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Detekcija mehanizmov delovanja zlonamerne programske opreme
ID Bašagić, Dino (Author), ID Sedlar, Urban (Mentor) More about this mentor... This link opens in a new window

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Abstract
Magistrsko delo podaja teoretični pregled zlonamerne programske opreme ter izdelavo lastnega vzorca in testiranje detekcije mehanizmov zlonamerne programske opreme. Izpostavljene so najznamenitejše vrste zlonamerne programske opreme, vključno z izsiljevalsko, vohunsko in brezdatotečno programsko opremo, trojanskimi konji, črvi, virusi, omrežji avtomatskih robotov, logičnimi bombami in hibridi, skupaj z njihovimi najbolj znanimi predstavniki. Obravnavani so tudi tipični mehanizmi zlonamerne programske opreme, kot so poviševanje privilegijev, kraja in spreminjanje podatkov, vztrajnost, oddaljen nadzor, izogibanje detekciji ter destruktivna dejanja. Analizirane so različne metode detekcije zlonamerne programske opreme: zaznavanje na podlagi podpisov, statična in dinamična analiza ter sistemi za zaznavanje in odziv končnih točk (angl. Endpoint Detection and Response – EDR) in razširjeno zaznavanje in odziv (angl. Extended Detection and Response – XDR). V praktičnem delu je implementiran prototipni vzorec zlonamerne programske opreme, ki vsebuje naslednje mehanizme: šifriranje datotek, vzpostavitev t. i. povezave povratne lupine (angl. reverse shell), spreminjanje registra, samoreplikacijo in izvajanje z zakasnitvijo. Ta vzorec je testiran v izoliranem laboratorijskem okolju na različnih brezplačnih in plačljivih varnostnih orodjih – testirana je stopnja uspešnosti njihove detekcije. Rezultati so presenetljivi in zaskrbljujoči, saj niti brezplačne niti plačljive različice antivirusnih programov oziroma EDR/XDR-sistemov niso bile uspešne pri zaznavanju relativno preprostega novega vzorca zlonamerne programske opreme. Skoraj vsaka preizkušena rešitev je bila uspešna le pri detekciji posameznih mehanizmov, nobena pa ni dosegla 100-odstotne uspešnosti. To jasno kaže, da se za prvo detekcijo nove zlonamerne programske opreme ne moremo z zagotovilom zanašati na tovrstne programe ter da datotek ali aplikacij, ki niso preverjene oziroma za katere sumimo, da bi lahko bile škodljive, ne bi smeli odpirati ali zaganjati. Če to ni mogoče, jih je treba dodatno preveriti oziroma testirati v varnem okolju.

Language:Slovenian
Keywords:zlonamerna programska oprema, mehanizmi zlonamerne programske opreme, detekcija zlonamerne programske opreme, testiranje zlonamerne programske opreme
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FE - Faculty of Electrical Engineering
Year:2026
PID:20.500.12556/RUL-179167 This link opens in a new window
COBISS.SI-ID:267786243 This link opens in a new window
Publication date in RUL:06.02.2026
Views:334
Downloads:116
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Secondary language

Language:English
Title:Detection of malware mechanisms of action
Abstract:
The master’s thesis provides a theoretical overview of malicious software (malware), along with the development of a custom malware sample and the evaluation of detection capabilities for malware mechanisms. It highlights the most prominent types of malicious software, including ransomware, spyware, fileless malware, trojans, worms, viruses, botnets, logic bombs, and hybrid forms, as well as their most well-known representatives. The thesis also examines common malware mechanisms, such as privilege escalation, data theft and manipulation, persistence, remote control, evasion of detection, and destructive actions. Furthermore, various malware detection methods are analysed, including signature-based detection, static and dynamic analysis, and EDR (Endpoint Detection and Response)/XDR (Extended Detection and Response) systems. In the practical section, a prototype malware sample was implemented, containing the following mechanisms: file encryption, establishment of a reverse-shell connection, registry modification, self-replication, and delayed execution. This sample was tested in an isolated laboratory environment using various free and commercial (professional/industrial) security tools, and the effectiveness of their detection was evaluated. The results were both surprising and concerning, as neither free nor commercial antivirus solutions nor EDR/XDR systems were successful in detecting a relatively simple zero-day malware sample. Most of the tested solutions were able to detect individual mechanisms, yet none achieved 100% accuracy. This clearly demonstrates that such tools cannot be fully relied upon for the initial detection of new malware, and that files or applications that are unverified or suspected to be malicious should not be opened or executed. If opening/running such files cannot be avoided, they must be additionally examined or tested within a secure environment.

Keywords:malware, malware mechanisms, malware detection, malware testing

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