Security, Privacy, and Ethical Risks in OpenClaw

This paper systematically investigates the security, privacy, and ethical risks, as well as the traceability challenges of OpenClaw, a locally executable AI agent system for natural language interaction and real-world task completion. While OpenClaw shows strong potential for personal assistance,...

OpenClaw 安全漏洞

OpenClaw is an open-source intelligent artificial assistant developed by OpenClaw. Versions of OpenClaw prior to 2026.3.28 contained security vulnerabilities. These vulnerabilities stemmed from an authorization bypass in the chat.send gateway method. This allowed authenticated operator clients to...

NetSecBed: A Container-Native Testbed for Reproducible Cybersecurity Experimentation

Cybersecurity research increasingly depends on reproducible evidence, such as traffic traces, logs, and labeled datasets, yet most public datasets remain static and offer limited support for controlled re-execution and traceability, especially in heterogeneous multi-protocol environments. This...

CVE-2025-52644

HCL AION is affected by a vulnerability where certain user actions are not adequately audited or logged. The absence of proper auditing mechanisms may reduce traceability of user activities and could potentially impact monitoring, accountability, or incident investigation processes...

Unspecified Vulnerability in HCL AION (CNVD-2026-15151)

HCL AION is an AI lifecycle management platform from HCL India. HCL AION has a security vulnerability that can be exploited by attackers to affect the traceability of user activities...

EUVD-2025-208737

HCL AION is affected by a vulnerability where certain user actions are not adequately audited or logged. The absence of proper auditing mechanisms may reduce traceability of user activities and could potentially impact monitoring, accountability, or incident investigation processes...

CVE-2025-52644

HCL AION is affected by a vulnerability where certain user actions are not adequately audited or logged. The absence of proper auditing mechanisms may reduce traceability of user activities and could potentially impact monitoring, accountability, or incident investigation processes...

CVE-2025-52644 HCL AION is affected by a vulnerability where certain user actions are not adequately audited or logged.

HCL AION is affected by a vulnerability where certain user actions are not adequately audited or logged. The absence of proper auditing mechanisms may reduce traceability of user activities and could potentially impact monitoring, accountability, or incident investigation processes...

CVE-2025-52644 HCL AION is affected by a vulnerability where certain user actions are not adequately audited or logged.

HCL AION is affected by a vulnerability where certain user actions are not adequately audited or logged. The absence of proper auditing mechanisms may reduce traceability of user activities and could potentially impact monitoring, accountability, or incident investigation processes...

CVE-2025-52644

HCL AION is affected by a vulnerability where certain user actions are not adequately audited or logged. The absence of proper auditing mechanisms may reduce traceability of user activities and could potentially impact monitoring, accountability, or incident investigation processes...

CVE-2025-52644

Technical details about CVE-2025-52644 are not publicly provided in the supplied documents. Monitor for updates from vendors and security advisories.

PT-2026-25749

HCL AION is affected by a vulnerability where certain user actions are not adequately audited or logged. The absence of proper auditing mechanisms may reduce traceability of user activities and could potentially impact monitoring, accountability, or incident investigation processes...

HCL AION 安全漏洞

HCL AION is an AI lifecycle management platform from HCL India. HCL AION has a security vulnerability that can be exploited by attackers to affect the traceability of user activities...

Evaluating the Reliability of Digital Forensic Evidence Discovered by Large Language Model: A Case Study

The growing reliance on AI-identified digital evidence raises significant concerns about its reliability, particularly as large language models LLMs are increasingly integrated into forensic investigations. This paper proposes a structured framework that automates forensic artifact extraction,...

Large Language Models As a (Bad) Security Norm in the Context of Regulation and Compliance

The use of Large Language Models LLM by providers of cybersecurity and digital infrastructures of all kinds is an ongoing development. It is suggested and on an experimental basis used to write the code for the systems, and potentially fed with sensitive data or what would otherwise be considered...

The Foundation Modern AppSec Is Still Missing: Code to Cloud, Rebuilt the Right Way

See every risk, from the first line of code to what’s running in production. No resource tagging. No CI/CD hacks. Just automatic, reliable traceability both developers and security teams can act on...

EUVD-2024-42170

Malicious code in bioql PyPI...

EUVD-2023-49452

Malicious code in bioql PyPI...

FakeSound2: a Benchmark for Explainable and Generalizable Deepfake Sound Detection

The rapid development of generative audio raises ethical and security concerns stemming from forged data, making deepfake sound detection an important safeguard against the malicious use of such technologies. Although prior studies have explored this task, existing methods largely focus on binary...

VehiclePassport: a GAIA-X-Aligned, Blockchain-Anchored Privacy-Preserving, Zero-Knowledge Digital Passport for Smart Vehicles

Modern vehicles accumulate fragmented lifecycle records across OEMs, owners, and service centers that are difficult to verify and prone to fraud. We propose VehiclePassport, a GAIA-X-aligned digital passport anchored on blockchain with zero-knowledge proofs ZKPs for privacy-preserving verificatio...