Skip to content

CHARGE: Leveraging CWE Hierarchies for Hardware Security SystemVerilog Assertion Generation

Jul 2026 · arXiv.org · Vol abs/2607.27776 · 0 citations · 28 references
Computer Science

TL;DR

CHARGE is an automated framework for generating security properties for unverified RTL modules using CWEs and large language models using CWEs and large language models that leverages the hierarchical nature of CWE entries to improve accuracy when identifying security-critical assets in unverified RTL modules.

Abstract

This paper presents CHARGE, an automated framework for generating security properties for unverified RTL modules using CWEs and large language models (LLMs). The hallmark is a reasoning process that leverages the hierarchical nature of CWE entries to improve accuracy when identifying security-critical assets in unverified RTL modules. As a result, the approach can infer expected security behaviors and generate properties from identified assets and CWE semantics, avoiding the need for trusted design specifications and reducing manual engineering effort. We evaluate the framework on the Hack@DAC18, 19, and 21 open source SoC designs using OpenAI's GPT-4.1. CHARGE detects 27 of 42 known bugs in these designs. For Hack@DAC21 OpenPiton SoC, 89% of the generated SVAs run in Cadence JasperGold FPV, and 92.2% are non-vacuous. We compare to an open-source, manually written set of properties for these designs and find that CHARGE correctly writes properties for three bugs in which the manually written properties were incorrect. In addition, CHARGE-generated properties identify a new bug in the Hack@DAC21 OpenPiton SoC that was not previously identified.

View source

Similar papers

Jul 2026

CWEEP: A Lexical Static Analysis Framework for CWE Early Prevention

CWEEP can identify the exact location in the RTL where the potential vulnerability resides and supports automatic code repair suggestions when applicable, so it can be used in the early stages of RTL development while properties are still under construction.

B. Kwan, Benjamin Tan · 0 citations
#software testing Open access Sep 2026

LLM-Assisted Porting of Security-Critical C Libraries to Idiomatic Rust: A Multi-Model Empirical Study

Differential fuzzing reveals complementary bugs in the manual and LLM porting of security-critical C libraries to idiomatic Rust and translates these findings into concrete practical guidance for teams planning a similar migration.

Marco Parrillo, Marco Grassi, Luigi Laura · 0 citations
Open access Jul 2026

Can Language Models Generate Secure Terraform Code? A Security-Focused Benchmark Using Static Analysis

An empirical benchmark evaluating whether LLMs and SLMs can generate security-compliant AWS Terraform configurations suggests that prompt design is a critical factor, highlighting the need for a proper pipeline for developing and validating LLM-assisted secure IaC generation.

Francis Luis Santos Vargas, R. Mansilha, Diego Kreutz · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.