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be exploited to cause an unsafe memory behaviour.
For that, a safety knowledge base is constructed using
a formal representation of errors and recommenda-
tion reports and also requirement that can provided by
users. The created safety knowledge base is used to
improve the obtained formulas by adding safety con-
straints. The latter are checked by an SMT solver to
detect vulnerability bugs. We illustrate our approach
through an example. Definitely the efficiency of our
approach depends strongly on the relevancy of the
used safety knowledge base. The current work ad-
dresses the problem of extracting and using knowl-
edge of attack and software vulnerabilities directo-
ries to build safety properties patterns. An alterna-
tive solution would be to use interactive annotation
through an interface for the tool as it has been done
in (Thomas, 2015). The aim of our ongoing and fu-
ture work is to formalize more unsafe predicate in-
cluding pointer references, cast operations and more.
By expanding the knowledge data base, we can treat
a broader class of bugs, and can then identify more
vulnerabilities.
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