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

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Showing 51–100 of 216 papers

TitleStatusHype
Old but Gold: Reconsidering the value of feedforward learners for software analyticsCode0
VulDeePecker: A Deep Learning-Based System for Vulnerability DetectionCode0
Are Sparse Autoencoders Useful for Java Function Bug Detection?Code0
SySeVR: A Framework for Using Deep Learning to Detect Software VulnerabilitiesCode0
SV-TrustEval-C: Evaluating Structure and Semantic Reasoning in Large Language Models for Source Code Vulnerability AnalysisCode0
The EarlyBIRD Catches the Bug: On Exploiting Early Layers of Encoder Models for More Efficient Code ClassificationCode0
Revisiting the Performance of Deep Learning-Based Vulnerability Detection on Realistic DatasetsCode0
Can You Really Trust Code Copilots? Evaluating Large Language Models from a Code Security PerspectiveCode0
SAFE: Self-Attentive Function Embeddings for Binary SimilarityCode0
Responsible Development of Offensive AICode0
Multi-role Consensus through LLMs Discussions for Vulnerability DetectionCode0
MTVHunter: Smart Contracts Vulnerability Detection Based on Multi-Teacher Knowledge TranslationCode0
Program Semantic Inequivalence Game with Large Language ModelsCode0
Boosting Vulnerability Detection of LLMs via Curriculum Preference Optimization with Synthetic Reasoning DataCode0
Machine Learning Techniques for Python Source Code Vulnerability DetectionCode0
Enhancing Large Language Models with Faster Code Preprocessing for Vulnerability DetectionCode0
LLMs in Software Security: A Survey of Vulnerability Detection Techniques and InsightsCode0
Large Language Models for Cyber Security: A Systematic Literature ReviewCode0
DSHGT: Dual-Supervisors Heterogeneous Graph Transformer -- A pioneer study of using heterogeneous graph learning for detecting software vulnerabilitiesCode0
Statement-Level Vulnerability Detection: Learning Vulnerability Patterns Through Information Theory and Contrastive LearningCode0
How to Select Pre-Trained Code Models for Reuse? A Learning PerspectiveCode0
Leveraging Generative AI to Enhance Automated Vulnerability ScoringCode0
Reasoning with LLMs for Zero-Shot Vulnerability DetectionCode0
Automated Vulnerability Detection in Source Code Using Quantum Natural Language Processing—0
Deep-Learning-based Vulnerability Detection in Binary Executables—0
An Empirical Study of Deep Learning Models for Vulnerability Detection—0
DCDetector: An IoT terminal vulnerability mining system based on distributed deep ensemble learning under source code representation—0
Data Quality Issues in Vulnerability Detection Datasets—0
Automated software vulnerability detection with machine learning—0
Augmenting Greybox Fuzzing with Generative AI—0
Adaptive Plan-Execute Framework for Smart Contract Security Auditing—0
A Systematic Literature Review on Explainability for Machine/Deep Learning-based Software Engineering Research—0
CovRL: Fuzzing JavaScript Engines with Coverage-Guided Reinforcement Learning for LLM-based Mutation—0
An Automated Vulnerability Detection Framework for Smart Contracts—0
CORE: Benchmarking LLMs Code Reasoning Capabilities through Static Analysis Tasks—0
Computing Modes of Instability of Parameterized Nonlinear Systems for Vulnerability Assessment—0
A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly—0
Comparison of Static Application Security Testing Tools and Large Language Models for Repo-level Vulnerability Detection—0
Pre-Training Representations of Binary Code Using Contrastive Learning—0
A Survey of Source Code Representations for Machine Learning-Based Cybersecurity Tasks—0
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair—0
ActiveClean: Generating Line-Level Vulnerability Data via Active Learning—0
A comparative study of neural network techniques for automatic software vulnerability detection—0
GenTAL: Generative Denoising Skip-gram Transformer for Unsupervised Binary Code Similarity Detection—0
Graph Neural Networks Enhanced Smart Contract Vulnerability Detection of Educational Blockchain—0
FuzzTheREST: An Intelligent Automated Black-box RESTful API Fuzzer—0
From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future—0
Harnessing Large Language Models for Software Vulnerability Detection: A Comprehensive Benchmarking Study—0
Harnessing the Power of LLMs in Source Code Vulnerability Detection—0
Code Vulnerability Repair with Large Language Model using Context-Aware Prompt Tuning—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