NVIDIA FLARE SDK 输入验证错误漏洞

NVIDIA FLARE SDK is a federal learning application development toolkit provided by NVIDIA Corporation in the United States. The NVIDIA Flare SDK has a vulnerability related to input validation errors. This vulnerability stems from path traversal, which leads to improper input validation,...

Scalable and Verifiable Federated Learning for Cross-Institution Financial Fraud Detection

The global financial ecosystem confronts a critical asymmetry: while fraud syndicates operate as borderless, distributed networks, banking institutions remain constrained by regulatory data silos, limiting visibility into cross-institutional threat patterns under strict privacy laws such as GDPR...

IBM DB2 Federated Server DoS (7269435) (Unix)

According to its self-reported version number, IBM Db2 is affected by a denial of service vulnerability: - IBM Db2 for Linux, UNIX and Windows includes DB2 Connect Server could allow an authenticated user to cause a denial of service due to improper neutralization of special elements in the data...

DP-FlogTinyLLM: Differentially Private Federated Log Anomaly Detection Using Tiny LLMs

Modern distributed systems generate massive volumes of log data that are critical for detecting anomalies and cyber threats. However, in real world settings, these logs are often distributed across multiple organizations and cannot be centralized due to privacy and security constraints. Existing...

Security Bulletin: IBM® Db2® Federated server is vulnerable to a denial of service with a specially crafted query in a Fenced environment (CVE-2026-3676)

Summary IBM® Db2® Federated server is vulnerable to a denial of service with a specially crafted query in a Fenced environment CVE-2026-3676 Vulnerability Details CVEID:CVE-2026-3676 DESCRIPTION: IBM Db2 for Linux, UNIX and Windows includes DB2 Connect Server could allow an authenticated user to...

Evaluating Differential Privacy against Membership Inference in Federated Learning: Insights from the NIST Genomics Red Team Challenge

While Federated Learning FL mitigates direct data exposure, the resulting trained models remain susceptible to membership inference attacks MIAs. This paper presents an empirical evaluation of Differential Privacy DP as a defense mechanism against MIAs in FL, leveraging the environment of the 202...

CVE-2026-34148 Fedify affected by resource exhaustion caused by unbounded redirect following during remote key/document resolution

Fedify is a TypeScript library for building federated server apps powered by ActivityPub. Prior to 1.9.6, 1.10.5, 2.0.8, and 2.1.1, @fedify/fedify follows HTTP redirects recursively in its remote document loader and authenticated document loader without enforcing a maximum redirect count or...

Digital Privacy in IoT: Exploring Challenges, Approaches and Open Issues

Privacy has always been a critical issue in the digital era, particularly with the increasing use of Internet of Things IoT devices. As the IoT continues to transform industries such as healthcare, smart cities, and home automation, it has also introduced serious challenges regarding the security...

Deserialization of Untrusted Data

Overview fedml is an A research and production integrated edge-cloud library for federated/distributed machine learning at anywhere at any scale. Affected versions of this package are vulnerable to Deserialization of Untrusted Data via the sendMessage function in grpcserver.py. An attacker can...

FEDML 路径遍历漏洞

FEDML is a unified and scalable machine learning training and deployment library open sourced by TensorOpera. Versions of FEDML 0.8.9 and earlier contained a path traversal vulnerability. This vulnerability stemmed from incorrect handling of the parameter dataSet, which could lead to path travers...

The vulnerability of the FedCM component in the Google Chrome browser allows a hacker to execute arbitrary code.

The vulnerability of the FedCM component’s Google Chrome browser component is related to the use of memory after deallocation. Exploiting this vulnerability could allow a remote attacker to execute arbitrary code using a specially created HTML page...

CVE-2026-33879

Federated Learning and Interoperability Platform FLIP is an open-source platform for federated training and evaluation of medical imaging AI models across healthcare institutions. The FLIP login page in versions 0.1.1 and prior has no rate limiting or CAPTCHA, enabling brute-force and...

CVE-2026-33879

Federated Learning and Interoperability Platform FLIP is an open-source platform for federated training and evaluation of medical imaging AI models across healthcare institutions. The FLIP login page in versions 0.1.1 and prior has no rate limiting or CAPTCHA, enabling brute-force and...

CVE-2026-33879

Federated Learning and Interoperability Platform FLIP is an open-source platform for federated training and evaluation of medical imaging AI models across healthcare institutions. The FLIP login page in versions 0.1.1 and prior has no rate limiting or CAPTCHA, enabling brute-force and...

CVE-2026-33879 FLIP doesn't have rate limiting or brute-force protection on login

Federated Learning and Interoperability Platform FLIP is an open-source platform for federated training and evaluation of medical imaging AI models across healthcare institutions. The FLIP login page in versions 0.1.1 and prior has no rate limiting or CAPTCHA, enabling brute-force and...

EUVD-2026-16818

Federated Learning and Interoperability Platform FLIP is an open-source platform for federated training and evaluation of medical imaging AI models across healthcare institutions. The FLIP login page in versions 0.1.1 and prior has no rate limiting or CAPTCHA, enabling brute-force and...

CVE-2026-33879

CVE-2026-33879 affects the Federated Learning and Interoperability Platform (FLIP). Technical details across sources show that FLIP versions prior to 0.1.1 expose the login page without rate limiting or CAPTCHA, enabling brute-force and credential-stuffing attacks. This affects external users and...

Federated Learning and Interoperability Platform 安全漏洞

Federated Learning and Interoperability Platform is an open-source medical imaging learning platform developed by the London AI Centre. Versions of the Federated Learning and Interoperability Platform FLIP prior to 0.1.1 contained security vulnerabilities. These vulnerabilities stemmed from the...

PT-2026-28547

Name of the Vulnerable Software and Affected Versions Federated Learning and Interoperability Platform FLIP versions prior to 0.1.1 Description The Federated Learning and Interoperability Platform FLIP login page lacks rate limiting or CAPTCHA protection, which could allow brute-force and...

Masters of Imitation: How Hackers and Art Forgers Perfect the Art of Deception

Unmasking impostors is something the art world has faced for decades, and there are valuable lessons from the works of Elmyr de Hory that can apply to the world of defensive cybersecurity. During the 1960s, de Hory gained infamy as a premier forger, passing off counterfeit masterworks of Picasso,...