Detection And Penetration Of 0-day Vulnerability Based On Buffer Overflow

Buffer overflow is a highly prevalent and perilous vulnerability.On one hand,attackers can exploit buffer overflow to pilfer data and even gain superuser privileges;on the other hand,vulnerability attacks evolve rapidly,and the real-time defense against buffer overflow attacks is insufficient,making them extensively exploited by hackers and viruses,posing significant threats.In response,a method combining neural networks for buffer overflow vulnerability discovery and defense strategies is proposed,with the main objectives outlined as follows.(1)For the detection of buffer overflow vulnerabilities,an automated mining method based on neural networks is introduced and implemented.This approach integrates three neural network models: MLP(Multilayer Perceptron),GCN(Graph Convolutional Network),and RNN(Recurrent Neural Network),forming a novel network model,RMG.The RMG model effectively and accurately identifies and extracts potential buffer overflow vulnerabilities from vast amounts of code,thereby enhancing the efficiency and accuracy of vulnerability mining.(2)Various buffer overflow vulnerabilities are analyzed to validate the effectiveness of the proposed RMG model.The RMG model is capable of detecting vulnerabilities such as Heartbleed,Eternal Blue,Shellshock,and Adobe Flash Player vulnerabilities.Defensive strategies are designed to effectively thwart attacks targeting these vulnerabilities.Subsequently,the RMG model is successfully employed to uncover multiple real-world buffer overflow vulnerabilities.This demonstrates that the RMG model can effectively defend against attacks exploiting these vulnerabilities,thereby bolstering system security.(3)A neural network-based defense strategy is introduced.By monitoring the system’s operational state in real-time,potential attack behaviors are detected.When such behaviors are identified,the proposed defense strategy is activated to prevent attacks.This adaptive defense strategy utilizes neural network technology to automatically adjust defense tactics in response to changing attack behaviors,thereby enhancing defense effectiveness.Additionally,identified vulnerabilities are repaired to prevent their exploitation.The aforementioned research holds substantial theoretical significance and practical application value in preventing and defending against buffer overflow vulnerabilities,while also enhancing system security.It not only presents a novel method for vulnerability discovery and defense but also provides insights and approaches for related research endeavors.