android - APKs generated through Eclipse are accepted or not? -


i little new android development.

i have hybrid app uses apache cordova plugins.

i using eclipse generate apk.

but when publish apk, google play store rejects saying:

app update rejected

your apk has been rejected containing security vulnerabilities, violates malicious behavior policy. alerts page has more information how resolve issue. if submitted update, previous version of app still live on google play.

and, when click on alerts page following error shows up:

security alert :

your app using version of apache cordova containing 1 or more security vulnerabilities. please see google center article details, including deadline fixing app.

i have tried followings:

  1. update android platform (cordova platform update android), no positive results.

  2. i not update cordova plugins getting errors. (wanted know can issue)

  3. i building apk using eclipse ide , went through adt plugin release note https://developer.android.com/studio/tools/sdk/eclipse-adt.html says: the eclipse adt plugin no longer supported

eventually importing project android studio want app update thats why still using eclipse.

if eclipse reason need import app android studio.

i want figure out 1 of last 2 point responsible app rejection.

also, if none of these responsible possible reason app rejection.

thanks in advance.

an apk apk, regardless of developed code. can write code in eclipse, android studio, or can write code in favorite plain text editor. end apk indistinguishable regardless of editor use.

the error in case seems pretty clear- version of cordova has known vulnerabilities , need update that.

run cordova platform version android check version. error message receiving show less 4.1.1.

the best path upgrade 5.x, as detailed here.


-

Comments

Post a Comment

Popular posts from this blog

serialization - Convert Any type in scala to Array[Byte] and back -

i have following question: i have variable value in program declared value. i want convert value byte array.. how can serialize byte array , back? found examples related other types such double or int, not any. this should need. it's pretty similar how 1 in java. import java.io.{bytearrayinputstream, bytearrayoutputstream, objectinputstream, objectoutputstream} object serialization extends app { def serialise(value: any): array[byte] = { val stream: bytearrayoutputstream = new bytearrayoutputstream() val oos = new objectoutputstream(stream) oos.writeobject(value) oos.close stream.tobytearray } def deserialise(bytes: array[byte]): = { val ois = new objectinputstream(new bytearrayinputstream(bytes)) val value = ois.readobject ois.close value } println(deserialise(serialise("my test"))) println(deserialise(serialise(list(1)))) println(deserialise(serialise(map(1 -> 2)))) println(deserialise(seri
Read more

matplotlib support failed in PyCharm on OSX -

any idea how fix ? how can debug might problem ? not seem : https://youtrack.jetbrains.com/issue/py-15520 i in console: python 2.6.9 (unknown, jul 14 2015, 19:46:31) [gcc 4.2.1 compatible apple llvm 6.0 (clang-600.0.39)] on darwin >>> import matplotlib.pyplot plt matplotlib support failed the backend : >>> import matplotlib >>> print(matplotlib.rcparams['backend']) macosx
Read more

python - Matplotlib: TypeError: 'AxesSubplot' object is not callable -

i new programming please pardon me if rookie mistake. i writing python script have defined functions create subplots of distributions. i have slider widget end user change value of variables(mu , sigma) , see effect on distribution. here's code import numpy np print np.__version__ import scipy print scipy.__version__ scipy.stats import norm, lognorm, uniform import matplotlib print matplotlib.__version__ import matplotlib.pyplot plt matplotlib.widgets import slider, button, radiobuttons, checkbuttons #####calculating mean , standard deviation##### global mu_a1 mu_a1 = 1 global mu_b1 mu_b1 = 10 global mu_c1 mu_c1 = -13 global sigma_a1 sigma_a1 = 0.14 global sigma_b1 sigma_b1 = 1.16 global sigma_c1 sigma_c1 = 2.87 mu_x01 = -11 sigma_x01 = 1.9 #####_____##### #####generating random data##### a1 = 0.75*mu_a1 + (1.25 - 0.75)*sigma_a1*np.random.sample(10000) b1 = 8*mu_b1 + (12 - 8)*sigma_b1*np.random.sample(10000) c1 = -12*mu_c1 + 2*sigma_c1*np.random.sample(10000)
Read more