Vector35 / Vector35/binaryninja-api
Loading images from DSC results in excessive memory consumption
@bdash is already working on this.
Since Feb 9, 2026.
- Dominant language
- C++
- Stars
- 1.3k
- Forks
- 298
- Avg merge
- 5d 5h
- Merged PRs (30d)
- 19
Description
Version and Platform (required):
- Binary Ninja Version: 4.2.6304-dev (65f49c87)
- OS: macOS
- OS Version: 15.0
- CPU Architecture: M1
Bug Description:
I am finding that when analysing dyld shared cache memory consumption becomes excessive relatively quickly. This is both the case in headless and when using the UI. Simply loading multiple images (2, maybe 3), one after the other, results in 10s of GBs of RAM being consumed by Binary Ninja. I've even had macOS run out of RAM because BN was using over 50GBs.
If the database is saved and then Binary Ninja is fully closed and the database re-opened, the amount of RAM usage is at more expected levels (couple of GBs, depending on how many DSC images are loaded).
Steps To Reproduce:
- Open a copy of DSC in Binary Ninja
- Load an image and wait for analysis to complete (may not be required but things are more stable this way)
- Repeat step 2 multiple times (load at least 2 images)
- Observe high RAM usage
- Save the database
- Close and re-open Binary Ninja
- Re-open the database
- Observe significantly less RAM usage
Binary:
Extract the DSC from any iOS 18+ IPSW. Not sure if its an iOS 18 related issues, its just the ones I've been testing on.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Assessment
This issue has not been assessed yet.