Winning at All Cost: a Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models

This study reveals how frontier Large Language Models LLMs can "game the system" when faced with impossible situations, a critical security and alignment concern. Using a novel textual simulation approach, we presented three leading LLMs o1, o3-mini, and r1 with a tic-tac-toe scenario designed to...

Safeguard-By-Development: a Privacy-Enhanced Development Paradigm for Multi-Agent Collaboration Systems

Multi-agent collaboration systems MACS, powered by large language models LLMs, solve complex problems efficiently by leveraging each agent's specialization and communication between agents. However, the inherent exchange of information between agents and their interaction with external...

RAP-SM: Robust Adversarial Prompt Via Shadow Models for Copyright Verification of Large Language Models

Recent advances in large language models LLMs have underscored the importance of safeguarding intellectual property rights through robust fingerprinting techniques. Traditional fingerprint verification approaches typically focus on a single model, seeking to improve the robustness of its...

NVIDIA TensorRT-LLM python executor code issue vulnerability

NVIDIA TensorRT-LLM is a high-performance inference acceleration library from NVIDIA for defining, optimizing, and executing inference in production environments for large language models LLMs. A code issue vulnerability exists in NVIDIA TensorRT-LLM that stems from insufficient data validation a...

A Proposal for Evaluating the Operational Risk for ChatBots Based on Large Language Models

The emergence of Generative AI Gen AI and Large Language Models LLMs has enabled more advanced chatbots capable of human-like interactions. However, these conversational agents introduce a broader set of operational risks that extend beyond traditional cybersecurity considerations. In this work, ...

Large Language Models Are Autonomous Cyber Defenders

Fast and effective incident response is essential to prevent adversarial cyberattacks. Autonomous Cyber Defense ACD aims to automate incident response through Artificial Intelligence AI agents that plan and execute actions. Most ACD approaches focus on single-agent scenarios and leverage...

netty: Denial of Service attack on windows app using Netty

A flaw was found in Netty. An unsafe reading of the environment file could cause a denial of service. When loaded on a Windows application, Netty attempts to load a file that does not exist. If an attacker creates a large file, the Netty application crash...

netty: Denial of Service attack on windows app using Netty

A flaw was found in Netty. An unsafe reading of the environment file could cause a denial of service. When loaded on a Windows application, Netty attempts to load a file that does not exist. If an attacker creates a large file, the Netty application crash...

netty: Denial of Service attack on windows app using Netty

A flaw was found in Netty. An unsafe reading of the environment file could potentially cause a denial of service. When loaded on a Windows application, Netty attempts to load a file that does not exist. If an attacker creates a large file, the Netty application crashes...

netty: Denial of Service attack on windows app using Netty

A flaw was found in Netty. An unsafe reading of the environment file could cause a denial of service. When loaded on a Windows application, Netty attempts to load a file that does not exist. If an attacker creates a large file, the Netty application crash...

netty: Denial of Service attack on windows app using Netty

A flaw was found in Netty. An unsafe reading of the environment file could potentially cause a denial of service. When loaded on a Windows application, Netty attempts to load a file that does not exist. If an attacker creates a large file, the Netty application crashes...

netty: Denial of Service attack on windows app using Netty

A flaw was found in Netty. An unsafe reading of the environment file could cause a denial of service. When loaded on a Windows application, Netty attempts to load a file that does not exist. If an attacker creates a large file, the Netty application crash...

netty: Denial of Service attack on windows app using Netty

A flaw was found in Netty. An unsafe reading of the environment file could potentially cause a denial of service. When loaded on a Windows application, Netty attempts to load a file that does not exist. If an attacker creates a large file, the Netty application crashes...

CVE-2025-21475

Memory corruption while processing escape code, when DisplayId is passed with large unsigned value...

CVE-2025-21475

Memory corruption while processing escape code, when DisplayId is passed with large unsigned value...

SKALD: Scalable K-Anonymisation for Large Datasets

Data privacy and anonymisation are critical concerns in today's data-driven society, particularly when handling personal and sensitive user data. Regulatory frameworks worldwide recommend privacy-preserving protocols such as k-anonymisation to de-identify releases of tabular data. Available...

BadLingual: a Novel Lingual-Backdoor Attack against Large Language Models

In this paper, we present a new form of backdoor attack against Large Language Models LLMs: lingual-backdoor attacks. The key novelty of lingual-backdoor attacks is that the language itself serves as the trigger to hijack the infected LLMs to generate inflammatory speech. They enable the precise...

Mitigating Backdoor Triggered and Targeted Data Poisoning Attacks in Voice Authentication Systems

Voice authentication systems remain susceptible to two major threats: backdoor triggered attacks and targeted data poisoning attacks. This dual vulnerability is critical because conventional solutions typically address each threat type separately, leaving systems exposed to adversaries who can...

Directed Greybox Fuzzing Via Large Language Model

Directed greybox fuzzing DGF focuses on efficiently reaching specific program locations or triggering particular behaviors, making it essential for tasks like vulnerability detection and crash reproduction. However, existing methods often suffer from path explosion and randomness in input mutatio...

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,...