Artificial Intelligence – What's all the fuss?

Talking about AI: Definitions Artificial Intelligence AI — AI refers to the simulation of human intelligence in machines, enabling them to perform tasks that typically require human intelligence, such as decision-making and problem-solving. AI is the broadest concept in this field, encompassing...

On the Feasibility of Using MultiModal LLMs to Execute AR Social Engineering Attacks

Augmented Reality AR and Multimodal Large Language Models LLMs are rapidly evolving, providing unprecedented capabilities for human-computer interaction. However, their integration introduces a new attack surface for social engineering. In this paper, we systematically investigate the feasibility...

InjectLab: a Tactical Framework for Adversarial Threat Modeling against Large Language Models

Large Language Models LLMs are changing the way people interact with technology. Tools like ChatGPT and Claude AI are now common in business, research, and everyday life. But with that growth comes new risks, especially prompt-based attacks that exploit how these models process language. InjectLa...

Provable Secure Steganography Based on Adaptive Dynamic Sampling

The security of private communication is increasingly at risk due to widespread surveillance. Steganography, a technique for embedding secret messages within innocuous carriers, enables covert communication over monitored channels. Provably Secure Steganography PSS is state of the art for making...

Making Acoustic Side-Channel Attacks on Noisy Keyboards Viable with LLM-Assisted Spectrograms' "Typo" Correction

The large integration of microphones into devices increases the opportunities for Acoustic Side-Channel Attacks ASCAs, as these can be used to capture keystrokes' audio signals that might reveal sensitive information. However, the current State-Of-The-Art SOTA models for ASCAs, including...

R-TPT: Improving Adversarial Robustness of Vision-Language Models through Test-Time Prompt Tuning

Vision-language models VLMs, such as CLIP, have gained significant popularity as foundation models, with numerous fine-tuning methods developed to enhance performance on downstream tasks. However, due to their inherent vulnerability and the common practice of selecting from a limited set of...

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,...

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...

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...

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 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...

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...

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...