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 101–150 of 216 papers

TitleStatusHype
An Empirical Study of Vulnerability Detection using Federated Learning—0
An Initial Exploration of Fine-tuning Small Language Models for Smart Contract Reentrancy Vulnerability Detection—0
ANVIL: Anomaly-based Vulnerability Identification without Labelled Training Data—0
A Study on Mixup-Inspired Augmentation Methods for Software Vulnerability Detection—0
A Survey of Source Code Representations for Machine Learning-Based Cybersecurity Tasks—0
A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly—0
A Systematic Literature Review on Explainability for Machine/Deep Learning-based Software Engineering Research—0
Augmenting Greybox Fuzzing with Generative AI—0
Automated software vulnerability detection with machine learning—0
Automated Vulnerability Detection in Source Code Using Quantum Natural Language Processing—0
Automated Vulnerability Detection Using Deep Learning Technique—0
Automating the Detection of Code Vulnerabilities by Analyzing GitHub Issues—0
AI Cyber Risk Benchmark: Automated Exploitation Capabilities—0
Beyond Random Inputs: A Novel ML-Based Hardware Fuzzing—0
Bi-Directional Transformers vs. word2vec: Discovering Vulnerabilities in Lifted Compiled Code—0
BugWhisperer: Fine-Tuning LLMs for SoC Hardware Vulnerability Detection—0
C2RUST-BENCH: A Minimized, Representative Dataset for C-to-Rust Transpilation Evaluation—0
Can LLM Prompting Serve as a Proxy for Static Analysis in Vulnerability Detection—0
Case Study: Fine-tuning Small Language Models for Accurate and Private CWE Detection in Python Code—0
CGP-Tuning: Structure-Aware Soft Prompt Tuning for Code Vulnerability Detection—0
Closing the Gap: A User Study on the Real-world Usefulness of AI-powered Vulnerability Detection & Repair in the IDE—0
Code Vulnerability Repair with Large Language Model using Context-Aware Prompt Tuning—0
Pre-Training Representations of Binary Code Using Contrastive Learning—0
Comparison of Static Application Security Testing Tools and Large Language Models for Repo-level Vulnerability Detection—0
Computing Modes of Instability of Parameterized Nonlinear Systems for Vulnerability Assessment—0
CORE: Benchmarking LLMs Code Reasoning Capabilities through Static Analysis Tasks—0
CovRL: Fuzzing JavaScript Engines with Coverage-Guided Reinforcement Learning for LLM-based Mutation—0
Data Quality Issues in Vulnerability Detection Datasets—0
DCDetector: An IoT terminal vulnerability mining system based on distributed deep ensemble learning under source code representation—0
Deep-Learning-based Vulnerability Detection in Binary Executables—0
Tasks People Prompt: A Taxonomy of LLM Downstream Tasks in Software Verification and Falsification Approaches—0
Today's Cat Is Tomorrow's Dog: Accounting for Time-Based Changes in the Labels of ML Vulnerability Detection Approaches—0
Top Score on the Wrong Exam: On Benchmarking in Machine Learning for Vulnerability Detection—0
Towards Causal Deep Learning for Vulnerability Detection—0
Bin2vec: Learning Representations of Binary Executable Programs for Security Tasks—0
Trace Gadgets: Minimizing Code Context for Machine Learning-Based Vulnerability Prediction—0
Transfer Learning in Pre-Trained Large Language Models for Malware Detection Based on System Calls—0
Transformer-Based Language Models for Software Vulnerability Detection—0
Transformer-based Vulnerability Detection in Code at EditTime: Zero-shot, Few-shot, or Fine-tuning?—0
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
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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