even lighter than AutoE2E and supports operation across different semiconductor platforms, including NVIDIA and Renesas. TIER IV also uses CoMET, the automated labeling platform within Co-MLOps, together with agentic AI to automate data labeling and model training, evaluation, and improvement, eliminating the need for manual coding and labeling. Automakers and component suppliers can optimize the open-source model to meet their own vehicle specifications and performance requirements.

GitHub (source code): https://github.com/tier4/METEORHugging Face (AI model): https://huggingface.co/AutowareFoundation/meteor

OnePlanner

OnePlanner is an E2E autonomous driving AI model that integrates perception of the surrounding environment with motion planning. It currently uses BEVFusion, which generates a BEV representation from LiDAR point-cloud data, with a planned transition to PTv3. Its flexible architecture allows the perception model to be replaced while directly using features extracted during perception for motion planning. Conventional autonomous driving systems convert perception results into information such as object positions and velocities before passing them to the planner. OnePlanner reduces these intermediate conversions, enabling richer use of information about the surrounding environment. It also incorporates HD maps, route information, traffic-signal states, and vehicle motion states to generate driving trajectories for the next six seconds. Integration with Autoware has been achieved.

GitHub (source code): https://github.com/autowarefoundation/autoware_oneplannerHugging Face (AI model): https://huggingface.co/AutowareFoundation/oneplanner

LatentDrive

LatentDrive is an E2E autonomous driving AI model that uses a world model to integrate predictions of the surrounding environment with motion planning. Using V-JEPA, a self-supervised learning approach, it represents features of the surrounding environment extracted from camera video in a latent space and uses these features to generate vehicle trajectories. Its distinguishing feature is that it directly leverages information from video for motion planning without intermediate processes such as object detection and tracking. It does not require HD maps and generates trajectories for the next four seconds using camera video, route information, and vehicle motion states. It supports configurations with either one or three cameras, and work is underway on integration with Autoware and validation in an in-vehicle environment.

GitHub (source code): https://github.com/autowarefoundation/autoware_latent_driveHugging Face (AI model): https://huggingface.co/AutowareFoundation/latent_drive

“Advances in E2E autonomous driving are fundamentally changing how autonomous driving systems are developed.” said Shinpei Kato, founder and CEO of TIER IV. “For automakers and component suppliers to incorporate AI technology into their own products, however, it is essential that they be able to internalize technologies according to their applications and performance requirements, without depending on a particular AI model or semiconductor platform. By releasing multiple AI models developed under the leadership of TIER IV and the Autoware Foundation, alongside the results of our collaboration with NVIDIA, we have significantly expanded those choices. We will continue to advance the open-source ecosystem centered on Autoware and work with partners around the world to democratize autonomous driving.”

“Advancing autonomous driving requires AI that can reason through complex situations and run efficiently in the car.” said Ali Kani, vice president of automotive at NVIDIA. “TIER IV’s integration of NVIDIA Alpamayo 2 Edge with Autoware gives developers an open foundation to bring that intelligence from research into their own vehicles.”

“The advancement of autonomous driving technology depends on an ecosystem in which diverse AI models can be developed and evaluated openly, then applied according to their respective use cases.” said Muhammad Zain Khawaja, President of the Autoware Foundation. “The AI models released today are an important demonstration of how Autoware is evolving into a flexible development platform that is not tied to any particular technology or hardware. We welcome TIER IV’s continued technology development and its collaboration with partners including NVIDIA. The Autoware Foundation will continue working with the global open-source community to make advanced autonomous driving technology accessible to everyone.”

Next Steps

TIER IV will continue improving the performance of the AI models released today and optimizing them for in-vehicle environments, while promoting the development and commercialization of E2E autonomous driving technology by automakers and partners through Autoware. TIER IV will also strengthen collaboration with the global open-source community and work to expand the adoption of autonomous driving systems across diverse vehicle types and applications.

About TIER IV

TIER IV stands at the forefront of deep tech innovation, pioneering Autoware, open-source software for autonomous driving. With a comprehensive suite of platforms and services built around Autoware, TIER IV provides everything from software development and vehicle procurement to operational support. Through the Autoware ecosystem, TIER IV works with partners worldwide to shape the future of intelligent vehicles with open-source software, aiming to create mobility that is safer, more sustainable, and accessible to all.

The word marks and logos of TIER IV are trademarks or registered trademarks of TIER IV, Inc. in Japan and other countries. All other company names, product names, service names, and logos referenced herein are trademarks or registered trademarks of their respective owners.

Autoware is a registered trademark of the Autoware Foundation.

Media contact
pr@tier4.jp 

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Dingdong to Report Third Quarter 2026 Financial Results on November 12, 2026

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SHANGHAI, Nov. 10, 2026 /PRNewswire/ — Dingdong (Cayman) Limited (“Dingdong” or the “Company”) (NYSE: DDL), a leading fresh grocery e-commerce company in China, with advanced supply chain capabilities, today announced that it will report its unaudited financial results for the third quarter ended September 30, 2026, before U.S. markets open on November 12, 2026.

About Dingdong (Cayman) Limited

Dingdong is the leading fresh grocery e-commerce company in mainland China, with sustainable long-term growth. The Company directly provides users and households with fresh groceries, prepared food, and other food products through delivering a convenient and excellent shopping experience supported by an extensive self-operated frontline fulfillment grid. Leveraging its deep insights into consumers’ evolving needs and its strong food innovation capabilities, Dingdong has successfully launched a series of private label products spanning a variety of food categories. Many of Dingdong’s private label products are produced at its own production plants, allowing it to more efficiently produce and offer safe and high-quality food products. Dingdong aims to be the first choice for fresh and food shopping.

For more information, please visit: https://ir.100.me.

 

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