3 citations · 4 across the 5 of their papers we have counts for
5 papers
Not All 4-bit Quantizers Are Equal: Deployment-Time Mitigation of PII Leakage in Fine-Tuned Small Language Models
Cristhian Kapelinski, Diego Kreutz
Organizations fine-tune small language models on private data and then compress them to 4 bits for resource-efficient deployment. We show that the compression method also affects p…
Security-First Evaluation of Text-to-Terraform: Benchmarking LLMs and SLMs for Secure IaC Generation
Francis Luis Santos Vargas, Rodrigo Brandão Mansilha, Diego Kreutz
Cloud misconfiguration remains a leading cause of security incidents, yet whether LLMs and SLMs can generate security-compliant Infrastructure-as-Code is an open question. We bench…
Decomposing Memorization Reduction in Privacy-Preserving Fine-Tuning of SLMs for CSIRTs
Cristhian Kapelinski, Diego Kreutz
CSIRTs increasingly fine tune language models on vulnerability scan records, but these records expose internal network topology and create privacy risks under regulations such as G…
MalDataGen: A Modular Framework for Synthetic Tabular Data Generation in Malware Detection
Kayua Oleques Paim, Angelo Gaspar Diniz Nogueira, Diego Kreutz +2
High-quality data scarcity hinders malware detection, limiting ML performance. We introduce MalDataGen, an open-source modular framework for generating high-fidelity synthetic tabu…
Exploiting Latent Space Discontinuities for Building Universal LLM Jailbreaks and Data Extraction Attacks
Kayua Oleques Paim, Rodrigo Brandao Mansilha, Diego Kreutz +2
The rapid proliferation of Large Language Models (LLMs) has raised significant concerns about their security against adversarial attacks. In this work, we propose a novel approach…