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20232026
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cs.CR2026

CodePoisonRAG: Knowledge Poisoning Attacks on Retrieval-Augmented Code Generation

Varun Gadey, Ziad Marey, Alexandra Dmitrienko

Retrieval-Augmented Code Generation (RACG) improves LLM-based software development by retrieving external code artifacts, documentation, and patches, and incorporating them into th…

cs.CR2026

RAVEN: Agentic RAG for Automated Vulnerability Repair

Varun Gadey, Zijie Liu, Alexandra Dmitrienko

Automated vulnerability repair has emerged as a promising direction to mitigate the growing number of software vulnerabilities. Recent advances in Large Language Models (LLMs) have…

cs.CR2024

GNN-Based Code Annotation Logic for Establishing Security Boundaries in C Code

Varun Gadey, Raphael Goetz, Christoph Sendner +2

Securing sensitive operations in today's interconnected software landscape is crucial yet challenging. Modern platforms rely on Trusted Execution Environments (TEEs), such as Intel…

cs.CR2024

Memory Backdoor Attacks on Neural Networks

Eden Luzon, Guy Amit, Roy Weiss +3

Neural networks are often trained on proprietary datasets, making them attractive attack targets. We present a novel dataset extraction method leveraging an innovative training tim…

cs.CR2024

DNNShield: Embedding Identifiers for Deep Neural Network Ownership Verification

Jasper Stang, Torsten Krauß, Alexandra Dmitrienko

The surge in popularity of machine learning (ML) has driven significant investments in training Deep Neural Networks (DNNs). However, these models that require resource-intensive t…

cs.CR2023

Vulnerability Scanners for Ethereum Smart Contracts: A Large-Scale Study

Christoph Sendner, Lukas Petzi, Jasper Stang +1

Ethereum smart contracts, which are autonomous decentralized applications on the blockchain that manage assets often exceeding millions of dollars, have become primary targets for…