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

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...

EUVD-2026-19671

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

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...

Towards the Development of an LLM-Based Methodology for Automated Security Profiling in Compliance with Ukrainian Cybersecurity Regulations

In recent years, the pace of development of information technology in various areas has increased drastically, forcing cybersecurity specialists to constantly review existing processes in order to prevent unauthorized access to confidential information. Using Ukraine as a primary case study, this...

MA-IDS: Multi-Agent RAG Framework for IoT Network Intrusion Detection with an Experience Library

Network Intrusion Detection Systems NIDS face important limitations. Signature-based methods are effective for known attack patterns, but they struggle to detect zero-day attacks and often miss modified variants of previously known attacks, while many machine learning approaches offer limited...

Argus: Reorchestrating Static Analysis Via a Multi-Agent Ensemble for Full-Chain Security Vulnerability Detection

Recent advancements in Large Language Models LLMs have sparked interest in their application to Static Application Security Testing SAST, primarily due to their superior contextual reasoning capabilities compared to traditional symbolic or rule-based methods. However, existing LLM-based approache...

CVE-2026-2286

CrewAI contains a server-side request forgery vulnerability that enables content acquisition from internal and cloud services, facilitated by the RAG search tools not properly validating URLs provided at runtime...

CVE-2026-2286 CVE-2026-2286

CrewAI contains a server-side request forgery vulnerability that enables content acquisition from internal and cloud services, facilitated by the RAG search tools not properly validating URLs provided at runtime...

PT-2026-29050

Name of the Vulnerable Software and Affected Versions CrewAI affected versions not specified Description CrewAI contains a server-side request forgery condition that allows for the acquisition of content from internal and cloud services. This is facilitated by Retrieval-Augmented Generation RAG...

CVE-2026-28788

Open WebUI is a self-hosted artificial intelligence platform designed to operate entirely offline. Prior to version 0.8.6, any authenticated user can overwrite any file's content by ID through the POST /api/v1/retrieval/process/files/batch endpoint. The endpoint performs no ownership check, so a...