Jalangi2 NPM | npm.io

Jalangi2

Introduction

Jalangi2 is a framework for writing dynamic analyses for JavaScript. Jalangi1 is still available at https://github.com/SRA-SiliconValley/jalangi, but we no longer plan to develop it. Jalangi2 does not support the record/replay feature of Jalangi1. In the Jalangi2 distribution you will find several analyses:

an analysis to track NaNs.
an analysis to check if an undefined is concatenated to a string.
Memory analysis: a memory-profiler for JavaScript and HTML5.
DLint: a dynamic checker for JavaScript bad coding practices.
JITProf: a dynamic JIT-unfriendly code snippet detection tool.
analysisCallbackTemplate.js: a template for writing a dynamic analysis.
and more ...

See our tutorial slides for a detailed overview of Jalangi and some client analyses.

Requirements

We have tested Jalangi on Mac OS X with Chromium browser. Jalangi should work on Mac OS 10.7, Ubuntu 11.0 and higher and Windows 7 or higher. Jalangi will NOT work with IE.

Node.js available at https://nodejs.org/en/download/releases/. We primarily test Jalangi with the Node LTS version (currently v12).
Chrome browser if you need to test web apps.
Python (http://python.org) version 2.7 or higher and less than 3.0.

On Windows you need the following extra dependencies:

Install Microsoft Visual Studio 2010 (Free express version is fine).
If on 64bit also install Windows 7 64-bit SDK.

If you have a fresh installation of Ubuntu, you can install all the requirements by invoking the following commands from a terminal (package names may be out of date).

sudo apt-get update
sudo apt-get install python-software-properties python g++ make
sudo add-apt-repository ppa:chris-lea/node.js
sudo apt-get update
sudo apt-get install nodejs
sudo apt-get update
sudo apt-get install chromium-browser

Installation

Clone the repository, and then run:

npm install

Run tests

python scripts/test.traceall.py
python scripts/test.analysis.py
python scripts/test.dlint.py

Usage

Analysis in node.js with on-the-fly instrumentation

An analysis can be performed on a JavaScript file in node.js by issuing the following commands:

node src/js/commands/jalangi.js --inlineIID --inlineSource --analysis src/js/sample_analyses/ChainedAnalyses.js --analysis src/js/sample_analyses/dlint/Utils.js --analysis src/js/sample_analyses/dlint/CheckNaN.js --analysis src/js/sample_analyses/dlint/FunCalledWithMoreArguments.js --analysis src/js/sample_analyses/dlint/CompareFunctionWithPrimitives.js --analysis src/js/sample_analyses/dlint/ShadowProtoProperty.js --analysis src/js/sample_analyses/dlint/ConcatUndefinedToString.js --analysis src/js/sample_analyses/dlint/UndefinedOffset.js tests/octane/deltablue.js

In the above analysis, we chained several analyses by including --analysis src/js/analyses/ChainedAnalyses.js as the first analysis. The command runs the following analyses

src/js/sample_analyses/dlint/CheckNaN.js
src/js/sample_analyses/dlint/FunCalledWithMoreArguments.js
src/js/sample_analyses/dlint/CompareFunctionWithPrimitives.js
src/js/sample_analyses/dlint/ShadowProtoProperty.js
src/js/sample_analyses/dlint/ConcatUndefinedToString.js
src/js/sample_analyses/dlint/UndefinedOffset.js

The implementation of an analysis requires the implementation of several callback functions. One can start writing an writing analysis using the template file src/js/runtime/analysisCallbackTemplate.js. A documentation of these call back functions can be found at docs/MyAnalysis.html. A tutorial on writing a Jalangi analysis can be found at docs/tutorial1.md. While writing an analysis one could run src/js/sample_analyses/pldi16/TraceAll.js analysis on a JavaScript file to print all the callback functions that got called during the execution of the file. Such a trace is useful to see what callbacks get called during an execution. The following command runs the TraceAll.js analysis on the file tests/octane/deltablue.js.

