Audit360
Audit360: Automate. Secure. Comply.
What’s your problem statement?
Manual auditing for compliance with CIS benchmarks on endpoints is time-consuming, error-prone, and lacks scalability. Organizations need an automated solution to streamline compliance checks, accurately identify deviations, and efficiently assess associated security risks and threats.
The problem Audit360 solves
This project tackles the inefficiencies of manual auditing by automating CIS benchmark compliance checks on endpoints. Through tailored scripts, it provides:
1.Automated Audits: Reduces human intervention and errors by automating the auditing process, ensuring consistent and comprehensive checks across all endpoints.
2.AI-Driven Reporting: Generates detailed, AI-enhanced reports that highlight non-compliant areas and outline associated security risks and potential threats.
3.Improved Risk Management: Empowers organizations with actionable insights to address vulnerabilities, prioritize remediation efforts, and enhance endpoint security.
This solution enables organizations to simplify compliance, strengthen endpoint security, and maintain a proactive stance against cybersecurity threats.
Challenges we ran into
1.Cross-Platform Script Integration (Bash and PowerShell): Integrating scripts for multiple operating systems (Linux and Windows) presented challenges, as differences in command syntax and system permissions required custom adjustments for each environment. To overcome this, we developed modular scripts with conditional checks to detect the operating system and execute the appropriate code for each platform.
2.Fine-Tuning the Cybersecurity LLM: Adapting a language model specifically for cybersecurity tasks required extensive fine-tuning to accurately identify and report non-compliance issues and security threats. We addressed this by curating a robust dataset focused on cybersecurity use cases, then using transfer learning to adapt the model’s outputs for audit-related insights and recommendations.
3.Python and JavaScript Backend Compatibility: Combining Python scripts with a JavaScript backend created compatibility challenges, particularly in managing data exchange and function execution across both languages. We resolved these issues by using APIs to standardize data communication, allowing Python to handle the heavy-lifting of data processing while JavaScript managed frontend responsiveness and user interactions.
Tracks Applied (1)