Revisiting Vul-RAG: Reproducibility and Replicability of RAG-Based Vulnerability Detection with Open-Weight Models

Large language models LLMs have shown strong potential for automated software vulnerability detection, particularly in retrieval-augmented generation RAG settings. However, for approaches relying on proprietary models and APIs, reproducibility and replicability remain largely unexplored, raising...

MaxKB 代码问题漏洞

MaxKB is an open-source question-answering system based on large language models and RAG, developed by 1Panel-dev. Versions of MaxKB prior to 2.8.1 contained code vulnerabilities. These vulnerabilities stemmed from a server-side request forgeing vulnerability in the OSS file service URL retrieval...

Intelligent Detection and Mitigation of Carpet-Bombing DDoS Attacks in SDN Using Retrieval-Augmented Generation and Large Language Models

Software-Defined Networking SDN provides flexible and programmable network management; however, its centralized control architecture remains highly vulnerable to Distributed Denial-of-Service DDoS attacks, particularly Carpet-Bombing DDoS attacks that distribute malicious traffic across multiple...

CVE-2026-21836 HCL DominoIQ is affected by broken access control

The HCL DominoIQ RAG feature is affected by a Broken Access Control vulnerability. Under certain circumstances, document level access restrictions will be ignored when determining what data to return from an AI query. This could enable an authenticated attacker to view sensitive data...

From Detection to Response: A Deep Learning and Retrieval-Augmented Generation Framework for Network Intrusion Mitigation

Machine-learning-based Intrusion Detection Systems IDS have achieved impressive accuracy in classifying network attacks, yet they consistently fall short on the question that matters most to a security analyst: what should I do next? This paper presents a unified, end-to-end framework that closes...

CVE-2026-45397 Open WebUI: Unauthenticated RAG Configuration Disclosure

Open WebUI is a self-hosted artificial intelligence platform designed to operate entirely offline. Prior to 0.9.5, GET /api/v1/retrieval/ returns live RAG pipeline configuration to any unauthenticated HTTP client. No Authorization header, cookie, or API key is required. Every adjacent endpoint on...

CVE-2026-45397

Open WebUI (self-hosted offline AI platform) is affected by CVE-2026-45397. The vulnerability is an information disclosure in the retrieval endpoint: GET /api/v1/retrieval/ can return live RAG configuration to unauthenticated clients. Affected component is backend/open_webui/routers/retrieval.py ...

Adversarial SQL Injection Generation with LLM-Based Architectures

SQL injection SQLi attacks are still one of the serious attacks ranked in the Open Worldwide Application Security Project OWASP Top 10 threats. Today, with advances in Artificial Intelligence AI, especially in Large Language Models LLMs, an opportunity has been created for automating adversarial...

Evaluating Retrieval-Augmented Generation for Explainable Malware Analysis

Large Language Models LLMs are increasingly being used as security engineering tools to summarize and explain malware behavior to analysts. A common assumption is that Retrieval-Augmented Generation RAG improves explanation quality by injecting external security knowledge. In this work, we...

When RAG Chatbots Expose Their Backend: An Anonymized Case Study of Privacy and Security Risks in Patient-Facing Medical AI

Background: Patient-facing medical chatbots based on retrieval-augmented generation RAG are increasingly promoted to deliver accessible, grounded health information. AI-assisted development lowers the barrier to building them, but they still demand rigorous security, privacy, and governance...

AsmRAG: LLM-Driven Malware Detection by Retrieving Functionally Similar Assembly Code

Deep learning malware detectors achieve high classification accuracy but suffer from severe interpretability limitations, typically returning probabilistic verdicts that lack forensic context. We introduce AsmRAG, a framework performing malware analysis through Assembly-Level Retrieval-Augmented...

ai-security-poc

AI Security POC A fully containerised proof-of-concept for te...

llm-security-lab

LLM Security Lab Laboratoire de sécurité pour application...

RAVEN: Retrieval-Augmented Vulnerability Exploration Network for Memory Corruption Analysis in User Code and Binary Programs

Large Language Models LLMs have demonstrated remarkable capabilities across various cybersecurity tasks, including vulnerability classification, detection, and patching. However, their potential in automated vulnerability report documentation and analysis remains underexplored. We present RAVEN...

MaxKB 安全漏洞

MaxKB is an open-source question-answering system based on large language models and RAG, developed by 1Panel-dev. Versions of MaxKB prior to 2.7.1 contained a security vulnerability. This vulnerability stemmed from a Eval injection flaw in the Markdown rendering engine, which could allow any use...

MaxKB 安全漏洞

MaxKB is an open-source question-answering system based on large language models and RAG, developed by 1Panel-dev. Versions of MaxKB prior to 2.7.1 contained a security vulnerability. This vulnerability stemmed from the use of storage-oriented cross-site scripting in the application name or icon...

MaxKB 代码注入漏洞

MaxKB is an open-source question-answering system based on large language models and RAG, developed by 1Panel-dev. Versions of MaxKB 2.2.1 and earlier have a code injection vulnerability. This vulnerability stems from incorrect handling of parameters in the file...

Securing Retrieval-Augmented Generation: A Taxonomy of Attacks, Defenses, and Future Directions

Retrieval-augmented generation RAG significantly enhances large language models LLMs but introduces novel security risks through external knowledge access. While existing studies cover various RAG vulnerabilities, they often conflate inherent LLM risks with those specifically introduced by RAG. I...

CVE-2026-35486

text-generation-webui is an open-source web interface for running Large Language Models. Prior to 4.3, he superbooga and superboogav2 RAG extensions fetch user-supplied URLs via requests.get with zero validation — no scheme check, no IP filtering, no hostname allowlist. An attacker can access clo...

CVE-2026-35486

CVE-2026-35486 affects text-generation-webui prior to 4.3, where the superbooga/superboogav2 RAG extensions fetch user-supplied URLs via requests.get() without validation. The root cause is lack of URL scheme validation, IP filtering, and hostname allowlisting, enabling an attacker to reach cloud...