CFM880

project frameworks/base/
diff --git a/core/java/android/app/Activity.java b/core/java/android/app/Activity.java
index db5dcc5c264b..404db6dfaf64 100644
--- a/core/java/android/app/Activity.java
+++ b/core/java/android/app/Activity.java
@@ -741,6 +741,7 @@ public class Activity extends ContextThemeWrapper
         OnCreateContextMenuListener, ComponentCallbacks2,
         Window.OnWindowDismissedCallback,
         AutofillManager.AutofillClient, ContentCaptureManager.ContentCaptureClient {

tuxity

#!/bin/bash

set -e

file=$(defaults read /Applications/Navicat\ Premium.app/Contents/Info.plist)

regex="CFBundleShortVersionString = \"([^\.]+)"
[[ $file =~ $regex ]]

version=${BASH_REMATCH[1]}

wshayes

# https://github.com/tiangolo/fastapi/issues/258#issuecomment-495975801

from typing import List

from fastapi import FastAPI
from starlette.responses import HTMLResponse
from starlette.websockets import WebSocket, WebSocketDisconnect


app = FastAPI()

elevenchars

Android RE using Frida

I figured that I would write down my findings somewhere since this is my first time using Frida. This won't cover installing frida, adb, apktool because these are well covered in other sources.

Tools

• https://github.com/frida/frida/
• https://github.com/sensepost/objection
• https://github.com/dweinstein/awesome-frida

Injecting Frida gadget into APKs

yutao8

Registered Name: https://zhile.io
License Key: 48891cf209c6d32bf4

koenrh

Running Hashcat on Google Cloud's GPU-based VMs

In February 2017, Google announced the availability GPU-based VMs. I spun up a few of these instances, and ran some benchmarks. Along the way, I wrote down the steps taken to provision these VM instances, and install relevant drivers.

Update April 2019: Updated instructions to use instances with the Tesla T4 GPUs.

chilts

var request = require('request');
var unzip   = require('unzip');
var csv2    = require('csv2');

request.get('http://s3.amazonaws.com/alexa-static/top-1m.csv.zip')
    .pipe(unzip.Parse())
    .on('entry', function (entry) {
        entry.pipe(csv2()).on('data', console.log);
    })
;