tensorflow / tensorflow/tflite-support

Crash in libtensorflowlite_jni.so with 16 KB alignment

Open
#1,006 1 comment 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Dominant language
C++
Stars
441
Forks
146
PR merge metrics
No merged PRs in 30d

Description

System information

  • Stripe CardScan SDK version: com.stripe:stripecardscan:21.24.3
  • Device/ABI: x86_64 (crash observed in libtensorflowlite_jni.so)

Issue
After updating our Android build to support 16 KB native library alignment, our app crashes when interacting with UI that triggers TFLite via the CardScan SDK.

Steps to reproduce

  1. Integrate Stripe’s CardScan SDK (version 21.24.3).
  2. Enable 16 KB native library alignment in the Android build.
  3. Run the app and perform a card scan.
  4. Trigger one of the following:
    • Click the Close button in the upper-left corner, OR
    • Use the “<” back navigation button in the bottom navigation bar.

Observed behavior
The app crashes with a native crash inside:

  • We reported this issue on Stripe’s CardScan GitHub repo, but based on the crash logs the root cause appears to be in the TensorFlow Lite JNI shared object.

Please let us know if you need more information on this.

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No source file, test, or complete native stack trace is named. Start by reproducing the crash with CardScan SDK 21.24.3 on x86_64 with 16 KB native library alignment, then inspect the failure around libtensorflowlite_jni.so during card-scan navigation; done means those Close and back-navigation actions no longer crash.

Written by the indexing model from the issue text.

Assessment

Tech stack
android, cpp, tensorflow
Domain
machine-learning, mobile-dev
Issue type
Bug
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.