# codilime/veles

Binary data analysis and visualization tool

Repository: https://github.com/codilime/veles
Canonical: https://ross.abutalabs.com/products/veles
Homepage: https://veles.io
Language: C++
License: Apache-2.0
License Family: permissive
Topics: hexeditor, qt, cpp, visualization, shaders, reverse-engineering, python
Archived: true
Last push: 2019-06-16T09:07:16+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3520, "days_push": 2635, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1239, forks 122 (observed 2026-08-28T04:04:05.985912+00:00)

## What it is
Veles is a cross-platform desktop tool for binary data analysis that uses statistical visualizations to reveal patterns in large binary files. It combines a hex editor with GPU-accelerated visualization built in C++ and Qt.

## Use cases
- visualize large binary files to spot patterns
- analyze malware samples as binary data
- inspect file formats and headers in a hex editor
- find embedded data in firmware dumps
- explore entropy of binary blobs

## When to choose
- you need visual/statistical insight into large binary data rather than raw hex
- you want a free, open-source alternative to commercial hex editors
- you do reverse engineering or malware analysis

## When to avoid
- you need an actively developed tool - the latest release is from 2019
- you only need simple hex editing without visualization
- you need a terminal-based or scriptable hex tool

## Facets
- artifact type: application
- maturity: maintenance
- function: data-visualization, reverse-engineering, developer-tools
- domain: security, reverse-engineering, developer-tools
- platform: windows, cpp, python
- tags: hex-editor, binary-analysis, statistical-visualization, qt, shaders, linux, macos

## Member repositories
- codilime/veles (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:05.985912+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T05:09:56.874975+00:00, confidence not recorded.
  - readme: https://github.com/codilime/veles (fetched 2026-08-28T04:04:05.985912+00:00, sha 0696e3cc302d)
- Data as of 2026-08-30T08:39:29.467469+00:00.