82 matches found
Detecting Vulnerabilities from Issue Reports for Internet-Of-Things
Timely identification of issue reports reflecting software vulnerabilities is crucial, particularly for Internet-of-Things IoT where analysis is slower than non-IoT systems. While Machine Learning ML and Large Language Models LLMs detect vulnerability-indicating issues in non-IoT systems, their I...
EUVD-2025-25825
Malicious code in bioql PyPI...
EUVD-2025-25826
Malicious code in bioql PyPI...
Dual-Path Phishing Detection: Integrating Transformer-Based NLP with Structural URL Analysis
Phishing emails pose a persistent and increasingly sophisticated threat, undermining email security through deceptive tactics designed to exploit both semantic and structural vulnerabilities. Traditional detection methods, often based on isolated analysis of email content or embedded URLs, fail t...
CVE-2025-23314
NVIDIA NeMo Framework for all platforms contains a vulnerability in the NLP component, where malicious data created by an attacker could cause a code injection issue. A successful exploit of this vulnerability might lead to code execution, escalation of privileges, information disclosure, and dat...
CVE-2025-23314
NVIDIA NeMo Framework for all platforms contains a vulnerability in the NLP component, where malicious data created by an attacker could cause a code injection issue. A successful exploit of this vulnerability might lead to code execution, escalation of privileges, information disclosure, and dat...
CVE-2025-23314
NVIDIA NeMo Framework for all platforms contains a vulnerability in the NLP component, where malicious data created by an attacker could cause a code injection issue. A successful exploit of this vulnerability might lead to code execution, escalation of privileges, information disclosure, and dat...
CVE-2025-23313
Summary (CVE-2025-23313) : NVIDIA NeMo Framework (NLP component) across platforms is described as vulnerable to code injection via malicious data. The underlying root cause is not detailed in the provided documents, but the consequence could include code execution, privilege escalation, informati...
CVE-2025-23313
NVIDIA NeMo Framework for all platforms contains a vulnerability in the NLP component, where malicious data created by an attacker could cause a code injection issue. A successful exploit of this vulnerability might lead to code execution, escalation of privileges, information disclosure, and dat...
CVE-2025-23313
NVIDIA NeMo Framework for all platforms contains a vulnerability in the NLP component, where malicious data created by an attacker could cause a code injection issue. A successful exploit of this vulnerability might lead to code execution, escalation of privileges, information disclosure, and dat...
CVE-2025-23313
NVIDIA NeMo Framework for all platforms contains a vulnerability in the NLP component, where malicious data created by an attacker could cause a code injection issue. A successful exploit of this vulnerability might lead to code execution, escalation of privileges, information disclosure, and dat...
NVIDIA Nemo Framework 代码注入漏洞
NVIDIA Nemo Framework is a framework for building and deploying generative AI models from NVIDIA. The NVIDIA Nemo Framework suffers from a code injection vulnerability that stems from malicious data in the NLP component that could lead to code injection, which in turn could lead to code execution...
PT-2025-34804
Name of the Vulnerable Software and Affected Versions: NVIDIA NeMo Framework affected versions not specified Description: The NVIDIA NeMo Framework contains an issue in the NLP component that could allow an attacker to inject code through maliciously crafted data. A successful exploit may lead to...
DINA: a Dual Defense Framework against Internal Noise and External Attacks in Natural Language Processing
As large language models LLMs and generative AI become increasingly integrated into customer service and moderation applications, adversarial threats emerge from both external manipulations and internal label corruption. In this work, we identify and systematically address these dual adversarial...
Automated Attack Testflow Extraction from Cyber Threat Report Using BERT for Contextual Analysis
In the ever-evolving landscape of cybersecurity, the rapid identification and mitigation of Advanced Persistent Threats APTs is crucial. Security practitioners rely on detailed threat reports to understand the tactics, techniques, and procedures TTPs employed by attackers. However, manually...
BackFed: an Efficient and Standardized Benchmark Suite for Backdoor Attacks in Federated Learning
Federated Learning FL systems are vulnerable to backdoor attacks, where adversaries train their local models on poisoned data and submit poisoned model updates to compromise the global model. Despite numerous proposed attacks and defenses, divergent experimental settings, implementation errors, a...
Enhancing Phishing Detection in Financial Systems through NLP
The threat of phishing attacks in financial systems is continuously growing. Therefore, protecting sensitive information from unauthorized access is paramount. This paper discusses the critical need for robust email phishing detection. Several existing methods, including blacklists and whitelists...
Human-Centred AI in FinTech: Developing a User Experience (UX) Research Point of View (PoV) Playbook
Advancements in Artificial Intelligence AI have significantly transformed the financial industry, enabling the development of more personalized and adaptable financial products and services. This research paper explores various instances where Human-Centred AI HCAI has facilitated these...
ModelForge: Using GenAI to Improve the Development of Security Protocols
Formal methods can be used for verifying security protocols, but their adoption can be hindered by the complexity of translating natural language protocol specifications into formal representations. In this paper, we introduce ModelForge, a novel tool that automates the translation of protocol...
