1343 matches found
Genesis: Evolving Attack Strategies for LLM Web Agent Red-Teaming
As large language model LLM agents increasingly automate complex web tasks, they boost productivity while simultaneously introducing new security risks. However, relevant studies on web agent attacks remain limited. Existing red-teaming approaches mainly rely on manually crafted attack strategies...
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...
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...
The Difference Between Vulnerability and Exposure Management Explained
To build a truly effective defense, you have to learn to see your organization through an attacker's eyes. Attackers don't care about your internal vulnerability scan reports or how many patches you applied last week. They look for one thing: an open door. They search for an accessible pathway th...
EUVD-2021-2276
Malware in sbrugna...
EUVD-2014-4464
Malware in sbrugna...
EUVD-2013-1034
Malware in sbrugna...
EUVD-2020-1480
Malware in sbrugna...
EUVD-2013-1033
Malware in sbrugna...
EUVD-2020-0343
Malware in sbrugna...
EUVD-2021-2219
Malware in sbrugna...
EUVD-2021-1325
Malware in sbrugna...
AutoDAN-Reasoning: Enhancing Strategies Exploration Based Jailbreak Attacks with Test-Time Scaling
Recent advancements in jailbreaking large language models LLMs, such as AutoDAN-Turbo, have demonstrated the power of automated strategy discovery. AutoDAN-Turbo employs a lifelong learning agent to build a rich library of attack strategies from scratch. While highly effective, its test-time...
EUVD-2025-26748
Malicious code in bioql PyPI...
EUVD-2022-6984
Malicious code in bioql PyPI...
EUVD-2023-0812
Malicious code in bioql PyPI...
EUVD-2025-30680
Malicious code in bioql PyPI...
EUVD-2025-4088
Malicious code in bioql PyPI...