Constructing and Benchmarking: A Labeled Email Dataset for Text-Based Phishing and Spam Detection Framework

Phishing and spam emails remain a major cybersecurity threat, with attackers increasingly leveraging Large Language Models LLMs to craft highly deceptive content. This study presents a comprehensive email dataset containing phishing, spam, and legitimate messages, explicitly distinguishing betwee...

CVE-2025-50402

FAST FAC1200R F400FAC1200RQ is vulnerable to Buffer Overflow in the function sub80435780 via the parameter string facpassword...

CVE-2025-33204

NVIDIA NeMo Framework for all platforms contains a vulnerability in the NLP and LLM components, where malicious data created by an attacker could cause code injection. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, information disclosure, and data...

MINI-PC4F-24F2-JMV9

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MINI-225Q-4RF2-892W

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Important: Red Hat Security Advisory: RHTAS 1.3.1 - Tech Preview Release of Model Transparency

The Tech Preview release of the RHTAS Model Transparency CLI image. For more details please visit the product documentation at https://access.redhat.com/documentation/en-us/redhattrustedartifactsigner/1.3 The RHTAS Model Transparency CLI image can be used to sign and verify AI/ML workloads...

CVE-2025-62372

vLLM is an inference and serving engine for large language models LLMs. From version 0.5.5 to before 0.11.1, users can crash the vLLM engine serving multimodal models by passing multimodal embedding inputs with correct ndim but incorrect shape e.g. hidden dimension is wrong, regardless of whether...

NVIDIA DGX Spark 安全漏洞

NVIDIA DGX Spark is a personal AI computer from NVIDIA, USA. A security vulnerability exists in NVIDIA DGX Spark GB10, which stems from improper integrity validation in the SROOT firmware, which could lead to information disclosure...

NVIDIA Nemo Framework 代码注入漏洞

NVIDIA Nemo Framework is a framework for building and deploying generative AI models from NVIDIA. A code injection vulnerability exists in NVIDIA Nemo Framework that stems from the presence of malicious data in the NLP and LLM components, which could lead to code injection that could result in co...

Effective Command-Line Interface Fuzzing with Path-Aware Large Language Model Orchestration

Command-line interface CLI fuzzing tests programs by mutating both command-line options and input file contents, thus enabling discovery of vulnerabilities that only manifest under specific option-input combinations. Prior works of CLI fuzzing face the challenges of generating semantics-rich opti...

CVE-2025-62155

The CVE-2025-62155 entry concerns QuantumNous/new-api. A SSRF vulnerability existed prior to version 0.9.6 where the fix only protected the first URL request; an attacker could bypass via a 302 redirect and reach internal/intranet resources. The issue has been addressed in version 0.9.6, accordin...

Malicious code in automation_model (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 1926379efdd9fddb153965f44070e510b81ea958a611dc7b2fafb891b856f35c The package automationmodel was found to contain malicious code. Source: ghsa-malware b6b4ab86b995aa30207899784d17feba68bd397866ebb733d0de222eeb2a4c1...

MINI-FX4G-4G66-GVVP

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MINI-P43W-98MH-MJ3R

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SUSE-SU-2025:4174-1 Security update for MozillaFirefox

This update for MozillaFirefox fixes the following issues: - Update to Firefox Extended Support Release 140.5.0 ESR bsc1253188 - CVE-2025-13012: Race condition in the Graphics component. - CVE-2025-13016: Incorrect boundary conditions in the JavaScript: WebAssembly component. - CVE-2025-13017:...

Cross-LLM Generalization of Behavioral Backdoor Detection in AI Agent Supply Chains

As AI agents become integral to enterprise workflows, their reliance on shared tool libraries and pre-trained components creates significant supply chain vulnerabilities. While previous work has demonstrated behavioral backdoor detection within individual LLM architectures, the critical question ...

DUALGUAGE: Automated Joint Security-Functionality Benchmarking for Secure Code Generation

Large language models LLMs and autonomous coding agents are increasingly used to generate software across a wide range of domains. Yet a core requirement remains unmet: ensuring that generated code is secure without compromising its functional correctness. Existing benchmarks and evaluations for...

Accuracy and Efficiency Trade-Offs in LLM-Based Malware Detection and Explanation: A Comparative Study of Parameter Tuning Vs. Full Fine-Tuning

This study examines whether Low-Rank Adaptation LoRA fine-tuned Large Language Models LLMs can approximate the performance of fully fine-tuned models in generating human-interpretable decisions and explanations for malware classification. Achieving trustworthy malware detection, particularly when...

FedPoisonTTP: A Threat Model and Poisoning Attack for Federated Test-Time Personalization

Test-time personalization in federated learning enables models at clients to adjust online to local domain shifts, enhancing robustness and personalization in deployment. Yet, existing federated learning work largely overlooks the security risks that arise when local adaptation occurs at test tim...

Ruijie NBR Router 安全漏洞

Ruijie NBR Router is a wireless router from Ruijie China. A security vulnerability exists in the Ruijie NBR Router that originates from an unauthenticated file upload function and could lead to arbitrary code execution...