Static taint analysis can be used to find various security weaknesses and vulnerabilities in programs by discovering dataflow paths from taint sources to taint sinks. In most cases the data is called ”tainted” if it was obtained from an untrusted source without proper sanitization. In this paper we present a static taint analyzer Irbis. It implements analysis based on IFDS (Interprocedural Finite Distributive Subset) dataflow problem, as well as various extensions aimed at improving accuracy and completeness of the analysis. It supports different definitions of tainted data, which enables it to find such weaknesses as out of buffer access, use of freed memory, hardcoded passwords, data leaks and discover dataflow paths between user-defined sources and sinks. All sources, sinks and propagators definitions are stored in JSON format and can be adjusted to meet the users’ needs. We compare analysis results on Juliet Test Suite for C/C++ with several other analyzers, such as Infer, Clang Static Analyzer and Svace. Irbis manages to demonstrate 100% coverage on taint-related subset of tests for implemented CWEs, while suppressing all the false positives using heuristics. We also show performance and false positive rate on real projects, with examples of real vulnerabilities, which can be detected by Irbis.

A three-dimensional mathematical model of coastal water dynamics in the Peter the Great Bay of the Sea of Japan is presented. The system of Navier-Stokes equations is written under the assumption of a hydrodynamic approximation of an inhomogeneous fluid and takes into account turbulent exchange, wind stresses, friction forces, complex topography of the bottom and coastline. On the basis of hydrographic information, a numerical method is used to reconstruct the bottom topography and coastline. The free water surface equation is replaced by a singularly perturbed problem. In the FreeFem++ application software package, a code was written for calculating the hydrodynamic characteristics of coastal waters. During the solution, the finite element mesh is built automatically, the mesh parameters are set by the user. To solve the singular problem, at each time layer, the grid is adapted around the numerical solution with the grid adaptation parameters.

Source code static analysis is widely used for program errors detection. Mostly it is used for finding critical issues like security vulnerabilities, critical program defects leading to runtime errors like crash and unexpected behavior of programs. Many SCSA tools are used for checking code conformance to different coding style guides. In this case study we present results of applying SCSA techniques for checking performance coding rules of Huawei and evaluate whether manually fixing found issues in accordance with the guidelines could impact performance, or if the compiler already applies all necessary optimizations during compilation.

This study investigates the linguistic competence of modern language models. Artificial neural networks demonstrate high quality in many natural language processing tasks. However, their implicit grammar knowledge remains unstudied. The ability to judge a sentence as grammatical or ungrammatical is regarded as key property of human’s linguistic competence. We suppose that language models’ grammar knowledge also occurs in their ability to judge the grammaticality of a sentence. In order to test neural networks’ linguistic competence, we probe their acquisition of number predicate agreement in Russian. A dataset consisted of artificially generated grammatical and ungrammatical sentences was created to train the language models. Automatic sentence generation allows us to test the acquisition of particular language phenomenon, to detach from vocabulary and pragmatic differences. We use transfer learning of pre-trained neural networks. The results show that all the considered models demonstrate high accuracy and Matthew's correlation coefficient values which can be attributed to successful acquisition of predicate agreement rules. The classification quality is reduced for sentences with inanimate nouns which show nominative-accusative case syncretism. The complexity of the syntactic structure turns out to be significant for Russian models and a model for Slavic languages, but it does not affect the errors distribution of multilingual models.

Using Received Signal Strength Indicator (RSSI) values to detect human presence is a well-known Wi-Fi sensing technique. In this paper, an overview of existing algorithms solving the problem is considered. Two new techniques based on the discrete Kolmogorov-Wiener filter and the gated recurrent unit neural network are proposed. Human detection experiment results are presented along with algorithms' accuracy analysis.

In this paper, the process of gas flow in the flow path of a turbomolecular vacuum pump using the Cercignani-Lampis (CL) model was simulated. CL model was used as new boundary conditions when calculating the transition probability. The test particle method (Monte Carlo method) was used in the simulation. The calculation of the molecules transition probability through the blade channel in the forward and reverse directions, the transition resulting probability, the compression ratio was made.

Security analysis of network programs includes set of reverse engineering tasks of network protocols. Data formats restoring and implemented protocol automaton are the previous task issues. Unlike quite researched problem of formats restoring where there are lots of scientist’s papers, finding out the protocol's automaton program implementation looks like terra incognita and the cornerstone is a protocol state description currently undefined. There are two general ways to retrieve the implemented protocol automaton: an analysis of the network traces and looking into binary trace of the target application. This article offers a second one method. The first aim of the paper is the way to describe a mathematical model of a protocol automaton and a method for projecting it onto an executing application binary code. The second is concept of the protocol state definition and a principle to detect the states transitions based on some "global" binary trace objects, are described. Thirdly, there is suggested a protocol automaton precising manner by in-memory fuzzing based on a "floating" fork-server to manage states transitions. Finally, developed toolset's scheme and experiments on its using with a real VPN client, are shown.

The influence of relative longitudinal position on the frequency characteristics of two interacting ships floating stationary in close proximity in head waves and shallow water is investigated in this paper. A CFD approach has been adopted to simulate the dynamic behavior of the interacting ships. The numerical simulation for “Aleksey Kosygin” and “Novgorod” ships floating on head waves at a small relative transverse distance was carried out using two scaled models. The effect of longitudinal separation on the frequency characteristics of both ships was studied. Heave, roll, and pitch RAOs for various cases were analyzed, and recommendations for relative longitudinal positions were made on the basis of the present analysis.

Modern software is rapidly developing, revealing new program errors. More and more companies follow security development lifecycle (SDL). Fuzzing and symbolic execution are among the most popular options for supporting SDL. They allow to automatically test programs and find errors. Hybrid fuzzing is one of the most effective ways to test programs, which combines these two techniques. Checking security predicates during symbolic execution is an advanced technique, which focuses on solving extra constraints for input data to find an error and generate an input file to reproduce it. In this paper we propose a method for automatically detecting errors with the help of dynamic symbolic execution, combining hybrid fuzzing and checking security predicates. Firstly, we run hybrid fuzzing, which is required to increase number of corpora seeds. Then we minimize corpora. Thus, it would give the same coverage as the original corpora. After that we check security predicates on minimized corpora. Thus, security predicates allow to find errors like division by zero, out of bounds access, integer overflow, and more. Security predicates results are later verified with sanitizers to filter false positive results. As a result of applying the proposed method to different open source programs, we found 11 new different errors in 5 projects.

Representation of the DNA sequence is possible in various ways. The variation graph is one of the most accurate methods that allows you to work with atypical areas and take into account all their diversity. Based on this data structure and the polygenic risk assessment method, a DNA interpretation system was built. As a result, a correlation coefficient was obtained between the path in the column responsible for a specific DNA sequence and the feature. We then compared it with a coefficient obtained by a similar method but using sequence representation using a reference genome. Such a comparison helped to evaluate the effectiveness of the representation in the form of a graph. After that, a modified method for calculating the polygenic score on the alignment data of the vg tool was built, which was also compared with existing methods. The modified method showed an improvement in the prediction of the trait.