The vulnerability in the AuthenticationMiddleware class of the vLLM library allows attackers to bypass security restrictions and disclose sensitive information.

The vulnerability of the AuthenticationMiddleware class in the library for working with Large Language Models LLMs like vLLM is related to the use of hidden time channels for data transmission. Exploiting this vulnerability can allow an attacker to bypass security restrictions and disclose...

Prompting the Priorities: A First Look at Evaluating LLMs for Vulnerability Triage and Prioritization

Security analysts face increasing pressure to triage large and complex vulnerability backlogs. Large Language Models LLMs offer a potential aid by automating parts of the interpretation process. We evaluate four models ChatGPT, Claude, Gemini, and DeepSeek across twelve prompting techniques to...

CVE-2025-60344

CVE-2025-60344 describes a path traversal vulnerability in the D-Link DSR series (DSR-150, DSR-150N, DSR-250N v1.09B32_WW). Unauthenticated remote attackers can manipulate file/directory path resolution (e.g., via “../”) due to insufficient input validation, potentially exposing sensitive system ...

CLASP: Cost-Optimized LLM-Based Agentic System for Phishing Detection

Phishing websites remain a significant cybersecurity threat, necessitating accurate and cost-effective detection mechanisms. In this paper, we present CLASP, a novel system that effectively identifies phishing websites by leveraging multiple intelligent agents, built using large language models...

The vulnerability of Moxa network device software of the EDR-G9010, EDR-8010, EDF-G1002-BP, TN-4900, NAT-102, NAT-108, and OnCell G4302-LTE4 series is related to deficiencies in authentication mechanisms. This allows unauthorized individuals to gain access to protected information.

The vulnerability of Moxa network devices with microprogrammed software, such as EDR-G9010, EDR-8010, EDG-G1002-BP, TN-4900, NAT-102, NAT-108, and OnCell G4302-LTE4, is related to deficiencies in authentication mechanisms. Exploiting this vulnerability can allow unauthorized actors to gain...

HarmNet: A Framework for Adaptive Multi-Turn Jailbreak Attacks on Large Language Models

Large Language Models LLMs remain vulnerable to multi-turn jailbreak attacks. We introduce HarmNet, a modular framework comprising ThoughtNet, a hierarchical semantic network; a feedback-driven Simulator for iterative query refinement; and a Network Traverser for real-time adaptive attack...

CVE-2025-5517

Heap-based Buffer Overflow vulnerability in ABB Terra AC wallbox UL40/80A, ABB Terra AC wallbox UL32A, ABB Terra AC wallbox MID/ CE -Terra AC MID, ABB Terra AC wallbox MID/ CE -Terra AC Juno CE, ABB Terra AC wallbox MID/ CE -Terra AC PTB, ABB Terra AC wallbox JP.This issue affects Terra AC wallbo...

CVE-2025-5517 Heap Memory Corruption Vulnerability

Heap-based Buffer Overflow vulnerability in ABB Terra AC wallbox UL40/80A, ABB Terra AC wallbox UL32A, ABB Terra AC wallbox MID/ CE -Terra AC MID, ABB Terra AC wallbox MID/ CE -Terra AC Juno CE, ABB Terra AC wallbox MID/ CE -Terra AC PTB, ABB Terra AC wallbox JP.This issue affects Terra AC wallbo...

CVE-2025-5517 Heap Memory Corruption Vulnerability

Heap-based Buffer Overflow vulnerability in ABB Terra AC wallbox UL40/80A, ABB Terra AC wallbox UL32A, ABB Terra AC wallbox MID/ CE -Terra AC MID, ABB Terra AC wallbox MID/ CE -Terra AC Juno CE, ABB Terra AC wallbox MID/ CE -Terra AC PTB, ABB Terra AC wallbox JP.This issue affects Terra AC wallbo...

CrossGuard: Safeguarding MLLMs against Joint-Modal Implicit Malicious Attacks

Multimodal Large Language Models MLLMs achieve strong reasoning and perception capabilities but are increasingly vulnerable to jailbreak attacks. While existing work focuses on explicit attacks, where malicious content resides in a single modality, recent studies reveal implicit attacks, in which...

Multimodal Safety Is Asymmetric: Cross-Modal Exploits Unlock Black-Box MLLMs Jailbreaks

Multimodal large language models MLLMs have demonstrated significant utility across diverse real-world applications. But MLLMs remain vulnerable to jailbreaks, where adversarial inputs can collapse their safety constraints and trigger unethical responses. In this work, we investigate jailbreaks i...

The vulnerability in the web interface of the microprogramming software for Cisco IP Phones 9800, 7800, 8800, and 8875 allows a perpetrator to cause service failure.

The vulnerability of the web interface of Microprogramming Software for Cisco IP Phones models 9800, 7800, 8800, and 8875 lies in the fact that the operation outputs data beyond the buffer in memory. Exploiting this vulnerability allows a malicious actor to cause service failure by sending a...

Can Transformer Memory Be Corrupted? Investigating Cache-Side Vulnerabilities in Large Language Models

Even when prompts and parameters are secured, transformer language models remain vulnerable because their key-value KV cache during inference constitutes an overlooked attack surface. This paper introduces Malicious Token Injection MTI, a modular framework that systematically perturbs cached key...

Structuring Security: A Survey of Cybersecurity Ontologies, Semantic Log Processing, and LLMs Application

This survey investigates how ontologies, semantic log processing, and Large Language Models LLMs enhance cybersecurity. Ontologies structure domain knowledge, enabling interoperability, data integration, and advanced threat analysis. Security logs, though critical, are often unstructured and...

When Intelligence Fails: An Empirical Study on Why LLMs Struggle with Password Cracking

The remarkable capabilities of Large Language Models LLMs in natural language understanding and generation have sparked interest in their potential for cybersecurity applications, including password guessing. In this study, we conduct an empirical investigation into the efficacy of pre-trained LL...

SoK: Taxonomy and Evaluation of Prompt Security in Large Language Models

Large Language Models LLMs have rapidly become integral to real-world applications, powering services across diverse sectors. However, their widespread deployment has exposed critical security risks, particularly through jailbreak prompts that can bypass model alignment and induce harmful outputs...

MalCVE: Malware Detection and CVE Association Using Large Language Models

Malicious software attacks are having an increasingly significant economic impact. Commercial malware detection software can be costly, and tools that attribute malware to the specific software vulnerabilities it exploits are largely lacking. Understanding the connection between malware and the...

Architectures, Risks, and Adoption: How to Assess and Choose the Right AI-SOC Platform

Scaling the SOC with AI - Why now? Security Operations Centers SOCs are under unprecedented pressure. According to SACR’s AI-SOC Market Landscape 2025 , the average organization now faces around 960 alerts per day , while large enterprises manage more than 3,000 alerts daily from an average of 28...

Bringing the Power of Agentic AI for Identity Risk, Adaptive Threat Prioritization, and Exposure Exploitability Validation

Qualys Enterprise TruRisk Management ETM extends the power of risk operations with agentic AI — Introducing ETM Identity, TruLens for industry-based threat prioritization, and TruConfirm exposure exploitability validation to accelerate your remediation. Every year at our yearly conference, now...

Toward Cybersecurity-Expert Small Language Models

Large language models LLMs are transforming everyday applications, yet deployment in cybersecurity lags due to a lack of high-quality, domain-specific models and training datasets. To address this gap, we present CyberPal 2.0, a family of cybersecurity-expert small language models SLMs ranging fr...