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https://github.com/samkg/nn-sat-verifier


https://github.com/samkg/nn-sat-verifier

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# NN-SAT-Verifier
It has been shown that adversarial inputs to neural networks can be generated using SMT solvers [1]. This project aims to explore these attacks in a simplified setting, based on Microsoft's open source z3 solver. See analysis/verification.py for the bulk of the logic of the solver.

[1] Guy Katz, Clark Barrett, David Dill, Kyle Julian, and Mykel Kochenderfer. Reluplex: Anefficient smt solver for verifying deep neural networks, 2017