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Embedding code into vectors

Vector representations of code

As we have stated over and over in the past, the most critical step in our ongoing project of building a machine learning (ML) based code classifier will be that of representing the code as...



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The Vectors of Language

Distributed representations of natural language

Recall that in previous iterations we described the required steps for our code classifier to work, which can be roughly summarized as: Fetching data. Representing code as vectors. Training the...



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Triage for Hackers

Prioritize code auditing via ML

Based upon our last experiment, in this article, I will provide a global vision of how our ML for vulnerability discovery approach should work. First, what problem would this solve? I am repeating...



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Vulnerability classifiers

A pipeline to classify vulnerable code

After our encounter with the Python machine learning ecosystem, we are now ready for a first attempt at creating a vulnerability classifier from samples of labeled code. Our objective is to...



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Digression to Regression

Simple linear regression in scikit

After our risk quantification series, it should come as no surprise that we like numbers and measuring. However, when confronted with the question, "Why do you need to translate code into...



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Vulnerabilities in Deep Learning

Deep Learning for vulnerability disclosure

Currently, data scientists have begun using AI (Artificial Intelligence) algorithms to solve problems from the data perspective. Data scientists have been working on problems related to areas like...



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Fool the Machine

Trick neural network classifiers

Artificial Neural Networks (ANNs) are certainly a wondrous achievement. They solve classification and other learning tasks with great accuracy. However, they are not flawless and might misclassify...



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Big Code

Learning from open source

In our Machine Learning (ML) for secure code series the mantra has always been the same: to figure out how to leverage the power of ML to detect security vulnerabilities in source code, regardless...



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Natural Code

Natural language processing for code security

Our return to the Machine Learning (ML) for secure code series is a bit of a digression, but one too interesting to resist. It is not too far a digression though, because the Natural Language...



Nicolás Acosta, CISO at Corona

Innovation more understandable

"We make innovation more understandable, more worldly."

Our guest Nicolás is the Chief Information Security Officer (CISO) of Corona; a Colombian Multinational company dedicated to manufacturing ceramics for home improvement, construction, industry,...



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Preventing Hacks at CERN

A chat with Andrés Gómez.

Have you heard about God’s particle? In 2012, the Large Hadron Collider (LHC) found the Higgs Boson; a particle predicted to exist in the 1960s thanks to the work of Peter Higgs and other...



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Binary learning

Learning to exploit binaries

While our main focus, as stated previously, is to apply machine learning (ML) techniques to the discovery of vulnerabilities in source code, that is, a white-box approach to ML-guided hacking,...




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