Search Results - Vulnerable JavaScript

Vulnerable JavaScript functions detection using stacking of convolutional neural networks

Authors: Abdullah Sheneamer

Source: PeerJ Computer Science, Vol 10, p e1838 (2024)

Subject Terms: Vulnerable Javascript functions detection, Code security, Security of web applications, JavaScript engine vulnerability, Cross-site scripting detection, Stacking convolutional neural networks (CNNs), Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: https://peerj.com/articles/cs-1838.pdf; https://peerj.com/articles/cs-1838/; https://doaj.org/toc/2376-5992

Access URL: https://doaj.org/article/79d988f5828444de9300ba102e28bb1b

Challenging Machine Learning Algorithms in Predicting Vulnerable JavaScript Functions

Authors: Ferenc, Rudolf Hegedűs, Péter Gyimesi, Péter et al.

Index Terms: Computer Science - Cryptography and Security, Computer Science - Software Engineering, text

URL: http://arxiv.org/abs/2405.07213

On Measuring Vulnerable JavaScript Functions in the Wild

Authors: Maryna Kluban Mohammad Mannan Amr Youssef

Source: Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security. :917-930

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Challenging Machine Learning Algorithms in Predicting Vulnerable JavaScript Functions

Authors: Ferenc Rudolf Hegedűs Péter Gyimesi Péter et al.

Source: 2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE). :8-14

Subject Terms: Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Software Engineering, Computer Science - Cryptography and Security, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 15. Life on land, 16. Peace & justice, Cryptography and Security (cs.CR), 3. Good health

File Description: text

Access URL: http://arxiv.org/abs/2405.07213

Saving the world wide web from vulnerable JavaScript

Authors: Salvatore Guarnieri Marco Pistoia Omer Tripp et al.

Source: Proceedings of the 2011 International Symposium on Software Testing and Analysis. :177-187

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

On the Impact of Outdated and Vulnerable Javascript Packages in Docker Images

Authors: Ahmed Zerouali Valerio Cosentino Tom Mens et al.

Source: 2019 IEEE 26th International Conference on Software Analysis, Evolution and Reengineering (SANER).

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

On Detecting and Measuring Exploitable JavaScript Functions in Real-world Applications.

Authors: Kluban, Maryna Mannan, Mohammad Youssef, Amr

Source: ACM Transactions on Privacy & Security; Feb2024, Vol. 27 Issue 1, p1-37, 37p

Subject Terms: JAVASCRIPT programming language, PATTERN recognition systems, DENIAL of service attacks, DATA security, INTEGRATED software

SōjiTantei: Function-Call Reachability Detection of Vulnerable Code for npm Packages

Authors: Akinori IHARA Bodin CHINTHANET Kenichi MATSUMOTO et al.

Source: IEICE Transactions on Information and Systems. 2022, E105.D(1):19

Studying JavaScript Security Through Static Analysis

Authors: Fass, Aurore Backes, Michael

Contributors: Fass, Aurore Backes, Michael

Subject Terms: ddc:004, JavaScript, Malicious JavaScript, Browser Extensions, Computersicherheit, Statische Analyse, Static Analysis, Data Flow, Control Flow, Machine Learning, Web Security, Vulnerable JavaScript, AST, Adversarial Attacks

A Study of Vulnerability Repair in JavaScript Programs with Large Language Models

Authors: Le, Tan Khang Alimadadi, Saba Ko, Steven Y.

Index Terms: Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2403.13193

A Study of Vulnerability Repair in JavaScript Programs with Large Language Models

Authors: Tan Khang Le Saba Alimadadi Steven Y. Ko

Source: Companion Proceedings of the ACM Web Conference 2024. :666-669

Subject Terms: FOS: Computer and information sciences, Computer Science - Cryptography and Security, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Cryptography and Security (cs.CR)

Access URL: http://arxiv.org/abs/2403.13193

Real-Time Threat Detection with JavaScript: Monitoring and Response Mechanisms

Authors: A.I. Orynchak O.V. Kuzmenko O.M. Svintsytska

Source: Технічна інженерія, Vol 1, Iss 93, Pp 201-210 (2024)

Subject Terms: javascript, response mechanisms, monitoring, web security, real-time threat detection, Engineering (General). Civil engineering (General), TA1-2040

File Description: electronic resource

Relation: http://ten.ztu.edu.ua/article/view/307715; https://doaj.org/toc/2706-5847; https://doaj.org/toc/2707-9619

Access URL: https://doaj.org/article/c60666bd74cc4c9e874f73fb9bdb8151

Relative Validity of the Food Recording Smartphone App Libro in Young People Vulnerable to Eating Disorder: A Preliminary Cross-Over Study.

