Building AusCI’s Free Cyber Security Audit Platform with AI
Client
The Australian Cyber Security Institute (AusCI)
Delivered by
PIP Total IT Solutions – AI & Engineering
Project Overview
As part of an ongoing collaboration, PIP Total IT Solutions was engaged by the Australian Cyber Security Institute to design and build a free, publicly accessible cyber security audit platform for Australian organisations.
The objective was to create a practical, standards‑aligned assessment tool that reflected real audit experience, rather than generic or theoretical checklists. The platform needed to be accurate, extensible, easy to use, and capable of producing professional audit outputs suitable for business and executive audiences.
While the overall project involved planning, validation, iteration and refinement, a key milestone was demonstrating how modern AI‑assisted engineering can dramatically compress delivery timelines for well‑defined software components—without compromising quality or security.
You can view the end result here : Australian Cyber Security Institution – Free Cyber Security Audit Tool
Using AI as an Engineering and Analysis Tool
PIP approached the project by deliberately positioning AI as a structured design and analysis assistant, not as an autonomous decision‑maker.
We began by utilising Microsoft Copilot in Work Mode to help design the audit framework itself. Copilot was provided with a comprehensive body of source material, including:
- Previous cyber security audits performed by AusCI
- The ISO/IEC 27000 series, including ISO 27001 and ISO 27002 guidance
- AusCI’s own ASD Essential Eight manuals and training resources
- Additional recognised industry cyber security requirements and control frameworks
Copilot was instructed to analyse these materials holistically—identifying overlap, resolving inconsistencies, and extracting common control themes grounded in real‑world audit practice.
Defining the Core Audit Structure
Following this analysis, Copilot was able to consistently identify eight core audit sections that formed the foundation of the assessment model.
For each section, Copilot was then tasked with producing:
- A clearly defined audit question
- A plain‑English explanation of what the question was assessing
- The appropriate answer type (binary, maturity‑based, or descriptive input)
- An explanation justifying why that answer type was required
This structured output was generated as a clean CSV/Excel file, creating a definitive and traceable audit specification that could be directly consumed by software.
Rapid Translation from Model to Application
With the audit logic finalised, PIP moved into application development.
The CSV specification was provided to Claude (Code) along with a concise functional brief outlining:
- The end‑user experience, including registration, survey completion and results generation
- Automated production of professional PDF audit reports
- An administrative interface allowing AusCI to
- Add, edit or remove questions
- Manage audit sections
- View registered users and audit progress
- Access completed surveys and outputs
Claude was guided by explicit requirements rather than creative freedom, ensuring the resulting software aligned precisely with AusCI’s operational and governance needs.
A fully working application was produced to a high standard in approximately two hours, demonstrating how clearly defined requirements and AI‑assisted development can significantly accelerate delivery of functional software components.
Secure Deployment into AusCI’s Environment
Once validated, the application was committed to a secure internal repository for controlled distribution.
AusCI operates within a Linux containerised environment hosted on a hypervisor platform in PIPs private cloud. Deployment involved:
- Provisioning the required Linux containers
- Synchronising the secure repository to the target environment
- Applying configuration and security controls
The container environment was established and synchronised in under an hour, enabling the platform to be online and test bench ready that day.
While the broader project lifecycle extended beyond this point, this phase clearly demonstrated how a well defined software system can move from conception, through to specification and to live deployment within a single working session.
Iterative Refinement Using AI
As expected with any real world software project, additional refinements, security and edge cases emerged following initial deployment.
These were addressed using the same AI‑assisted workflow:
- Clearly describe the required change or issue
- Request solutions form either co-pilot or Claude and asses against decades of knowledge
- Engage Claude to implement the modification
- Commit updates to the repository
- Pull changes into the live container environment
This approach allowed functionality to evolve quickly while maintaining consistency and control.
Example Enhancement: Secure Email Verification
One practical enhancement involved improving registration security by validating user email addresses.
Rather than making assumptions, PIP asked both Co-Pilot and Claude to outline current best practices for email verification in security focused applications. Both Claude and Co-Pilot presented several options, with a clear recommendation for:
- Email verification using a secure, time limited authorisation link Emailed to the user.
This aligned with industry expectations and PIP’s own design principles, therefore, Claude was then instructed to implement the verification workflow, ensuring users could only access the audit once their email address had been validated.
This like all the enhancements was implemented cleanly and deployed without disruption.
Outcomes and Learnings
AusCI received a:
- Free, standards aligned cyber security audit platform
- Tool grounded in real audit experience and recognised frameworks
- System that is maintainable, extensible, and adaptable to future requirements
For PIP, the project reinforced an important reality:
AI does not replace engineering discipline – it amplifies it.
When used correctly, AI accelerates analysis, reduces friction, and compresses delivery timelines, while architecture, security, and governance remain firmly under human control.
A Practical Example of AI‑Led Engineering
This engagement illustrates how AI can be integrated responsibly into professional software delivery, supporting analysis, accelerating development and enabling rapid iteration. All without compromising quality, security or accountability.
For organisations like AusCI, it enables faster delivery of meaningful tools.
For PIP, it demonstrates how modern AI‑assisted workflows are reshaping what is possible in secure software engineering.
