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Vulnerability Detection
3260 papers • 126 benchmarks • 313 datasets
Vulnerability detection plays a crucial role in safeguarding against these threats by identifying weaknesses and potential entry points that malicious actors could exploit. Through advanced scanning techniques and penetration testing, vulnerability detection tools meticulously analyze web applications and websites for vulnerabilities such as SQL injection, cross-site scripting (XSS), and insecure authentication mechanisms. By proactively identifying and addressing vulnerabilities, organizations can strengthen their online security posture and mitigate the risk of data breaches, financial loss, and reputational damage. Additionally, vulnerability detection empowers businesses to stay compliant with industry regulations and standards, demonstrating their commitment to safeguarding sensitive information and maintaining the trust of their customers. With the evolving threat landscape and increasingly sophisticated attack vectors, investing in robust vulnerability detection measures is paramount for staying one step ahead of cyber threats and ensuring the resilience of web-based platforms and services.
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2 papers 271
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Most implemented papers
VulDeePecker: A Deep Learning-Based System for Vulnerability Detection
Z. Li, Deqing Zou, Shouhuai Xu, Xinyu Ou, Hai Jin, Sujuan Wang, Yuyi Zhong•Thu Jan 04 2018
The study of using deep learning-based vulnerability detection to relieve human experts from the tedious and subjective task of manually defining features and Experimental results show that VulDeePecker can achieve much fewer false negatives and reasonable false positives than other approaches.
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