The vulnerability of the vLLM library for working with large language models involves unverified array indexing, which allows attackers to trigger service interruptions.

The vulnerability of the vLLM library for working with large language models is related to unverified array indexing. Exploiting this vulnerability could allow a malicious actor to cause service failures...

EUVD-2025-199609

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...

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...

CVE-2025-33204

CVE-2025-33204 affects NVIDIA NeMo Framework (all platforms). The vulnerability lies in the NLP/LLM components, where malicious input data can lead to code injection, with potential outcomes including code execution, privilege escalation, information disclosure, and data tampering. According to R...

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...

CVE-2025-59365

A stack buffer overflow vulnerability has been identified in certain router models. An authenticated attacker may trigger this vulnerability by sending a crafted request, potentially impacting the availability of the device. Refer to the ' Security Update for ASUS Router Firmware' section on the...

CVE-2025-59365

A stack buffer overflow vulnerability has been identified in certain router models. An authenticated attacker may trigger this vulnerability by sending a crafted request, potentially impacting the availability of the device. Refer to the ' Security Update for ASUS Router Firmware' section on the...

CVE-2025-59365

CVE-2025-59365 corresponds to a stack buffer overflow in ASUS Router firmware affecting certain router models. According to PT-2025-48016, the issue is triggered by an authenticated attacker sending a specially crafted request, potentially causing a denial of service and impacting device availabi...

A Research and Development Portfolio of GNN Centric Malware Detection, Explainability, and Dataset Curation

Graph Neural Networks GNNs have become an effective tool for malware detection by capturing program execution through graph-structured representations. However, important challenges remain regarding scalability, interpretability, and the availability of reliable datasets. This paper brings togeth...

PT-2025-48016

Name of the Vulnerable Software and Affected Versions ASUS Router Firmware affected versions not specified Description A stack buffer overflow condition exists in certain router models. An authenticated attacker can trigger this issue by sending a specially crafted request, which may lead to a...

PT-2025-48021

An authentication bypass vulnerability has been identified in the IFTTT integration feature. A remote, authenticated attacker could leverage this vulnerability to potentially gain unauthorized access to the device. This vulnerability does not affect Wi-Fi 7 series models. Refer to the 'Security...

LLM-CSEC: Empirical Evaluation of Security in C/C++ Code Generated by Large Language Models

The security of code generated by large language models LLMs is a significant concern, as studies indicate that such code often contains vulnerabilities and lacks essential defensive programming constructs. This work focuses on examining and evaluating the security of LLM-generated code,...

Defending Large Language Models against Jailbreak Exploits with Responsible AI Considerations

Large Language Models LLMs remain susceptible to jailbreak exploits that bypass safety filters and induce harmful or unethical behavior. This work presents a systematic taxonomy of existing jailbreak defenses across prompt-level, model-level, and training-time interventions, followed by three...

Lack of Sufficient Guardrails Lead to Excessive Agency (LLM08) in Some LLM Applications

Overview Retell AI's API creates AI voice agents that have excessive permissions and functionality, as a result of insufficient amounts of guardrails. As a result, attackers can exploit this and conduct large scale social engineering, phishing, and misinformation campaigns. Description Retell AI...

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 ...

Frequency Bias Matters: Diving into Robust and Generalized Deep Image Forgery Detection

As deep image forgery powered by AI generative models, such as GANs, continues to challenge today's digital world, detecting AI-generated forgeries has become a vital security topic. Generalizability and robustness are two critical concerns of a forgery detector, determining its reliability when...

TASO: Jailbreak LLMs Via Alternative Template and Suffix Optimization

Many recent studies showed that LLMs are vulnerable to jailbreak attacks, where an attacker can perturb the input of an LLM to induce it to generate an output for a harmful question. In general, existing jailbreak techniques either optimize a semantic template intended to induce the LLM to produc...

From Reviewers' Lens: Understanding Bug Bounty Report Invalid Reasons with LLMs

Bug bounty platforms e.g., HackerOne, BugCrowd leverage crowd-sourced vulnerability discovery to improve continuous coverage, reduce the cost of discovery, and serve as an integral complement to internal red teams. With the rise of AI-generated bug reports, little work exists to help bug hunters...

Think Fast: Real-Time IoT Intrusion Reasoning Using IDS and LLMs at the Edge Gateway

As the number of connected IoT devices continues to grow, securing these systems against cyber threats remains a major challenge, especially in environments with limited computational and energy resources. This paper presents an edge-centric Intrusion Detection System IDS framework that integrate...

CVE-2025-62426

Summary: CVE-2025-62426 affects vLLM up to versions before 0.11.1. The /v1/chat/completions and /tokenize endpoints accept a chat_template_kwargs parameter that is used before validation, allowing an attacker to block the API server by forcing large tokenization tasks and delaying all other reque...