Collaborative penetration testing suite for emerging generative AI algorithms

TL;DR

This paper introduces a comprehensive suite combining classical and quantum cybersecurity tools to identify and mitigate vulnerabilities in generative AI models, enhancing security against emerging threats.

Contribution

It presents a novel integrated framework that combines traditional penetration testing, blockchain logging, quantum cryptography, and AI red teaming for secure generative AI.

Findings

Identified over 300 vulnerabilities in test environments.

Achieved 70% reduction in high-severity issues within two weeks.

Maintained 100% integrity of quantum-resistant cryptography.

Abstract

Problem Space: AI Vulnerabilities and Quantum Threats Generative AI vulnerabilities: model inversion, data poisoning, adversarial inputs. Quantum threats Shor Algorithm breaking RSA ECC encryption. Challenge Secure generative AI models against classical and quantum cyberattacks. Proposed Solution Collaborative Penetration Testing Suite Five Integrated Components: DAST SAST OWASP ZAP, Burp Suite, SonarQube, Fortify. IAST Contrast Assess integrated with CI CD pipeline. Blockchain Logging Hyperledger Fabric for tamper-proof logs. Quantum Cryptography Lattice based RLWE protocols. AI Red Team Simulations Adversarial ML & Quantum-assisted attacks. Integration Layer: Unified workflow for AI, cybersecurity, and quantum experts. Key Results 300+ vulnerabilities identified across test environments. 70% reduction in high-severity issues within 2 weeks. 90% resolution efficiency for blockchain-logged vulnerabilities. Quantum-resistant cryptography maintained 100% integrity in tests. Outcome: Quantum AI Security Protocol integrating Blockchain Quantum Cryptography AI Red Teaming.