Can LLMs Handle WebShell Detection? Overcoming Detection Challenges with Behavioral Function-Aware Framework

WebShell attacks, in which malicious scripts are injected into web servers, are a major cybersecurity threat. Traditional machine learning and deep learning methods are hampered by issues such as the need for extensive training data, catastrophic forgetting, and poor generalization. Recently, Lar...

Investigating Cybersecurity Incidents Using Large Language Models in Latest-Generation Wireless Networks

The purpose of research: Detection of cybersecurity incidents and analysis of decision support and assessment of the effectiveness of measures to counter information security threats based on modern generative models. The methods of research: Emulation of signal propagation data in MIMO systems,...

MAI-2025-0013

This vulnerability affects Large Language Models LLMs by enabling attackers to bypass built-in safety mechanisms and extract detailed harmful responses through the strategic manipulation of input prompts. The vulnerability leverages the LLM's sensitivity to "scenario shifts," which are contextual...

LlamaIndex 安全漏洞

LlamaIndex is a data framework for LLM applications from the LlamaIndex open source. A security vulnerability exists in LlamaIndex version v0.12.5 that stems from an unhandled thread exception and could lead to a denial of service attack...

Lunary 安全漏洞

lunary is lunary open source a production toolkit for LLM . An access control error vulnerability exists in lunary that stems from improper access control on the /prompts/promptid endpoint, and no detailed vulnerability details are provided at this time...

Researchers Use AI Jailbreak on Top LLMs to Create Chrome Infostealer

New Immersive World LLM jailbreak lets anyone create malware with GenAI. Discover how Cato Networks researchers tricked ChatGPT, Copilot, and DeepSeek into coding infostealers - In this case, a Chrome infostealer...

MAI-2025-0007

Multimodal Large Language Models MLLMs are susceptible to attacks based on Jailbreak Probability, known as Jailbreak-Probability-based Attacks JPA. These attacks utilize a specialized Jailbreak Probability Prediction Network JPPN to detect and refine adversarial perturbations within input images...

12,000+ API Keys and Passwords Found in Public Datasets Used for LLM Training

A dataset used to train large language models LLMs has been found to contain nearly 12,000 live secrets, which allow for successful authentication. The findings once again highlight how hard-coded credentials pose a severe security risk to users and organizations alike, not to mention compounding...

Building Effective Agents with Spring AI (Part 1)

In a recent research publication: Building effective agents, Anthropic shared valuable insights about building effective Large Language Model LLM agents. What makes this research particularly interesting is its emphasis on simplicity and composability over complex frameworks. Let's explore how...

New Research: Enhancing Botnet Detection with AI using LLMs and Similarity Search

As botnets continue to evolve, so do the techniques required to detect them. While Transport Layer Security TLS encryption is widely adopted for secure communications, botnets leverage TLS to obscure command-and-control C2 traffic. These malicious actors often have identifiable characteristics...

AI-supported spear phishing fools more than 50% of targets

One of the first things everyone predicted when artificial intelligence AI became more commonplace was that it would assist cybercriminals in making their phishing campaigns more effective. Now, researchers have conducted a scientific study into the effectiveness of AI supported spear phishing, a...

AI Could Generate 10,000 Malware Variants, Evading Detection in 88% of Case

Cybersecurity researchers have found that it's possible to use large language models LLMs to generate new variants of malicious JavaScript code at scale in a manner that can better evade detection. "Although LLMs struggle to create malware from scratch, criminals can easily use them to rewrite or...

The vulnerability of Ollama’s system for running and managing large language models lies in the improper restriction on the path name to the restricted-access catalog, which allows a violator to trigger a service failure.

The vulnerability of the Ollama system for running and managing large language models is related to an incorrect restriction on the path name to the restricted-access catalog. Exploiting this vulnerability could allow a malicious actor to trigger a service failure...

The vulnerability of Ollama’s system for launching and managing large language models, related to the exposure of system data to unauthorized individuals, allows a violator to trigger a service failure.

The vulnerability of Ollama’s system for running and managing large language models is related to the exposure of system data to unauthorized individuals. Exploiting this vulnerability could allow a malicious actor to cause service failures...

The vulnerability of Ollama’s system for running and managing large language models, related to uncontrolled resource consumption, allows a hacker to trigger a service failure.

The vulnerability of Ollama’s system for running and managing large language models is related to an uncontrolled consumption of resources. Exploiting this vulnerability could allow a malicious actor to cause service failures...

Secure Your Generative Investments: Qualys Advances Enterprise TruRisk Platform with Qualys TotalAI to Protect Your LLM Investments

Artificial intelligence AI and large language models LLMs are reshaping industries, streamlining enterprise operations, and fueling unprecedented innovation. However, as adoption accelerates, so do the associated risks. While 70% of enterprises plan to deploy LLMs in production within the next 12...

MAI-2024-0017

Large Language Models LLMs utilizing Reinforcement Learning from Human Feedback RLHF for safety alignment are susceptible to a sophisticated "alignment-based" jailbreak attack. This attack employs a best-of-N sampling strategy in conjunction with an adversarial LLM to efficiently craft prompts th...

MAI-2024-0015

Large Language Models LLMs that employ prefix-forcing safety measures are susceptible to jailbreak attacks when the set of "safe" prefixes lacks diversity or fails to accommodate model-specific response styles. Attackers can exploit this vulnerability by crafting prompts that induce alternative...

Subverting LLM Coders

Really interesting research: "An LLM-Assisted Easy-to-Trigger Backdoor Attack on Code Completion Models: Injecting Disguised Vulnerabilities against Strong Detection": Abstract : Large Language Models LLMs have transformed code completion tasks, providing context-based suggestions to boost...

The vulnerability of the software’s user data loading function for running large language models (LLMs) like ChuanhuChatGPT allows a perpetrator to execute arbitrary code.

The vulnerability of the software’s user data loading function for running large language models like ChuanhuChatGPT is related to an incorrect restriction on the path name to the restricted-access directory. Exploiting this vulnerability could allow a malicious actor to execute arbitrary code...