horsicq/detect-it-easy

Program for determining types of files for Windows, Linux and MacOS.

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Summary Information

Updated 50 minutes ago
Added to GitGenius on September 5th, 2026
Created on June 1st, 2014
Open Issues & Pull Requests: 32 (+0)
GitHub issues: Enabled
Number of forks: 951
Total Stargazers: 11,497 (+2)
Total Subscribers: 175 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 2.7 hours
Mean response time: 2.2 days
90th percentile: 16.3 hours
Tracked items: 81

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Only 4% of issues opened in the past year have been closed. Three people close 84% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 27
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 787 days
Stale 30+ days: 22
Stale 90+ days: 19

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • bug (26)
  • suggestion (17)
  • approved (10)
  • enhancement (7)
  • sample files required (7)
  • help wanted (6)
  • question (5)
  • invalid (3)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

Detect It Easy is a file type identification tool for Windows, Linux, and MacOS that combines signature-based and heuristic analysis to detect packers, malware, and other file characteristics.

The tool addresses the limitations of traditional static analyzers by combining signature matching with heuristic analysis to reduce false positives and handle modified samples. Its detection architecture is script-driven, allowing users to create, modify, and optimize detection rules. For PE files, the heuristic engine performs specialized analysis passes over headers, data directories, sections, imports, exports, resources, .NET metadata, and code around the entry point without executing the file. It includes lightweight surface-level emulation of native instructions to expose patterns left by packers, such as proxy jumps and NOP padding. For managed code, it uses an internal MSIL opcode model to detect obfuscation patterns including indirect calls, control-flow transformations, and arithmetic mutations.

Detect It Easy suits malware analysts, cybersecurity experts, and reverse engineers who need reliable file identification across multiple platforms. It is particularly valuable when exact signatures are unknown or samples have been modified to evade ordinary detection. The flexible signature system and customizable detection logic make it suitable for integration into digital forensics workflows where precision matters and false positives are costly.

Development activity shows consistent engagement with the project. The repository maintains an active changelog documenting updates. Community contributions are actively solicited through translation efforts and general contribution channels. The tool has accumulated recognition through participation in community events, indicating sustained visibility and developer interest over time.