109 matches found
Microsoft raises the bar: A smarter way to measure AI for cybersecurity
ExCyTIn-Bench is Microsoft’s newest open-source benchmarking tool designed to evaluate how well AI systems perform real-world cybersecurity investigations.1 It helps business leaders assess language models by simulating realistic cyberthreat scenarios and providing clear, actionable insights into...
EUVD-2022-54493
Malicious code in bioql PyPI...
Explainable but Vulnerable: Adversarial Attacks on XAI Explanation in Cybersecurity Applications
Explainable Artificial Intelligence XAI has aided machine learning ML researchers with the power of scrutinizing the decisions of the black-box models. XAI methods enable looking deep inside the models' behavior, eventually generating explanations along with a perceived trust and transparency...
ExpIDS: a Drift-Adaptable Network Intrusion Detection System with Improved Explainability
Despite all the advantages associated with Network Intrusion Detection Systems NIDSs that utilize machine learning ML models, there is a significant reluctance among cyber security experts to implement these models in real-world production settings. This is primarily because of their opaque natur...
Adversarial Attacks on VQA-NLE: Exposing and Alleviating Inconsistencies in Visual Question Answering Explanations
Natural language explanations in visual question answering VQA-NLE aim to make black-box models more transparent by elucidating their decision-making processes. However, we find that existing VQA-NLE systems can produce inconsistent explanations and reach conclusions without genuinely understandi...
Interpreting Differential Privacy in Terms of Disclosure Risk
As the use of differential privacy DP becomes widespread, the development of effective tools for reasoning about the privacy guarantee becomes increasingly critical. In pursuit of this goal, we demonstrate novel relationships between DP and measures of statistical disclosure risk. We suggest how...
MalGuard: Towards Real-Time, Accurate, and Actionable Detection of Malicious Packages in PyPI Ecosystem
Malicious package detection has become a critical task in ensuring the security and stability of the PyPI. Existing detection approaches have focused on advancing model selection, evolving from traditional machine learning ML models to large language models LLMs. However, as the complexity of the...
MultiPhishGuard: an LLM-Based Multi-Agent System for Phishing Email Detection
Phishing email detection faces critical challenges from evolving adversarial tactics and heterogeneous attack patterns. Traditional detection methods, such as rule-based filters and denylists, often struggle to keep pace with these evolving tactics, leading to false negatives and compromised...
VADER: a Human-Evaluated Benchmark for Vulnerability Assessment, Detection, Explanation, and Remediation
Ensuring that large language models LLMs can effectively assess, detect, explain, and remediate software vulnerabilities is critical for building robust and secure software systems. We introduce VADER, a human-evaluated benchmark designed explicitly to assess LLM performance across four key...
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...
Evaluating Explanation Quality in X-IDS Using Feature Alignment Metrics
Explainable artificial intelligence XAI methods have become increasingly important in the context of explainable intrusion detection systems X-IDSs for improving the interpretability and trustworthiness of X-IDSs. However, existing evaluation approaches for XAI focus on model-specific properties...
Bridging Expertise Gaps: the Role of LLMs in Human-AI Collaboration for Cybersecurity
This study investigates whether large language models LLMs can function as intelligent collaborators to bridge expertise gaps in cybersecurity decision-making. We examine two representative tasks-phishing email detection and intrusion detection-that differ in data modality, cognitive complexity,...
AlmaLinux 8 : raptor2 (ALSA-2025:0314)
The remote AlmaLinux 8 host has packages installed that are affected by a vulnerability as referenced in the ALSA-2025:0314 advisory. raptor: integer underflow when normalizing a URI with the turtle parser CVE-2024-57823 Tenable has extracted the preceding description block directly from the...
CVE-2024-56761 x86/fred: Clear WFE in missing-ENDBRANCH #CPs
In the Linux kernel, the following vulnerability has been resolved: x86/fred: Clear WFE in missing-ENDBRANCH CPs An indirect branch instruction sets the CPU indirect branch tracker IBT into WAITFORENDBRANCH WFE state and WFE stays asserted across the instruction boundary. When the decoder finds a...
Security Bulletin: IBM Cognos Analytics Mobile (iOS) is affected by multiple vulnerabilities
Summary There are vulnerabilities in Open Source Software OSS libraries consumed by IBM Cognos Analytics Mobile. These issues have been addressed by upgrading or removing the vulnerable libraries. Additionally, vulnerabilites related to CORS misconfiguration and Certificate Pinning have been...
The detail explanation about the parameters in License file
This article explains the parameter details in License file...
Exploit for Insufficient Verification of Data Authenticity in Rarlab Winrar
💥 WinRAR Vulnerability Description CVE-2023-38831 There...
Exploit for Path Traversal in Aiohttp
poc-cve-2024-23334 This repository contains a proof of concept...