node src/js/commands/jalangi.js --inlineIID --inlineSource --analysis src/js/sample_analyses/ChainedAnalyses.js --analysis src/js/runtime/SMemory.js --analysis src/js/sample_analyses/pldi16/TraceAll.js tests/octane/deltablue.js

Analysis in node.js with explicit one-file-at-a-time offline instrumentation

An analysis can be performed on a JavaScript file in node.js by issuing the following commands:

node src/js/commands/esnstrument_cli.js --inlineIID --inlineSource tests/octane/deltablue.js
node src/js/commands/direct.js --analysis src/js/sample_analyses/ChainedAnalyses.js --analysis src/js/sample_analyses/dlint/Utils.js --analysis src/js/sample_analyses/dlint/CheckNaN.js --analysis src/js/sample_analyses/dlint/FunCalledWithMoreArguments.js --analysis src/js/sample_analyses/dlint/CompareFunctionWithPrimitives.js --analysis src/js/sample_analyses/dlint/ShadowProtoProperty.js --analysis src/js/sample_analyses/dlint/ConcatUndefinedToString.js --analysis src/js/sample_analyses/dlint/UndefinedOffset.js tests/octane/deltablue_jalangi_.js

In the above analysis, we chained several analyses by including --analysis src/js/analyses/ChainedAnalyses.js.

Analysis in a browser using offline instrumentation

An analysis can be performed on a web app using the Chrome browser by issuing the following commands:

node src/js/commands/instrument.js --inlineIID --inlineSource -i --inlineJalangi --analysis src/js/sample_analyses/ChainedAnalyses.js --analysis src/js/sample_analyses/dlint/Utils.js --analysis src/js/sample_analyses/dlint/CheckNaN.js --analysis src/js/sample_analyses/dlint/FunCalledWithMoreArguments.js --analysis src/js/sample_analyses/dlint/CompareFunctionWithPrimitives.js --analysis src/js/sample_analyses/dlint/ShadowProtoProperty.js --analysis src/js/sample_analyses/dlint/ConcatUndefinedToString.js --analysis src/js/sample_analyses/dlint/UndefinedOffset.js --outputDir /tmp tests/tizen/annex
open file:///tmp/annex/index.html

While performing analysis in a browser, one needs to press Alt-Shift-T to end the analysis and to print the analysis results in the console.

Analysis in a browser using a proxy and on-the-fly instrumentation

You can also setup a proxy to instrument JavaScript files on-the-fly. To do so, you need to install mitmproxy. We highly recommend version 0.11.3; later versions may not work with Jalangi. On Linux, you can follow the standard installation instructions, but instead of running sudo pip install mitmproxy, run sudo pip install mitmproxy==0.11.3 to get the right version. On Mac OS, the easiest path we have found is to use Homebrew. With Homebrew installed, you can install the right version by running:

brew install python
pip install -U pip
pip install mitmproxy==0.11.3

Note that you might need to restart your shell afterward, to ensure the python being used is /usr/local/bin/python.

For instrumenting code served over HTTPS, you will additionally need to set up a root certificate for mitmproxy. See their instructions or this document.

After installation, you can run the Jalangi instrumentation proxy by issuing the following command:

mitmdump --quiet --anticache -s "scripts/proxy.py --inlineIID --inlineSource --analysis src/js/sample_analyses/ChainedAnalyses.js --analysis src/js/runtime/analysisCallbackTemplate.js"

In your browser, the http and https proxy should be set to 127.0.0.1:8080. Now if you load a website in your browser, all JavaScript files associated with the website will get instrumented on-the-fly.

On a Mac, the proxy can be set and launched automatically by issuing the following command:

./scripts/mitmproxywrapper.py --toggle --auto-disable --quiet --anticache -s "scripts/proxy.py --inlineIID --inlineSource --analysis src/js/sample_analyses/ChainedAnalyses.js --analysis src/js/runtime/analysisCallbackTemplate.js"

The command starts mitmproxy if the proxy is not currently enabled, and disables it otherwise. The --auto-disable option will automatically disable the proxy when the script is interrupted.

Jalangi2 caches the instrumented source files in ./cache/. The use of the cache can be disabled during development by passing the --no-cache flag to scripts/proxy.py.