CoCo: Efficient Browser Extension Vulnerability Detection via Coverage-guided, Concurrent Abstract Interpretation

J Yu, S Li, J Zhu, Y Cao - Proceedings of the 2023 ACM SIGSAC …, 2023 - dl.acm.org
Extensions complement web browsers with additional functionalities and also bring new
vulnerability venues, allowing privilege escalations from adversarial web pages to use …

Detection of obfuscated malicious JavaScript code

A Alazab, A Khraisat, M Alazab, S Singh - Future Internet, 2022 - mdpi.com
Websites on the Internet are becoming increasingly vulnerable to malicious JavaScript code
because of its strong impact and dramatic effect. Numerous recent cyberattacks use …

Hidenoseek: Camouflaging malicious javascript in benign asts

A Fass, M Backes, B Stock - Proceedings of the 2019 ACM SIGSAC …, 2019 - dl.acm.org
In the malware field, learning-based systems have become popular to detect new malicious
variants. Nevertheless, attackers with specific and internal knowledge of a target system may …

Deep learning with customized abstract syntax tree for bug localization

H Liang, L Sun, M Wang, Y Yang - IEEE Access, 2019 - ieeexplore.ieee.org
Given a bug report, bug localization technique can help developers automatically locate
potential buggy files. Information retrieval and deep learning approaches have been applied …

Jstap: a static pre-filter for malicious javascript detection

A Fass, M Backes, B Stock - Proceedings of the 35th Annual Computer …, 2019 - dl.acm.org
Given the success of the Web platform, attackers have abused its main programming
language, namely JavaScript, to mount different types of attacks on their victims. Due to the …

Wobfuscator: Obfuscating javascript malware via opportunistic translation to webassembly

A Romano, D Lehmann, M Pradel… - 2022 IEEE Symposium …, 2022 - ieeexplore.ieee.org
To protect web users from malicious JavaScript code, various malware detectors have been
proposed, which analyze and classify code as malicious or benign. State-of-the-art detectors …

A systematic literature review and quality analysis of Javascript malware detection

MF Sohan, A Basalamah - IEEE Access, 2020 - ieeexplore.ieee.org
Context: JavaScript (JS) is an often-used programming language by millions of web pages
and is also affected by thousands of malicious attacks. Objective: In this investigation, we …

Scaling javascript abstract interpretation to detect and exploit node. js taint-style vulnerability

M Kang, Y Xu, S Li, R Gjomemo, J Hou… - … IEEE Symposium on …, 2023 - ieeexplore.ieee.org
Taint-style vulnerabilities, such as OS command injection and path traversal, are common
and severe software weaknesses. There exists an inherent trade-off between analysis …

An empirical study on the effects of obfuscation on static machine learning-based malicious javascript detectors

K Ren, W Qiang, Y Wu, Y Zhou, D Zou… - Proceedings of the 32nd …, 2023 - dl.acm.org
Machine learning is increasingly being applied to malicious JavaScript detection in
response to the growing number of Web attacks and the attendant costly manual …

Supply-chain vulnerability elimination via active learning and regeneration

N Vasilakis, A Benetopoulos, S Handa… - Proceedings of the …, 2021 - dl.acm.org
Software supply-chain attacks target components that are integrated into client applications.
Such attacks often target widely-used components, with the attack taking place via …