Reconstructing Source Code from Compiled Binaries with GPT-5.6 Luna and REagent

On X, software and security practitioner @dryxio2 shared an operational reverse engineering hack for reconstructing source code from compiled binaries by pairing GPT-5.6 Luna with the REagent harness, enabling round-the-clock decompilation loops without burning through API usage quotas.

Image source: @dryxio2 via X

While frontier language models are increasingly tested against decompilation and binary analysis workloads, top-tier flagship models often hit steep quota ceilings when tasked with long-running, multi-day codebase reconstruction. @dryxio2 highlighted a practical alternative: instead of deploying the heavy GPT-6 Astra, pointing the lightweight GPT-5.6 Luna at the open-source REagent harness allows continuous, automated decompilation passes to run uninterrupted 24/7.

Decompilation Workflow: Pointing GPT-5.6 Luna at REagent

The reverse engineering hack outlined by @dryxio2 breaks down into three key steps:

1. Target the REagent Harness Direct the agent setup to the open-source REagent repository, an orchestration harness designed to manage program decompilation and source code reconstruction loops.
2. Assign GPT-5.6 Luna to Compiled Binaries Point the GPT-5.6 Luna model at the target compiled executable to iteratively reconstruct original source logic and function bodies.
3. Maintain Continuous Multi-Day Execution Keep the reconstruction loop active for days without hitting strict rate caps or draining token allowances, allowing the model to steadily parse functions in the background.

Why GPT-5.6 Luna Outperforms GPT-6 Astra in Continuous Workloads

A notable takeaway from @dryxio2's explanation is the operational comparison between flagship reasoning tiers and high-efficiency models during extended analysis tasks.

When another user (@WolfyBlair) suggested using Astra 6 instead, @dryxio2 pointed out the operational ceiling that limits top-tier models in production runs:

"You can't let Astra run for more than a day without nuking your limits. Luna can run 24/7, with this harness (REagent) it does wonders."

Reconstructing readable source code from a compiled program requires thousands of iterative passes across control flow graphs, disassembled routines, and symbol mappings. Under such continuous workloads, a flagship model like GPT-6 Astra quickly exhausts rate limits and API ceilings within hours. In contrast, GPT-5.6 Luna delivers capable code reasoning while remaining within sustainable API budgets, making it well-suited for autonomous, multi-day reverse engineering pipelines.

Original source

Primary discussions and open-source tooling references for this workflow can be accessed directly through the links below:

• Original thread by @dryxio2 on X: reverse engineering hack: point GPT-5.6 Luna at this repo
• REagent GitHub repository: GitHub - Dryxio/reagent