LIBLOOM is designed for third-party library (TPL) detection in Android apps, which encodes the signature of each class into an individual Bloom filter for fast containment queries and then performs TPL detection on the query results. Advanced non-structure-preserving (NSP) obfuscations including class repackaging and package flattening are heuristically addressed in it.
The artifact is built under Java Development Kit 1.8.
LIBLOOM is composed of two steps, i.e. profiling and detection. To detect TPLs from Android apps, you should first use "profile" command to generate profiles for Android apps and libraries. Then, you should use "detect" command to detect which TPLs are potentially used in Android apps. The detection result can be found in your specified directory (i.e., result_dir).
java -jar LIBLOOM.jar profile [-h] -d app_lib_dir -o profile_dir [-v]
Arguments:
-h show help message.
-d app_lib_dir specify app(.apk) or lib(.aar/.jar) folder.
-o profile_dir specify profile folder.
-v show debug information.
java -jar LIBLOOM.jar detect [-h] -ad apps_profile_dir -ld libs_profile_dir
-o result_dir [-v]
Arguments:
-h show help message.
-ad apps_profile_dir specify app profile folder.
-ld libs_profile_dir specify lib profile folder.
-o result_dir specify result folder.
-v show debug information.
Note
- To identify the library version accurately, the best library naming format should be
libname-version
, i.e.,gson-2.8.6.jar. An irregular naming format would lead to inaccurate result.For instance, com.google.gson-v2.8.6.jar and gson.2.8.6.jar are both reported by detector if one app depends on the library gson. - If several versions of a library have the highest similarity score, these potential versions will all be listed in the result for auditing.
- Metrics specification. Library-level or version-level TPLs evaluation methods can be selected. In our paper, we use the library-level method, which means a library is considered a true positive (TP) when its name is found in the ground truth (GT), and a false positive (FP) when it is not found. The version-level method is also supported by Libloom.
Hyper-parameters are configurable in artifacts/config/parameters.properties
.
CLASS_LEVEL_K=3
CLASS_LEVEL_M=256
PKG_LEVEL_K=3
PKG_LEVEL_M=21640
PKG_OVERLAP_THRESHOLD=0.8
SIMILARITY_THRESHOLD=0.6
You can test LIBLOOM by detecting given demo app(artifacts/demo/apps
).
First, generating profiles for demo app and libraries.
java -jar LIBLOOM.jar profile -d demo/apps -o profile/apps
java -jar LIBLOOM.jar profile -d demo/libs -o profile/libs
Then, detecting TPLs from demo app.
java -jar LIBLOOM.jar detect -ad profile/apps -ld profile/libs -o result
The detection result (.json) can be found in result
directory.
For more details about LIBLOOM, you can find in our paper.