justicerage/gepetto

IDA plugin which queries language models to speed up reverse-engineering

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Summary Information

Updated 40 minutes ago
Added to GitGenius on September 20th, 2026
Created on December 4th, 2022
Open Issues & Pull Requests: 16 (+0)
GitHub issues: Enabled
Number of forks: 331
Total Stargazers: 3,470 (+0)
Total Subscribers: 53 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 5.9 hours
Mean response time: 7.7 days
90th percentile: 17.0 days
Tracked items: 39

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Issue Activity (beta)

Open issues: 10
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 485 days
Stale 30+ days: 9
Stale 90+ days: 7

Recent activity

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

Top labels

  • enhancement (1)
  • good first issue (1)
  • help wanted (1)

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Detailed Description

Gepetto is an IDA Pro plugin that uses large language models to accelerate reverse-engineering work.

The plugin addresses the time-consuming task of understanding decompiled code by querying language models to generate explanations of function behavior and automatically rename variables with meaningful identifiers. It integrates directly into IDA Pro's interface, allowing analysts to request analysis of decompiled functions and receive results within seconds rather than manually studying the code.

Gepetto suits reverse-engineers and security researchers who work regularly with IDA Pro and want to reduce the manual effort of code comprehension. The tool requires an API key from a supported language model provider and incurs per-query costs, so it works best for workflows where the time savings justify API expenses. Installation is straightforward through the Hex-Rays CLI tool or manual placement in the IDA plugins directory, with configuration stored in the user's IDA directory to persist across plugin updates.

The project shows consistent maintenance with regular updates addressing user-reported issues and expanding model support. Development activity demonstrates responsiveness to community feedback, with fixes and enhancements applied to core functionality. The codebase remains actively refined to improve reliability and expand compatibility with different language model providers.