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AI security company Adversa AI has released a shocking report stating that Elon Musk's startup xAI's newly launched Grok3 model has significant vulnerabilities in terms of cybersecurity. Adversa's research team found that this latest AI model is susceptible to 'simple jailbreak attacks', potentially allowing malicious actors to access sensitive information such as 'how to groom children, handle corpses, extract DMT, and make bombs'. Worse still, Adversa

Recently, researchers from Stanford University and the University of Hong Kong discovered that current AI Agents (such as Claude) are more easily disrupted by pop-ups than humans, with significantly reduced performance even when faced with simple pop-ups. According to the study, AI Agents achieved an average attack success rate of 86% when confronted with deliberately designed pop-ups in experimental environments, leading to a 47% decrease in task success rate. This finding has sparked new concerns regarding the safety of AI Agents, especially as they are assigned more autonomous tasks.

AI painting is a revolutionary image generation technology based on deep learning algorithms, particularly Generative Adversarial Networks (GANs) and diffusion models. This approach analyzes vast amounts of image data to learn and simulate human painting techniques, thereby creating entirely new visual works. AI painting not only captures and reproduces the complex details of the real world accurately but also blends different artistic styles, showcasing astonishing creativity and imagination. The core of this technology lies in transforming abstract textual descriptions into concrete visual expressions.

Deep learning-based software security detection systems act as the 'security inspectors' of the digital age, efficiently identifying software vulnerabilities. However, a study named EaTVul has unveiled new challenges in this field. EaTVul is an innovative evasion attack strategy that modifies vulnerable code, leading deep learning detection systems to misjudge, achieving success rates ranging from 83% to 100%. Its method includes using support vector machines to identify key samples, attention mechanisms to recognize critical features, AI chatbots to generate confusing data, and fuzzy logic.

The Prompt-Guard-86M model released by Meta is designed to defend against prompt injection attacks by restricting large language models from processing inappropriate inputs, thereby protecting system security. However, the model itself also exposes risks of being attacked. Research conducted by Aman Priyanshu found that by adding simple character spacing such as spaces or removing punctuation in the input, the model disregards prior security instructions, achieving an almost 100% success rate for attacks. This finding highlights the importance of AI security, despite Prompt

Recently, a new image super-resolution model called AuraSR has garnered widespread attention in the artificial intelligence community. Developed by Fal AI, this model is based on Adobe's latest GigaGAN paper and utilizes Generative Adversarial Network (GAN) technology to significantly enhance image resolution in a very short time.

In this era of information explosion, deaf and hard-of-hearing individuals often feel disconnected from the world. The UK-based AI company Signapse is building a bridge to the world for this long-neglected group through its innovative sign language translation technology.

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Due to the characteristics of neural networks, they are susceptible to adversarial attacks. Google DeepMind's latest research shows that human judgment is also influenced by these adversarial perturbations. What is the relationship between the human neural network and artificial neural networks? Research suggests our previous understanding may be incorrect! Human judgment is also affected by these adversarial perturbations.

Teams from Google DeepMind, the University of Washington, and others have successfully unveiled the sources of ChatGPT's training data through a 'poetry attack'. This attack method involves repeating specific vocabulary, which led ChatGPT to disclose personal information, including phone numbers and email addresses. The vulnerability was reported to OpenAI on August 30, and no further comments have been made. The research calls for environmentally-friendly AI usage, pointing out the significant energy burden that text and image generation imposes on the environment.

As the application of LLMs becomes increasingly widespread, enhancing their security has become urgent. Prompt attacks directly affect the accuracy of LLM execution and system security. This article introduces various methods of adversarial prompt attacks and instances of red team exercises that can strengthen the LLM's capability against attacks. Users should enhance their awareness of cybersecurity precautions.

Fujitsu has announced the launch of two new AI trust technologies aimed at enhancing the reliability of conversational AI models, including technologies for detecting hallucinations and adversarial attacks. These technologies will be integrated into Fujitsu's AI platform 'Kozuchi', designed to provide tools for businesses and individual users to assess the reliability of conversational AI responses, thereby enhancing AI security. The first technology aims to detect hallucinations in conversational AI responses with high precision, addressing potential misinformation issues in those replies. The second technology is used to detect conversational...

This article introduces a new type of cyber attack where hackers can steal personal data by listening to the sounds of keyboard inputs. This attack utilizes a custom deep learning-based algorithm to perform acoustic analysis of keyboard sounds and automatically decode the input content. Research shows that it can accurately decode 95% of the input content through this method. The article explains the principle of this attack and possible defense measures.