Machine learning

Posts with this tag talk about the branch of artificial intelligence known as machine learning and cover several of its functions or uses within the field of cybersecurity.

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Felipe Ruiz


Attackers can indirectly instruct AI for malicious aims

We show you that LLM-integrated apps can suffer indirect prompt injection attacks through different methods that can put the security of their users at risk.

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Felipe Ruiz


NIST sheds light on the classification of attacks on AI

Here is an overview of a recent NIST report on adversarial machine learning that could help us understand more about attacks against and from AI systems.

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Julian Arango


A chat with Daniel Correa

We had the pleasure of chatting with Daniel Correa, a Security Expert who shared his views on current threats, human factors in cybersecurity, and technology.

Photo by Fern M. Lomibao on Unsplash

Rafael Ballestas


With symbolic execution

Here's a reflection on the need to represent code before actually feeding it into neural network based encoders, such as code2vec, word2vec, and code2seq.

Book in two languages

Rafael Ballestas


From code to words

Here we talk about Code2seq, which differs in adapting neural machine translation techniques to the task of mapping a snippet of code to a sequence of words.

Target and darts

Rafael Ballestas


Vector representations of code

Here is a tutorial on the usage of code2vec to predict method names, determine the accuracy of the model, and exporting the corresponding vector embeddings.

Arrows vector field

Rafael Ballestas


Vector representations of code

Here we discuss code2vec relation with word2vec and autoencoders to grasp better how feasible it is to represent code as vectors, which is our main interest.

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Rafael Ballestas


Distributed representations of natural language

This post is an overview of word2vec, a method for obtaining vectors that represent natural language in a way that is suitable for machine learning algorithms.

Photo by camilo jimenez on Unsplash

Rafael Ballestas


Prioritize code auditing via ML

This post is a high-level review of our previous discussion concerning machine learning techniques applied to vulnerability discovery and exploitation.

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