Incorrect Authorization

Overview Affected versions of this package are vulnerable to Incorrect Authorization via the ExperimentalSettings function. An attacker can exploit this issue by accessing unauthorized settings through the System Console. Note: This is only exploitable if the RestrictSystemAdmin setting is true,...

​​How the Microsoft Secure Future Initiative brings Zero Trust to life

In this blog, you'll learn more about how the Microsoft Secure Future Initiative SFI—a real-world case study on Zero Trust—aligns with Zero Trust strategies. We’ll share key updates from the April 2025 SFI progress report and practical Zero Trust guidance to help you strengthen your organization’...

Sybil-Based Virtual Data Poisoning Attacks in Federated Learning

Federated learning is vulnerable to poisoning attacks by malicious adversaries. Existing methods often involve high costs to achieve effective attacks. To address this challenge, we propose a sybil-based virtual data poisoning attack, where a malicious client generates sybil nodes to amplify the...

On Technique Identification and Threat-Actor Attribution Using LLMs and Embedding Models

Attribution of cyber-attacks remains a complex but critical challenge for cyber defenders. Currently, manual extraction of behavioral indicators from dense forensic documentation causes significant attribution delays, especially following major incidents at the international scale. This research...

DataSentinel: a Game-Theoretic Detection of Prompt Injection Attacks

LLM-integrated applications and agents are vulnerable to prompt injection attacks, where an attacker injects prompts into their inputs to induce attacker-desired outputs. A detection method aims to determine whether a given input is contaminated by an injected prompt. However, existing detection...

Enhancing IoT Cyber Attack Detection in the Presence of Highly Imbalanced Data

Due to the rapid growth in the number of Internet of Things IoT networks, the cyber risk has increased exponentially, and therefore, we have to develop effective IDS that can work well with highly imbalanced datasets. A high rate of missed threats can be the result, as traditional machine learnin...

Defending the Edge: Representative-Attention for Mitigating Backdoor Attacks in Federated Learning

Federated learning FL enhances privacy and reduces communication cost for resource-constrained edge clients by supporting distributed model training at the edge. However, the heterogeneous nature of such devices produces diverse, non-independent, and identically distributed non-IID data, making t...

SecReEvalBench: a Multi-Turned Security Resilience Evaluation Benchmark for Large Language Models

The increasing deployment of large language models in security-sensitive domains necessitates rigorous evaluation of their resilience against adversarial prompt-based attacks. While previous benchmarks have focused on security evaluations with limited and predefined attack domains, such as...

Automating Security Audit Using Large Language Model Based Agent: an Exploration Experiment

In the current rapidly changing digital environment, businesses are under constant stress to ensure that their systems are secured. Security audits help to maintain a strong security posture by ensuring that policies are in place, controls are implemented, gaps are identified for cybersecurity...

CVE-2025-47274

ToolHive is a utility designed to simplify the deployment and management of Model Context Protocol MCP servers. Due to the ordering of code used to start an MCP server container, versions of ToolHive prior to 0.0.33 inadvertently store secrets in the run config files which are used to restart...

The vulnerability of the /goform/formTcpipSetup function in D-Link DIR-618 and DIR-605L router microprogramming software allows a hacker to execute arbitrary code.

The vulnerability of the /goform/formTcpipSetup function in D-Link DIR-618 and DIR-605L router microprogramming software is related to access control errors. Exploiting this vulnerability allows a remote attacker to execute arbitrary code...

Adversarial Suffix Filtering: a Defense Pipeline for LLMs

Large Language Models LLMs are increasingly embedded in autonomous systems and public-facing environments, yet they remain susceptible to jailbreak vulnerabilities that may undermine their security and trustworthiness. Adversarial suffixes are considered to be the current state-of-the-art...

CVE-2025-22892

Summary of CVE-2025-22892 : Uncontrolled resource consumption in Intel OpenVINO Model Server software (pre-2024.4) could allow an unauthenticated, adjacent attacker to trigger a denial of service. The issue stems from resource management weaknesses that permit excessive resource use. Affected pro...

CVE-2025-22892

Uncontrolled resource consumption for some OpenVINO™ model server software maintained by IntelR before version 2024.4 may allow an unauthenticated user to potentially enable denial of service via adjacent access...

php: libxml streams use wrong content-type header when requesting a redirected resource

A flaw was found in PHP's DOM and SimpleXML extensions. This vulnerability allows incorrect parsing of a redirected HTTP resource via improper content-type header handling...

Intel OpenVINO Model Server Software Advisory - Lenovo Support US

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Defining a new methodology for modeling and tracking compartmentalized threats

In the evolving cyberthreat landscape, Cisco Talos is witnessing a significant shift towards compartmentalized attack kill chains, where distinct stages -- such as initial compromise and subsequent exploitation -- are executed by multiple threat actors. This trend complicates traditional threat...

kernel: xdp: fix invalid wait context of page_pool_destroy()

In the Linux kernel, the following vulnerability has been resolved: xdp: fix invalid wait context of pagepooldestroy If the driver uses a page pool, it creates a page pool with pagepoolcreate. The reference count of page pool is 1 as default. A page pool will be destroyed only when a reference...

On the Interplay of Explainability, Privacy and Predictive Performance with Explanation-Assisted Model Extraction

Machine Learning as a Service MLaaS has gained important attraction as a means for deploying powerful predictive models, offering ease of use that enables organizations to leverage advanced analytics without substantial investments in specialized infrastructure or expertise. However, MLaaS...

VMware Aria Automation 安全漏洞

VMware Aria Automation is a modern workflow automation platform from VMware that simplifies and automates complex data center infrastructure tasks to improve scalability and agility. A security vulnerability exists in VMware Aria Automation that originates from DOM-type cross-site scripting and...