Vision Transformers: the Threat of Realistic Adversarial Patches

The increasing reliance on machine learning systems has made their security a critical concern. Evasion attacks enable adversaries to manipulate the decision-making processes of AI systems, potentially causing security breaches or misclassification of targets. Vision Transformers ViTs have gained...

PyTorch 安全漏洞

PyTorch is a Python package open-sourced by PyTorch. PyTorch suffers from a security vulnerability that stems from mishandling when compiling models containing torch.Tensor.tosparse and torch.Tensor.todense, which can be exploited by an attacker to cause a denial of service...

Two Critical Flaws Uncovered in Wondershare RepairIt Exposing User Data and AI Models

Cybersecurity researchers have disclosed two security flaws in Wondershare RepairIt that exposed private user data and potentially exposed the system to artificial intelligence AI model tampering and supply chain risks. The critical-rated vulnerabilities in question, discovered by Trend Micro, ar...

STAF: Leveraging LLMs for Automated Attack Tree-Based Security Test Generation

In modern automotive development, security testing is critical for safeguarding systems against increasingly advanced threats. Attack trees are widely used to systematically represent potential attack vectors, but generating comprehensive test cases from these trees remains a labor-intensive,...

Investigating Security Implications of Automatically Generated Code on the Software Supply Chain

In recent years, various software supply chain SSC attacks have posed significant risks to the global community. Severe consequences may arise if developers integrate insecure code snippets that are vulnerable to SSC attacks into their products. Particularly, code generation techniques, such as...

CyberSOCEval: Benchmarking LLMs Capabilities for Malware Analysis and Threat Intelligence Reasoning

Today's cyber defenders are overwhelmed by a deluge of security alerts, threat intelligence signals, and shifting business context, creating an urgent need for AI systems to enhance operational security work. While Large Language Models LLMs have the potential to automate and scale Security...

Can Federated Learning Safeguard Private Data in LLM Training? Vulnerabilities, Attacks, and Defense Evaluation

Fine-tuning large language models LLMs with local data is a widely adopted approach for organizations seeking to adapt LLMs to their specific domains. Given the shared characteristics in data across different organizations, the idea of collaboratively fine-tuning an LLM using data from multiple...

Bi-GRPO: Bidirectional Optimization for Jailbreak Backdoor Injection on LLMs

With the rapid advancement of large language models LLMs, their robustness against adversarial manipulations, particularly jailbreak backdoor attacks, has become critically important. Existing approaches to embedding jailbreak triggers--such as supervised fine-tuning SFT, model editing, and...

LLM-Based Vulnerability Discovery through the Lens of Code Metrics

Large language models LLMs excel in many tasks of software engineering, yet progress in leveraging them for vulnerability discovery has stalled in recent years. To understand this phenomenon, we investigate LLMs through the lens of classic code metrics. Surprisingly, we find that a classifier...

VulnCheck KEV: CVE-2025-45985

Blink routers BL-WR9000 V2.4.9 , BL-AC2100AZ3 V1.0.4, BL-X10AC8 v1.0.5 , BL-LTE300 v1.2.3, BL-F1200AT1 v1.0.0, BL-X26AC8 v1.2.8, BLAC450MAE4 v4.0.0 and BL-X26DA3 v1.2.7 were discovered to contain a command injection vulnerability via the bsSetSSIDHide function...

A Comparative Analysis of Ensemble-Based Machine Learning Approaches with Explainable AI for Multi-Class Intrusion Detection in Drone Networks

The growing integration of drones into civilian, commercial, and defense sectors introduces significant cybersecurity concerns, particularly with the increased risk of network-based intrusions targeting drone communication protocols. Detecting and classifying these intrusions is inherently...

CVE-2025-57685

The LB-Link routers, including the BL-AC2100AZ3 V1.0.4, BL-WR4000 v2.5.0, BL-WR9000AE4 v2.4.9, BL-AC1900AZ2 v1.0.2, BL-X26AC8 v1.2.8, and BL-LTE300DA4 V1.2.3 models, are vulnerable to unauthorized command injection. Attackers can exploit this vulnerability by accessing the /goform/setserialcfg...

LB-Link多款产品 安全漏洞

LB-Link BL-AC2100AZ3 and others are a wireless router from China Bilink LB-Link. A security vulnerability exists in various LB-Link products, which originates from an unauthorized command injection in the /goform/setserialcfg interface, which may result in the remote execution of malicious...

Flowise 代码注入漏洞

Flowise is a FlowiseAI open source tool for easily building LLM applications. A cross-site scripting vulnerability exists in Flowise version 3.0.5, which originates from a CustomMCP node directly executing user-entered JavaScript code and can be exploited by an attacker to cause remote code...

Coherence-Driven Inference for Cybersecurity

Large language models LLMs can compile weighted graphs on natural language data to enable automatic coherence-driven inference CDI relevant to red and blue team operations in cybersecurity. This represents an early application of automatic CDI that holds near- to medium-term promise for...

PT-2025-39007

The LB-Link routers, including the BL-AC2100 AZ3 V1.0.4, BL-WR4000 v2.5.0, BL-WR9000 AE4 v2.4.9, BL-AC1900 AZ2 v1.0.2, BL-X26 AC8 v1.2.8, and BL-LTE300 DA4 V1.2.3 models, are vulnerable to unauthorized command injection. Attackers can exploit this vulnerability by accessing the /goform/set serial...

SilentStriker: toward Stealthy Bit-Flip Attacks on Large Language Models

The rapid adoption of large language models LLMs in critical domains has spurred extensive research into their security issues. While input manipulation attacks e.g., prompt injection have been well studied, Bit-Flip Attacks BFAs -- which exploit hardware vulnerabilities to corrupt model paramete...

FakeSound2: a Benchmark for Explainable and Generalizable Deepfake Sound Detection

The rapid development of generative audio raises ethical and security concerns stemming from forged data, making deepfake sound detection an important safeguard against the malicious use of such technologies. Although prior studies have explored this task, existing methods largely focus on binary...

DecipherGuard: Understanding and Deciphering Jailbreak Prompts for a Safer Deployment of Intelligent Software Systems

Intelligent software systems powered by Large Language Models LLMs are increasingly deployed in critical sectors, raising concerns about their safety during runtime. Through an industry-academic collaboration when deploying an LLM-powered virtual customer assistant, a critical software engineerin...

"Digital Camouflage": the LLVM Challenge in LLM-Based Malware Detection

Large Language Models LLMs have emerged as promising tools for malware detection by analyzing code semantics, identifying vulnerabilities, and adapting to evolving threats. However, their reliability under adversarial compiler-level obfuscation is yet to be discovered. In this study, we empirical...