secretflow

简体中文｜English SecretFlow is a unified framework for privacy-preserving data intelligence and machine learning. To achieve this goal, it provides: An abstract device layer consists of plain devices and secret devices which encapsulate various cryptographic protocols. A device flow layer modeling...

Dark-Moon

DarkMoon Open-source autonomous AI penetration testing — finds, exploits and qualifies every vulnerability on your own infrastructure ⭐ Star DarkMoon · 🚀 Quick Start · 🧩 Integrations · 📊 Benchmark · 🔒 Darkmoon Pro · ▶️ Install & Run OSS · ▶️ Demo Pro DarkMoon is autonomous AI penetration testing...

Mandating-Honeypots-Project

Mandating-Honeypots-Project As laws like the Parents Decide Act H.R.8250 and California's Digital Age Assurance Act Assembly Bill 1043 move through legislative bodies, privacy, anonymity, and data security becomes laden with systemic threats and new security architecture with unexamined attack...

secretflow

简体中文｜English SecretFlow es un marco unificado para la inteligencia de datos y el aprendizaje automático con preservación de la privacidad. Para lograr este objetivo, proporciona: Una capa abstracta de dispositivos que consta de dispositivos simples y dispositivos secretos que encapsulan varios...

CorrectGuard: Eyes-Off Correctness Estimation for Black-Box Security Guardrails

AI services increasingly rely on black-box security guardrails, yet privacy-preserving model auditing regimes often cannot measure how well these systems perform in both a human eyes-off production setting, which disallows human inspection of user input, and a machine eyes-off setting, which...

Link Inference Attack on Privacy-Preserving Knowledge Graphs

Knowledge Graphs KGs are widely used to store and share structured information across sensitive domains such as healthcare, fi- nance, and social networks. A common privacy practice is to delete sen- sitive relations before publishing the graph, under the assumption that removing edges is...

PrivCert: Certifying Statement Support under Differential Privacy

Differentially private DP text generation can protect individual records, but privacy alone does not specify what evidence a released statement carries about the underlying data. We identify this as an evidence gap: a private report may contain plausible claims without indicating whether they are...

Conformal Prediction for Offensive Security

Despite its introduction more than a quarter century ago, Conformal Prediction CP has seen surprisingly few applications to the cyber security world thus far. In particular, we observe that, while CP has been employed as a defensive measure in many recent works, its use for carrying out attacks...

Federated Learning and LLM-Driven Threat Intelligence for Zero Trust IoT Architecture

While the Internet of Things IoT has become essential, they introduced serious security and privacy challenges, especially for mission-critical environments. Legacy devices are vulnerable to viruses, data breaches, and unauthorized access, and updating these devices would be infeasibly costly. As...

ARENA: An Architecture for Measuring the Transferability of Autonomous Cyber Defense

Operational evidence is not automatically scientific evidence. The most realistic Security Operations Center SOC data is production telemetry, yet it remains scientifically inaccessible because raw logs cannot be released; as a result, research relies on synthetic or dated datasets. We treat the...

CVE-2026-54533

vantage6 is an open-source infrastructure for privacy preserving analysis. Prior to version 5.0.0, malicious algorithms can potentially access other algorithms input and output files. Version 5.0.0 fixes the issue. As a workaround, verify and restrict the algorithm containers that are allowed to...

CVE-2024-27928

vantage6 is an open-source infrastructure for privacy preserving analysis. Prior to version 5.0.0, if an attacker hacks into a vantage6 user's email account, they can 1 reset the password via email and then 2 reset the 2FA token via email. This way they reduce 2FA to 1FA email access. Note that...

CVE-2026-54533

vantage6 node (open-source infrastructure for privacy-preserving analysis) contains an Improper Access Control vulnerability prior to version 5.0.0 that could allow malicious algorithms to access other algorithms’ input and output files. Version 5.0.0 fixes the issue. As a workaround, verify and ...

EUVD-2026-37825

vantage6 is an open-source infrastructure for privacy preserving analysis. Prior to version 5.0.0, malicious algorithms can potentially access other algorithms input and output files. Version 5.0.0 fixes the issue. As a workaround, verify and restrict the algorithm containers that are allowed to...

EUVD-2024-55640

vantage6 is an open-source infrastructure for privacy preserving analysis. Prior to version 5.0.0, users can reset their MFA token via API routes that send them an email. Currently the number of emails that is sent is not limited. This gives attackers the option to flood someones mailbox with a l...

CVE-2026-54533: Improper Access Control

vantage6 is an open-source infrastructure for privacy preserving analysis. Prior to version 5.0.0, malicious algorithms can potentially access other algorithms input and output files. Version 5.0.0 fixes the issue. As a workaround, verify and restrict the algorithm containers that are allowed to...

PT-2026-50570

Name of the Vulnerable Software and Affected Versions vantage6 versions prior to 5.0.0 Description Malicious algorithms can potentially access input and output files belonging to other algorithms. Recommendations Update to version 5.0.0. As a temporary workaround, verify and restrict the algorith...

CyberMaskQA: A Privacy-Aware Benchmark for Evaluating Large Language Models in Cybersecurity Question Answering

Large language models LLMs are increasingly applied to cybersecurity question answering QA for critical tasks such as incident response and vulnerability analysis. However, real-world operational contexts, including system logs and network configurations, inherently contain sensitive identifiers,...

XAI FL-IDS: A Federated Learning and SHAP-Based Explainable Framework for Distributed Intrusion Detection Systems

An Intrusion Detection System IDS is vital in cybersecurity, detecting unauthorized activity across networks. With attacks on network layers increasing, stronger IDSs are needed. Yet most IDSs rely on centralized detection, forcing IoT nodes to ship data to a server, adding overhead and offering ...

AoI-Guided Client Selection for Robust and Timely Federated Intrusion Detection in Cloud-Edge Security Analytics

Federated learning FL is attractive for cloud-edge intrusion detection because it enables collaborative training over distributed telemetry without centralizing raw logs. In production security analytics pipelines, however, only a subset of clients participates in each round, and heterogeneous...