Using MLeap for loading a saved model (zip archive) can lead to path traversal/arbitrary file creation and possibly remote code execution.
ml.combust.mleap.mleap-tensorflow
[0.18.0,0.23.0], Fixed in 0.23.1
FileUtil.extract() enumerates all zip file entries and extracts each file without validating whether file paths in the archive are outside the intended directory.
When creating an instance of TensorflowModel using the saved_model format and an exported TensorFlow model, the apply() function invokes the vulnerable implementation of FileUtil.extract().
Arbitrary file creation can directly lead to code execution
Example of a vulnerable usage of MLeap -
package example
import ml.combust.mleap.core.types._
import ml.combust.mleap.tensor.Tensor
import ml.combust.mleap.tensorflow.TensorflowModel
import org.tensorflow
import java.nio.file.{Files, Paths}
object LoadModelFromZip extends App {
// Read zip file
def readZipFileAsByteArray(filePath: String): Array[Byte] = {
val fileBytes = Files.readAllBytes(Paths.get(filePath))
fileBytes
}
// Stub
val _file = "/models/malicious.zip"
val modelAsBytes = readZipFileAsByteArray(_file)
// Create a model from zip file
val model = TensorflowModel(
inputs = Seq(
("InputA", TensorType.Float()), ("InputB", TensorType.Float())
),
outputs = Seq(("MyResult", TensorType.Float())),
format = Option("saved_model"),
modelBytes = modelAsBytes
)
// Invoke FileUtil.extract()
model.apply(Tensor.create(Array(2.0, 1.0, 34.0), Seq(-1)))
}
No mitigations are supplied for this issue