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 151–200 of 216 papers

TitleStatusHype
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
Maximal Divergence Sequential Autoencoder for Binary Software Vulnerability Detection—0
MetaReflection: Learning Instructions for Language Agents using Past Reflections—0
Multi-Class classification of vulnerabilities in Smart Contracts using AWD-LSTM, with pre-trained encoder inspired from natural language processing—0
Multi-context Attention Fusion Neural Network for Software Vulnerability Identification—0
MVD: A Multi-Lingual Software Vulnerability Detection Framework—0
On the Compression of Language Models for Code: An Empirical Study on CodeBERT—0
On the Lack of Robustness of Binary Function Similarity Systems—0
Potential Auto-driving Threat: Universal Rain-removal Attack—0
Probing Model Signal-Awareness via Prediction-Preserving Input Minimization—0
Prompt Injection Attacks in Defended Systems—0
RealVul: Can We Detect Vulnerabilities in Web Applications with LLM?—0
Reasoning Under Threat: Symbolic and Neural Techniques for Cybersecurity Verification—0
Evolving Diverse Red-team Language Models in Multi-round Multi-agent Games—0
Retrieval Augmented Generation Integrated Large Language Models in Smart Contract Vulnerability Detection—0
SafeGenBench: A Benchmark Framework for Security Vulnerability Detection in LLM-Generated Code—0
SCoPE: Evaluating LLMs for Software Vulnerability Detection—0
SecureFalcon: Are We There Yet in Automated Software Vulnerability Detection with LLMs?—0
Security Vulnerability Detection Using Deep Learning Natural Language Processing—0
Security Vulnerability Detection with Multitask Self-Instructed Fine-Tuning of Large Language Models—0
Smart Learning to Find Dumb Contracts (Extended Version)—0
Smart-LLaMA-DPO: Reinforced Large Language Model for Explainable Smart Contract Vulnerability Detection—0
Smart-LLaMA: Two-Stage Post-Training of Large Language Models for Smart Contract Vulnerability Detection and Explanation—0
SmartLLMSentry: A Comprehensive LLM Based Smart Contract Vulnerability Detection Framework—0
SmartLLM: Smart Contract Auditing using Custom Generative AI—0
Software Vulnerability Detection via Deep Learning over Disaggregated Code Graph Representation—0
Software Vulnerability Prediction Knowledge Transferring Between Programming Languages—0
SoK: On Closing the Applicability Gap in Automated Vulnerability Detection—0
SV-LLM: An Agentic Approach for SoC Security Verification using Large Language Models—0
Machine Learning Techniques for Python Source Code Vulnerability DetectionCode0
Leveraging Generative AI to Enhance Automated Vulnerability ScoringCode0
Boosting Vulnerability Detection of LLMs via Curriculum Preference Optimization with Synthetic Reasoning DataCode0
The EarlyBIRD Catches the Bug: On Exploiting Early Layers of Encoder Models for More Efficient Code ClassificationCode0
LLMs in Software Security: A Survey of Vulnerability Detection Techniques and InsightsCode0
MTVHunter: Smart Contracts Vulnerability Detection Based on Multi-Teacher Knowledge TranslationCode0
Defining and Detecting Vulnerability in Human Evaluation Guidelines: A Preliminary Study Towards Reliable NLG EvaluationCode0
Enhancing Large Language Models with Faster Code Preprocessing for Vulnerability DetectionCode0
Multi-role Consensus through LLMs Discussions for Vulnerability DetectionCode0
VulDeePecker: A Deep Learning-Based System for Vulnerability DetectionCode0
Large Language Models for Cyber Security: A Systematic Literature ReviewCode0
Vulnerability Detection via Topological Analysis of Attention MapsCode0
Automated Vulnerability Detection in Source Code Using Deep Representation LearningCode0
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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