# GView: A Survey of Binary Forensics via Visual, Semantic, and AI-Enhanced Analysis

arXiv: https://arxiv.org/abs/2509.13025 · HTML: https://mlsanity.com/paper/2509.13025/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 18 references that are in the map.
- First posted on arXiv 16 Sep 2025.

## Builds on (most cited first, 1 of 1)

- [GView: A Versatile Assistant for Security Researchers](https://mlsanity.com/paper/2404.09058/) (2024)

## Abstract (arXiv)

Cybersecurity threats continue to become more sophisticated and diverse in their artifacts, boosting both their volume and complexity. To overcome those challenges, we present GView, an open-source forensic analysis framework with visual and AI-enhanced reasoning. It started with focus on the practical cybersecurity industry. It has evolved significantly, incorporating large language models (LLMs) to dynamically enhance reasoning and ease the forensic workflows. This paper surveys both the current state of GView with its published papers alongside those that are in the publishing process. It also includes its innovative use of logical inference through predicates and inference rules for both the analyzed documents and the user's actions for better suggestions. We highlight the extensible architecture, showcasing its potential as a bridge between the practical forensics worlds with the academic research.