SOTAVerified

Vulnerability Detection

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.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 126–150 of 216 papers

TitleStatusHype
Unsupervised Features Extraction for Binary Similarity Using Graph Embedding Neural Networks—0
Unveiling Project-Specific Bias in Neural Code Models—0
Using ChatGPT as a Static Application Security Testing Tool—0
Using ML filters to help automated vulnerability repairs: when it helps and when it doesn't—0
Vignat: Vulnerability identification by learning code semantics via graph attention networks—0
VUDENC: Vulnerability Detection with Deep Learning on a Natural Codebase for Python—0
VuLASTE: Long Sequence Model with Abstract Syntax Tree Embedding for vulnerability Detection—0
VulCatch: Enhancing Binary Vulnerability Detection through CodeT5 Decompilation and KAN Advanced Feature Extraction—0
μVulDeePecker: A Deep Learning-Based System for Multiclass Vulnerability Detection—0
Vulnerability Detection: From Formal Verification to Large Language Models and Hybrid Approaches: A Comprehensive Overview—0
Vulnerability Detection in Ethereum Smart Contracts via Machine Learning: A Qualitative Analysis—0
Vulnerability Detection in Smart Contracts: A Comprehensive Survey—0
Vulnerability Detection Using Two-Stage Deep Learning Models—0
Vulnerability Detection in C/C++ Code with Deep Learning—0
VulnLLMEval: A Framework for Evaluating Large Language Models in Software Vulnerability Detection and Patching—0
VulnSense: Efficient Vulnerability Detection in Ethereum Smart Contracts by Multimodal Learning with Graph Neural Network and Language Model—0
Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAG—0
XGV-BERT: Leveraging Contextualized Language Model and Graph Neural Network for Efficient Software Vulnerability Detection—0
Your Instructions Are Not Always Helpful: Assessing the Efficacy of Instruction Fine-tuning for Software Vulnerability Detection—0
Automated Software Vulnerability Static Code Analysis Using Generative Pre-Trained Transformer Models—0
ZeroLeak: Using LLMs for Scalable and Cost Effective Side-Channel Patching—0
A Qualitative Study on Using ChatGPT for Software Security: Perception vs. Practicality—0
A comparative study of neural network techniques for automatic software vulnerability detection—0
A Comparative Study of Static Code Analysis tools for Vulnerability Detection in C/C++ and JAVA Source Code—0
To Err is Machine: Vulnerability Detection Challenges LLM Reasoning—0
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All datasetsVulScribeRVulnerability Java Dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Reveal Model - Tested on Reveal (Training on Devign + VulScribeR 20K + Extra Cleans)F1 Score26.18—Unverified
2Devign Model - Tested on Reveal (Training on Devign + VulScribeR 20K + Extra Cleans)F1 Score24.99—Unverified
3Reveal Model - Tested on Bigvul (Training on Devign + VulScribeR 20K + Extra Cleans)F1 Score18.98—Unverified
4Devign Model - Tested on Bigvul (Training on Devign + VulScribeR 20K + Extra Cleans)F1 Score18.51—Unverified
5LineVul - Tested on Reveal (Training on Devign + VulScribeR 20K + Extra Cleans)F1 Score17.38—Unverified
6LineVul - Tested on BigVul (Training on Devign + VulScribeR 20K+ Extra Cleans)F1 Score16.23—Unverified
#ModelMetricClaimedVerifiedStatus
1WizardCoderAUC0.86—Unverified
2ContraBERTAUC0.85—Unverified