ArtPerception: ASCII Art-Based Jailbreak on LLMs with Recognition Pre-Test

The integration of Large Language Models LLMs into computer applications has introduced transformative capabilities but also significant security challenges. Existing safety alignments, which primarily focus on semantic interpretation, leave LLMs vulnerable to attacks that use non-standard data...

EUVD-2025-32853

vLLM is an inference and serving engine for large language models LLMs. Before version 0.11.0rc2, the API key support in vLLM performs validation using a method that was vulnerable to a timing attack. API key validation uses a string comparison that takes longer the more characters the provided A...

CVE-2025-59425 vLLM vulnerable to timing attack at bearer auth

vLLM is an inference and serving engine for large language models LLMs. Before version 0.11.0rc2, the API key support in vLLM performs validation using a method that was vulnerable to a timing attack. API key validation uses a string comparison that takes longer the more characters the provided A...

Towards Reliable and Practical LLM Security Evaluations Via Bayesian Modelling

Before adopting a new large language model LLM architecture, it is critical to understand vulnerabilities accurately. Existing evaluations can be difficult to trust, often drawing conclusions from LLMs that are not meaningfully comparable, relying on heuristic inputs or employing metrics that fai...

PT-2025-41178

🔴 vLLM, Timing Attack on API Key, CVE-2024-53500 Critical https://t.co/adbNFksIgb...

AutoPentester: An LLM Agent-Based Framework for Automated Pentesting

Penetration testing and vulnerability assessment are essential industry practices for safeguarding computer systems. As cyber threats grow in scale and complexity, the demand for pentesting has surged, surpassing the capacity of human professionals to meet it effectively. With advances in AI,...

Real-VulLLM: An LLM Based Assessment Framework in the Wild

Artificial Intelligence AI and more specifically Large Language Models LLMs have demonstrated exceptional progress in multiple areas including software engineering, however, their capability for vulnerability detection in the wild scenario and its corresponding reasoning remains underexplored...

EUVD-2025-29404

Malicious code in bioql PyPI...

EUVD-2023-41186

Malicious code in bioql PyPI...

EUVD-2025-24154

Malicious code in bioql PyPI...

EUVD-2024-2594

Malicious code in bioql PyPI...

EUVD-2025-25446

Malicious code in bioql PyPI...

POLAR: Automating Cyber Threat Prioritization through LLM-Powered Assessment

Large Language Models LLMs are intensively used to assist security analysts in counteracting the rapid exploitation of cyber threats, wherein LLMs offer cyber threat intelligence CTI to support vulnerability assessment and incident response. While recent work has shown that LLMs can support a wid...

Red Teaming Program Repair Agents: When Correct Patches Can Hide Vulnerabilities

LLM-based agents are increasingly deployed for software maintenance tasks such as automated program repair APR. APR agents automatically fetch GitHub issues and use backend LLMs to generate patches that fix the reported bugs. However, existing work primarily focuses on the functional correctness ...

Microsoft Flags AI-Driven Phishing: LLM-Crafted SVG Files Outsmart Email Security

Microsoft is calling attention to a new phishing campaign primarily aimed at U.S.-based organizations that has likely utilized code generated using large language models LLMs to obfuscate payloads and evade security defenses. "Appearing to be aided by a large language model LLM, the activity...

STAC: When Innocent Tools Form Dangerous Chains to Jailbreak LLM Agents

As LLMs advance into autonomous agents with tool-use capabilities, they introduce security challenges that extend beyond traditional content-based LLM safety concerns. This paper introduces Sequential Tool Attack Chaining STAC, a novel multi-turn attack framework that exploits agent tool use. STA...

EvoMail: Self-Evolving Cognitive Agents for Adaptive Spam and Phishing Email Defense

Modern email spam and phishing attacks have evolved far beyond keyword blacklists or simple heuristics. Adversaries now craft multi-modal campaigns that combine natural-language text with obfuscated URLs, forged headers, and malicious attachments, adapting their strategies within days to bypass...

VLA-RL 代码问题漏洞

VLA-RL is a visual language action model by the individual developer of lgx. A code issue vulnerability exists in VLA-RL, which stems from misuse of the parameter Message in the file experiments/robot/bridge/reasoningserver.py, which could lead to a deserialization attack...

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...

CVE-2025-23354

NVIDIA Megatron-LM for all platforms contains a vulnerability in the ensembleclassifer script where malicious data created by an attacker may cause an injection. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, Information disclosure, and data...