300 matches found
An LLM-Based Self-Evolving Security Framework for 6G Space-Air-Ground Integrated Networks
Recently emerged 6G space-air-ground integrated networks SAGINs, which integrate satellites, aerial networks, and terrestrial communications, offer ubiquitous coverage for various mobile applications. However, the highly dynamic, open, and heterogeneous nature of SAGINs poses severe security...
Directed Greybox Fuzzing Via Large Language Model
Directed greybox fuzzing DGF focuses on efficiently reaching specific program locations or triggering particular behaviors, making it essential for tasks like vulnerability detection and crash reproduction. However, existing methods often suffer from path explosion and randomness in input mutatio...
LLM Watermarking Using Mixtures and Statistical-To-Computational Gaps
Given a text, can we determine whether it was generated by a large language model LLM or by a human? A widely studied approach to this problem is watermarking. We propose an undetectable and elementary watermarking scheme in the closed setting. Also, in the harder open setting, where the adversar...
LLM Security: Vulnerabilities, Attacks, Defenses, and Countermeasures
As large language models LLMs continue to evolve, it is critical to assess the security threats and vulnerabilities that may arise both during their training phase and after models have been deployed. This survey seeks to define and categorize the various attacks targeting LLMs, distinguishing...
vLLM 安全漏洞
vLLM is a vLLM open source high throughput and memory efficient reasoning and service engine for LLM. A security vulnerability exists in vLLM versions prior to 0.5.2 through 0.8.5, which stems from ZeroMQ could lead to denial of service and data exposure...
The Hidden Risks of LLM-Generated Web Application Code: a Security-Centric Evaluation of Code Generation Capabilities in Large Language Models
The rapid advancement of Large Language Models LLMs has enhanced software development processes, minimizing the time and effort required for coding and enhancing developer productivity. However, despite their potential benefits, code generated by LLMs has been shown to generate insecure code in...
Leveraging LLM to Strengthen ML-Based Cross-Site Scripting Detection
According to the Open Web Application Security Project OWASP, Cross-Site Scripting XSS is a critical security vulnerability. Despite decades of research, XSS remains among the top 10 security vulnerabilities. Researchers have proposed various techniques to protect systems from XSS attacks, with...
SAGE: a Generic Framework for LLM Safety Evaluation
Whitepaper called SAGE: A Generic Framework For LLM Safety Evaluation...
dify 安全漏洞
dify is an open source LLM application development platform from LangGenius Open Source. A security vulnerability exists in versions of dify prior to 1.3.0, which stems from a clickjacking vulnerability in the default settings that could lead to unauthorized operations...
ThreMoLIA: Threat Modeling of Large Language Model-Integrated Applications
Large Language Models LLMs are currently being integrated into industrial software applications to help users perform more complex tasks in less time. However, these LLM-Integrated Applications LIA expand the attack surface and introduce new kinds of threats. Threat modeling is commonly used to...
SUSE CVE-2025-31363
Mattermost versions 10.4.x = 10.4.2, 10.5.x = 10.5.0, 9.11.x = 9.11.9 fail to restrict domains the LLM can request to contact upstream which allows an authenticated user to exfiltrate data from an arbitrary server accessible to the victim via performing a prompt injection in the AI plugin's Jira...
Automated Static Vulnerability Detection Via a Holistic Neuro-Symbolic Approach
Static vulnerability detection is still a challenging problem and demands excessive human efforts, e.g., manual curation of good vulnerability patterns. None of prior works, including classic program analysis or Large Language Model LLM-based approaches, have fully automated such vulnerability...
BadApex: Backdoor Attack Based on Adaptive Optimization Mechanism of Black-Box Large Language Models
Previous insertion-based and paraphrase-based backdoors have achieved great success in attack efficacy, but they ignore the text quality and semantic consistency between poisoned and clean texts. Although recent studies introduce LLMs to generate poisoned texts and improve the stealthiness,...
OpDiffer: LLM-Assisted Opcode-Level Differential Testing of Ethereum Virtual Machine
As Ethereum continues to thrive, the Ethereum Virtual Machine EVM has become the cornerstone powering tens of millions of active smart contracts. Intuitively, security issues in EVMs could lead to inconsistent behaviors among smart contracts or even denial-of-service of the entire blockchain...
Mattermost 安全漏洞
Mattermost is an open source collaboration platform from Mattermost, Inc. in the United States. Mattermost suffers from an information disclosure vulnerability. The vulnerability stems from an under-restricted LLM request domain. An attacker can exploit the vulnerability to perform prompt injecti...
Prompt Engineering Techniques with Spring AI
This blog post demonstrates practical implementations of Prompt Engineering techniques using Spring AI. The examples and patterns in this article are based on the comprehensive Prompt Engineering Guide that covers the theory, principles, and patterns of effective prompt engineering. The blog show...
Lunary 安全漏洞
Lunary is Lunary open source a production toolkit for LLM . Lunary afc5df4 version of a security vulnerability , the vulnerability stems from a flaw in the permission checking mechanism , an attacker can use this vulnerability to cause unauthorized access to sensitive endpoints...
Lunary 授权问题漏洞
lunary is lunary open source a production toolkit for LLM . An authorization issue vulnerability exists in lunary that stems from the checklists.post endpoint not being properly privilege-validated and can be exploited by an attacker to cause unauthorized creation or modification of checklists...
Lunary 访问控制错误漏洞
Lunary is Lunary open source a production toolkit for LLM . Lunary suffers from an Access Control Error vulnerability that originates from the POST /api/v1/data-warehouse/bigquery endpoint without proper access control, which can be exploited by an attacker to obtain sensitive information...