2081 matches found
EUVD-2017-0720
Malware in sbrugna...
EUVD-2006-0845
Malware in sbrugna...
EUVD-2006-6416
Malware in sbrugna...
EUVD-2006-5791
Malware in sbrugna...
NatGVD: Natural Adversarial Example Attack Towards Graph-Based Vulnerability Detection
Graph-based models learn rich code graph structural information and present superior performance on various code analysis tasks. However, the robustness of these models against adversarial example attacks in the context of vulnerability detection remains an open question. This paper proposes...
EUVD-2023-32442
Malicious code in bioql PyPI...
EUVD-2022-42711
Malicious code in bioql PyPI...
EUVD-2021-32108
Malicious code in bioql PyPI...
EUVD-2021-31889
Malicious code in bioql PyPI...
EUVD-2025-2171
Malicious code in bioql PyPI...
EUVD-2024-41443
Malicious code in bioql PyPI...
EUVD-2023-45272
Malicious code in bioql PyPI...
Evaluating the Robustness of a Production Malware Detection System to Transferable Adversarial Attacks
As deep learning models become widely deployed as components within larger production systems, their individual shortcomings can create system-level vulnerabilities with real-world impact. This paper studies how adversarial attacks targeting an ML component can degrade or bypass an entire...
FuncPoison: Poisoning Function Library to Hijack Multi-Agent Autonomous Driving Systems
Autonomous driving systems increasingly rely on multi-agent architectures powered by large language models LLMs, where specialized agents collaborate to perceive, reason, and plan. A key component of these systems is the shared function library, a collection of software tools that agents use to...
web-application-firewall
🔒 Project 2 — WAF Rule Development & Evasion Testing Projec...
winlow
Windows Internals & Exploitation A concise, practical referen...
Automatic Red Teaming LLM-Based Agents with Model Context Protocol Tools
The remarkable capability of large language models LLMs has led to the wide application of LLM-based agents in various domains. To standardize interactions between LLM-based agents and their environments, model context protocol MCP tools have become the de facto standard and are now widely...
Cybercriminals Have a Weird New Way to Target You With Scam Texts
Scammers are now using “SMS blasters” to send out up to 100,000 texts per hour to phones that are tricked into thinking the devices are cell towers. Your wireless carrier is powerless to stop them...
New Raven Stealer Malware Hits Browsers for Passwords and Payment Data
New research reveals Raven Stealer malware that targets browsers like Chrome and Edge to steal personal data. Learn how this threat uses simple tricks like process hollowing to evade antiviruses and why it's a growing risk for everyday users...
A Practical Adversarial Attack against Sequence-Based Deep Learning Malware Classifiers
Sequence-based deep learning models e.g., RNNs, can detect malware by analyzing its behavioral sequences. Meanwhile, these models are susceptible to adversarial attacks. Attackers can create adversarial samples that alter the sequence characteristics of behavior sequences to deceive malware...