ADVANCED BACKDOOR USING PYTHON

Authors

  • Rajeshwar Singh
  • Madan Lal

Keywords:

Reverse Connection, Persistence, Registry, Vulnerability

Abstract

A malware is a piece of code or software whose main functionality is to infect a system to manipulate, steal or destroy data and in turn violate the security of that system. Malwares are heavily used to gain access to systems for the purpose of security breach or vulnerability testing.Backdoor is a type of malware that create a way for hacker to get inside a device and execute commands without knowing of the owner. In this paper we have created a malware using python and different libraries that addresses different types of issues in current backdoors and solves it.

References

Kolli, Yaswanth, Tauheed Khan Mohd, and Ahmad Y. Javaid. "Remote Desktop Backdoor Implementation with Reverse TCP Payload using Open Source Tools for Instructional Use." 2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). IEEE, 2018

C. Atwell, T. Blasi, and T. Hayajneh, "Reverse TCP and Social Engineering Attacks in the Era of Big Data," pp. 1- 6, 2016.

R. Winding, T. Wright, and C. Michael, "System Anomaly Detection: Mining Firewall Logs," pp. 1-5, 2006

X. Yue, W. Chen, and Y. Wang, "The Research of Firewall Technology in Computer Security," pp. 1-4, 2009

Lee, YounSu, et al. "A Lightweight Malware Classification Method Based on Detection Results of Anti-Virus Software." 2017 12th Asia Joint Conference on Information Security (AsiaJCIS). IEEE, 2017

Khokhar, Umar Mujahid, and Binh Tran. "Fundamentals of Ethical Hacking and Penetration Testing." Proceedings of the 20th Annual SIG Conference on Information Technology Education. 2019.

Fleshman, William, et al. "Static malware detection & subterfuge: Quantifying the robustness of machine learning and current anti-virus." 2018 13th International Conference on Malicious and Unwanted Software (MALWARE). IEEE, 2018

Jang, Moonsu, Hongchul Kim, and Youngtae Yun. "Detection of DLL inserted by Windows malicious code." 2007 International Conference on Convergence Information Technology (ICCIT 2007). IEEE, 2007

Alashwali, Eman, and Hanene Ben-Abdallah. "Design and evaluation of competition-based hacking exercises." 2015 IEEE Global Engineering Education Conference (EDUCON). IEEE, 2015

Kim, Jinoh, et al. "Practical network attack situation analysis using sliding window cache scheme." 9th Asia-Pacific Conference on Communications (IEEE Cat. No. 03EX732). Vol. 3. IEEE, 2003.

Khera, Yugansh, Deepansh Kumar, and Nidhi Garg. "Analysis and Impact of Vulnerability Assessment and Penetration Testing." 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon). IEEE, 2019

Kotkar, Chetan, and Pravin Game. "Prevention mechanism for prohibiting SMS malware attack on android smartphone." 2015 annual IEEE India conference (INDICON). IEEE, 2015.

Zhu, Hui, Cheng Huang, and Hui Li. "MPPM: Malware propagation and prevention model in online SNS." 2014 IEEE International Conference on Communications Workshops (ICC). IEEE, 2014.

Barabosch, Thomas, and Elmar Gerhards-Padilla. "Host-based code injection attacks: A popular technique used by malware." 2014 9th International Conference on Malicious and Unwanted Software: The Americas (MALWARE). IEEE, 2014.

Gamayunov, Dennis. "Towards malware-resistant networking environment." 2011 First SysSec Workshop. IEEE, 2011.

Bedi, Anav, Nitin Pandey, and Sunil Kumar Khatri. "Analysis of Detection and Prevention of Malware in Cloud Computing Environment." 2019 Amity International Conference on Artificial Intelligence (AICAI). IEEE, 2019.

Avasarala, Bhargav R., John C. Day, and Donald Steiner. "System and method for automated machine-learning, zero-day malware detection." U.S. Patent No. 9,292,688. 22 Mar. 2016.

Tyagi, Akshay, et al. "Prevention of Drive by Download Attack (URL Malware Detector)." 2019 Third International Conference on Inventive Systems and Control (ICISC). IEEE, 2019.

O'Donnell, Adam J. "When malware attacks (anything but windows)." IEEE Security & Privacy 6.3 (2008): 68-70.

Markel, Zane, and Michael Bilzor. "Building a machine learning classifier for malware detection." 2014 Second Workshop on Anti-malware Testing Research (WATeR). IEEE, 2014.

Yousefi-Azar, Mahmood, et al. "Malytics: a malware detection scheme." IEEE Access 6 (2018): 49418-49431.

Chang, Chih-Pai, et al. "Study on constructing malware attack forensic procedure of digital evidence." 2013 International Conference on System Science and Engineering (ICSSE). IEEE, 2013.

Sethia, Vasu, and A. Jeyasekar. "Malware Capturing and Analysis using Dionaea Honeypot." 2019 International Carnahan Conference on Security Technology (ICCST). IEEE, 2019.

Asaduzzaman, Abu, Muhammad F. Mridh, and M. Nazim Uddin. "An inexpensive plug-and-play hardware security module to restore systems from malware attacks." 2013 International Conference on Informatics, Electronics and Vision (ICIEV). IEEE, 2013.

Zabidi, Muhammad Najmi Ahmad, Mohd Aizaini Maarof, and Anazida Zainal. "Challenges in high accuracy of malware detection." 2012 IEEE Control and System Graduate Research Colloquium. IEEE, 2012.

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Published

2023-12-30

How to Cite

Rajeshwar Singh, & Madan Lal. (2023). ADVANCED BACKDOOR USING PYTHON. Journal Punjab Academy of Sciences, 23, 368–373. Retrieved from https://jpas.in/index.php/home/article/view/91