CVE-2026-2555 JeecgBoot Retrieval-Augmented Generation AiragKnowledgeController.java importDocumentFromZip deserialization

A weakness has been identified in JeecgBoot 3.9.1. This vulnerability affects the function importDocumentFromZip of the file org/jeecg/modules/airag/llm/controller/AiragKnowledgeController.java of the component Retrieval-Augmented Generation. Executing a manipulation can lead to deserialization...

CVE-2026-2555

A weakness has been identified in JeecgBoot 3.9.1. This vulnerability affects the function importDocumentFromZip of the file org/jeecg/modules/airag/llm/controller/AiragKnowledgeController.java of the component Retrieval-Augmented Generation. Executing a manipulation can lead to deserialization...

CVE-2026-2111

A weakness has been identified in JeecgBoot up to 3.9.0. Affected by this issue is some unknown functionality of the file /airag/knowledge/doc/edit of the component Retrieval-Augmented Generation Module. Executing a manipulation of the argument filePath can lead to path traversal. The attack can ...

CVE-2026-2111 JeecgBoot Retrieval-Augmented Generation edit path traversal

A weakness has been identified in JeecgBoot up to 3.9.0. Affected by this issue is some unknown functionality of the file /airag/knowledge/doc/edit of the component Retrieval-Augmented Generation Module. Executing a manipulation of the argument filePath can lead to path traversal. The attack can ...

CVE-2026-2111

JeecgBoot

EUVD-2026-5716

A weakness has been identified in JeecgBoot up to 3.9.0. Affected by this issue is some unknown functionality of the file /airag/knowledge/doc/edit of the component Retrieval-Augmented Generation Module. Executing a manipulation of the argument filePath can lead to path traversal. The attack can ...

CVE-2026-2111 JeecgBoot Retrieval-Augmented Generation edit path traversal

A weakness has been identified in JeecgBoot up to 3.9.0. Affected by this issue is some unknown functionality of the file /airag/knowledge/doc/edit of the component Retrieval-Augmented Generation Module. Executing a manipulation of the argument filePath can lead to path traversal. The attack can ...

JeecgBoot 路径遍历漏洞

JeecgBoot is a Java low-code platform developed by Jeecg Corporation, designed for enterprise web applications. JeecgBoot versions 3.9.0 and earlier contained a path traversal vulnerability. This vulnerability stemmed from incorrect handling of the parameter “filePath” in the Component...

Persistent Human Feedback, LLMs, and Static Analyzers for Secure Code Generation and Vulnerability Detection

Existing literature heavily relies on static analysis tools to evaluate LLMs for secure code generation and vulnerability detection. We reviewed 1,080 LLM-generated code samples, built a human-validated ground-truth, and compared the outputs of two widely used static security tools, CodeQL and...

User-Centric Phishing Detection: A RAG and LLM-Based Approach

The escalating sophistication of phishing emails necessitates a shift beyond traditional rule-based and conventional machine-learning-based detectors. Although large language models LLMs offer strong natural language understanding, using them as standalone classifiers often yields elevated...

Lightweight LLMs for Network Attack Detection in IoT Networks

The rapid growth of Internet of Things IoT devices has increased the scale and diversity of cyberattacks, exposing limitations in traditional intrusion detection systems. Classical machine learning ML models such as Random Forest and Support Vector Machine perform well on known attacks but requir...

Rethinking On-Device LLM Reasoning: Why Analogical Mapping Outperforms Abstract Thinking for IoT DDoS Detection

The rapid expansion of IoT deployments has intensified cybersecurity threats, notably Distributed Denial of Service DDoS attacks, characterized by increasingly sophisticated patterns. Leveraging Generative AI through On-Device Large Language Models ODLLMs provides a viable solution for real-time...

An Empirical Evaluation of LLM-Based Approaches for Code Vulnerability Detection: RAG, SFT, and Dual-Agent Systems

The rapid advancement of Large Language Models LLMs presents new opportunities for automated software vulnerability detection, a crucial task in securing modern codebases. This paper presents a comparative study on the effectiveness of LLM-based techniques for detecting software vulnerabilities...

LLM-Driven Feature-Level Adversarial Attacks on Android Malware Detectors

The rapid growth in both the scale and complexity of Android malware has driven the widespread adoption of machine learning ML techniques for scalable and accurate malware detection. Despite their effectiveness, these models remain vulnerable to adversarial attacks that introduce carefully crafte...

ReGAIN: Retrieval-Grounded AI Framework for Network Traffic Analysis

Modern networks generate vast, heterogeneous traffic that must be continuously analyzed for security and performance. Traditional network traffic analysis systems, whether rule-based or machine learning-driven, often suffer from high false positives and lack interpretability, limiting analyst...

Agentic AI for 6G: A New Paradigm for Autonomous RAN Security Compliance

Agentic AI systems are emerging as powerful tools for automating complex, multi-step tasks across various industries. One such industry is telecommunications, where the growing complexity of next-generation radio access networks RANs opens up numerous opportunities for applying these systems...

Llama-Based Source Code Vulnerability Detection: Prompt Engineering Vs Fine Tuning

The significant increase in software production, driven by the acceleration of development cycles over the past two decades, has led to a steady rise in software vulnerabilities, as shown by statistics published yearly by the CVE program. The automation of the source code vulnerability detection...

From Reviewers' Lens: Understanding Bug Bounty Report Invalid Reasons with LLMs

Bug bounty platforms e.g., HackerOne, BugCrowd leverage crowd-sourced vulnerability discovery to improve continuous coverage, reduce the cost of discovery, and serve as an integral complement to internal red teams. With the rise of AI-generated bug reports, little work exists to help bug hunters...

ReVul-CoT: Towards Effective Software Vulnerability Assessment with Retrieval-Augmented Generation and Chain-Of-Thought Prompting

Context: Software Vulnerability Assessment SVA plays a vital role in evaluating and ranking vulnerabilities in software systems to ensure their security and reliability. Objective: Although Large Language Models LLMs have recently shown remarkable potential in SVA, they still face two major...

Securing AI Agents against Prompt Injection Attacks

Retrieval-augmented generation RAG systems have become widely used for enhancing large language model capabilities, but they introduce significant security vulnerabilities through prompt injection attacks. We present a comprehensive benchmark for evaluating prompt injection risks in RAG-enabled A...