Submission + - ETH/SRL uses machine learning for JavaScript code de-obfuscation
velco writes: ETH Zurich Software Reliability Lab announced JSNice (jsnice.org), statistical
de-obfuscation and de-minification tool for JavaScript.
The interesting thing about JSNice is that it combines program analysis with
machine learning techniques to build a database of name and type regularities
from large amounts of available open source code on GitHub.
Then, given new JavaScript code, JSNice tries to infer the most likely names and
types for that code by basing its decision on the learned regularities in the
training phase.
de-obfuscation and de-minification tool for JavaScript.
The interesting thing about JSNice is that it combines program analysis with
machine learning techniques to build a database of name and type regularities
from large amounts of available open source code on GitHub.
Then, given new JavaScript code, JSNice tries to infer the most likely names and
types for that code by basing its decision on the learned regularities in the
training phase.
