RUSTSEC-2025-0115 tandem_http_server is unmaintained

The tandem crates in https://github.com/sine-fdn are no longer maintained by the SINE Foundation. The repository has been archived. Recommended alternative We are continuing our work on SMPC by implementing our secure multi-party computation engine Polytune...

tandem_http_server is unmaintained

The tandem crates in https://github.com/sine-fdn are no longer maintained by the SINE Foundation. The repository has been archived. Recommended alternative We are continuing our work on SMPC by implementing our secure multi-party computation engine Polytune...

EUVD-2024-0829

Malicious code in bioql PyPI...

EUVD-2024-0169

Malicious code in bioql PyPI...

EUVD-2024-0170

Malicious code in bioql PyPI...

EUVD-2024-0168

Malicious code in bioql PyPI...

EUVD-2023-0256

Malicious code in bioql PyPI...

EUVD-2024-0813

Malicious code in bioql PyPI...

EUVD-2024-0171

Malicious code in bioql PyPI...

A Survey on Privacy-Preserving Computing in the Automotive Domain

As vehicles become increasingly connected and autonomous, they accumulate and manage various personal data, thereby presenting a key challenge in preserving privacy during data sharing and processing. This survey reviews applications of Secure Multi-Party Computation MPC and Homomorphic Encryptio...

CVE-2025-43863 vantage6 lacks brute-force protection on change password functionality

vantage6 is an open source framework built to enable, manage and deploy privacy enhancing technologies like Federated Learning and Multi-Party Computation. If attacker gets access to an authenticated session, they can try to brute-force the user password by using the change password functionality...

CVE-2025-43863 vantage6 lacks brute-force protection on change password functionality

vantage6 is an open source framework built to enable, manage and deploy privacy enhancing technologies like Federated Learning and Multi-Party Computation. If attacker gets access to an authenticated session, they can try to brute-force the user password by using the change password functionality...

Commitment Schemes for Multi-Party Computation

The paper presents an analysis of Commitment Schemes CSs used in Multi-Party Computation MPC protocols. While the individual properties of CSs and the guarantees offered by MPC have been widely studied in isolation, their interrelation in concrete protocols and applications remains mostly...

CVE-2024-21671

The vantage6 technology enables to manage and deploy privacy enhancing technologies like Federated Learning FL and Multi-Party Computation MPC. It is possible to find out usernames from the response time of login requests. This could aid attackers in credential attacks. Version 4.2.0 patches this...

CVE-2024-22193

The vantage6 technology enables to manage and deploy privacy enhancing technologies like Federated Learning FL and Multi-Party Computation MPC. There are no checks on whether the input is encrypted if a task is created in an encrypted collaboration. Therefore, a user may accidentally create a tas...

CVE-2024-24770

vantage6 is an open source framework built to enable, manage and deploy privacy enhancing technologies like Federated Learning and Multi-Party Computation. Much like GHSA-45gq-q4xh-cp53, it is possible to find which usernames exist in vantage6 by calling the API routes /recover/lost and /2fa/lost...

Privacy-Preserving Runtime Verification

Runtime verification offers scalable solutions to improve the safety and reliability of systems. However, systems that require verification or monitoring by a third party to ensure compliance with a specification might contain sensitive information, causing privacy concerns when usual runtime...

SAFE-SiP: Secure Authentication Framework for System-In-Package Using Multi-Party Computation

The emergence of chiplet-based heterogeneous integration is transforming the semiconductor, AI, and high-performance computing industries by enabling modular designs and improved scalability. However, assembling chiplets from multiple vendors after fabrication introduces a complex supply chain th...

Federated One-Shot Learning with Data Privacy and Objective-Hiding

Privacy in federated learning is crucial, encompassing two key aspects: safeguarding the privacy of clients' data and maintaining the privacy of the federator's objective from the clients. While the first aspect has been extensively studied, the second has received much less attention. We present...

CVE-2024-21649

The vantage6 technology enables to manage and deploy privacy enhancing technologies like Federated Learning FL and Multi-Party Computation MPC. Prior to 4.2.0, authenticated users could inject code into algorithm environment variables, resulting in remote code execution. This vulnerability is...