Authors: Basso, Melissa Zhang, Liangzi Savva, George M. et al.

Source: Nutrients. Jun2025, Vol. 17 Issue 11, p1823. 16p.

Detection of Obfuscated Malicious JavaScript Code.

Authors: Alazab, Ammar Khraisat, Ansam Alazab, Moutaz et al.

Source: Future Internet. Aug2022, Vol. 14 Issue 8, p217-N.PAG. 15p.

Subject Terms: *JavaScript programming language, *Machine learning, *Internet users, *Cyberterrorism, *Malware, *Websites, Intrusion detection systems (Computer security)

Social Engineering Attacks Using Technical Job Interviews: Real-Life Case Analysis and AI-Assisted Mitigation Proposals.

Authors: Sanguino, Tomás de J. Mateo¹ (AUTHOR)

Source: Information. Jan2026, Vol. 17 Issue 1, p98. 25p.

Subject Terms: *Malware, Social engineering (Fraud), Field research, Language models, Internet security, Employment interviewing

DeDup.js: Discovering Malicious and Vulnerable Extensions by Detecting Duplication

Authors: Picazo-Sanchez, Pablo Algehed, Maximilian Sabelfeld, Andrei

Source: 8th International Conference on Information Systems Security and Privacy (ICISSP), Online International Conference on Information Systems Security and Privacy. 1:528-535

Subject Terms: Browser Extensions, Web Privacy, Web Security

File Description: electronic

Access URL: https://research.chalmers.se/publication/531079
https://research.chalmers.se/publication/531079/file/531079_Fulltext.pdf

Social Engineering Attacks Using Technical Job Interviews: Real-Life Case Analysis and AI-Assisted Mitigation Proposals

Authors: Tomás de J. Mateo Sanguino

Source: Information, Vol 17, Iss 1, p 98 (2026)

Subject Terms: social engineering, technical job interviews, malicious code detection, obfuscated JavaScript, AI-assisted cybersecurity, crypto wallet compromise, Information technology, T58.5-58.64

File Description: electronic resource

Relation: https://www.mdpi.com/2078-2489/17/1/98; https://doaj.org/toc/2078-2489

Access URL: https://doaj.org/article/cf843ba0ca3248c6beebf00b8d3cc92b

SecBench.js: An Executable Security Benchmark Suite for Server-Side JavaScript.

Authors: Bhuiyan, Masudul Hasan Masud Parthasarathy, Adithya Srinivas Vasilakis, Nikos et al.

Source: ICSE: International Conference on Software Engineering; 2023, p1059-1070, 12p

Subject Terms: COMPUTER security, BENCHMARKING (Management), CLIENT/SERVER computing, JAVASCRIPT programming language, COMPUTER users

Javascript global identifier conflicts detection based on static analysis.

Authors: Sun, Shibo Yao, Shixiong Chen, Jiageng et al.

Source: Cybersecurity (2523-3246); 1/4/2026, Vol. 9 Issue 1, p1-12, 12p

Subject Terms: JAVASCRIPT programming language, WEB-based user interfaces, COMPUTER performance, SOURCE code

Dependency Network Structure and Security Vulnerabilities in Software Supply Chains.

Authors: Yoo, Eunae Craighead, Christopher W. Samtani, Sagar

Source: Journal of Management Information Systems; 2025, Vol. 42 Issue 4, p1149-1176, 28p

Subject Terms: COMPUTER security vulnerabilities, SUPPLY chains, STATISTICAL correlation, COMPUTER software developers, COMPUTATIONAL complexity