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Hashcat is a password recovery tool. It had a proprietary code base until 2015, but was then released as open source software. Versions are available for Linux, macOS, and Windows. Examples of hashcat-supported hashing algorithms are LM hashes, MD4, MD5, SHA-family and Unix Crypt formats as well as algorithms used in MySQL and Cisco PIX.
The analysis highlights Variants, Attack types and Competitions as prominent areas in the source structure around Hashcat.
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around Hashcat shows recurring relationship patterns in the source. For example, Hashcat → Can, Competitions, Crack Me If, DefCon, DerbyCon, KoreLogic, Team Hashcat Another extracted example is Hashcat → Brute-force, CPU, Lookup, These, Toggle-Case. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
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TTTA extracted 32 structured relationships around Hashcat. Examples in this analysis include Hashcat → Developers → Jens 'atom' Steube, Gabriele 'matrix' Gristina and Hashcat → License → MIT License. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Hashcat | Developers | Jens 'atom' Steube, Gabriele 'matrix' Gristina | 1.00 | infobox |
| Hashcat | License | MIT License | 1.00 | infobox |
| Hashcat | Operating system | Cross-platform | 1.00 | infobox |
| Hashcat | Repository | github.com/hashcat/hashcat | 1.00 | infobox |
| Hashcat | Stable release | 7.1.2 / 23 August 2025; 12 months ago (23 August 2025) | 1.00 | infobox |
| Hashcat | Type | Password cracking | 1.00 | infobox |
| Hashcat | Website | www.hashcat.net | 1.00 | infobox |
| Hashcat | is a | password recovery tool | 0.90 | text |
| data-dependent branching | instance of | Due to factors | 0.80 | text |
| serialization | instance of | Due to factors | 0.80 | text |
| and memory | instance of | Due to factors | 0.80 | text |
| Hashcat | related to Attack types | These | 0.60 | section |
The concept neighborhoods around Hashcat bring nearby vocabulary together. In this analysis, examples include Attack, Oclhashcat and Tool. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Hashcat, one of the stronger structural bridges in this analysis connects Hashcat with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around Hashcat to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Variants, Attack types & Competitions, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Hashcat · EN edition · Analysis: TopicsToTalkAbout