SecureAudit-AI Development Risk Assessment

As part of building SecureAudit-AI in public, I wanted to share the risk assessment I performed before diving into development. This exercise forced me to think through what could go wrong and what controls I need in place from the start.

Scope

Ensure risks are properly considered and addressed in the context of developing the SecureAudit-AI system. Assumptions:

• Using a combination of VSCode and ClaudeCode to develop and manage the deployment of source code.
• Deploy Kubernetes infrastructure to Azure.
• Store source code on a public GitHub repository.
• Using Claude API keys

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Risk Assessment Matrix

Likelihood Definitions

• Low: Unlikely to occur without specific circumstances aligning
• Medium: Could reasonably occur during normal operations
• High: Likely to occur without preventive controls in place

Impact Definitions

• Low: Minor inconvenience, minimal cost, easily recoverable
• Medium: Significant disruption, moderate cost increase, requires effort to recover
• High: Major service failure, data breach, substantial unplanned costs, or reputational damage

Risk Rating Matrix

	Low Impact	Medium Impact	High Impact
High Likelihood	Medium Risk	High Risk	Critical Risk
Medium Likelihood	Low Risk	Medium Risk	High Risk
Low Likelihood	Low Risk	Low Risk	Medium Risk

Identified Risks

RISK-001: Disclosure of sensitive information - API keys, Cloud Credentials, etc.

Attribute	Value
Category	Information Disclosure
Likelihood	High
Impact	High
Risk Rating	Critical
Status	Open

Risk Assessment:

Assessment	Details
Likelihood	High - Without the proper protections in place, the likelihood of accidentally committing sensitive information to a public repository is high.
Impact	High - Disclosure of sensitive information could directly result in financial impact. The two most likely scenarios are: (1) API keys leveraged to consume pre-loaded Claude API tokens. (2) Cloud credentials leveraged to spin up Azure resources without knowledge, driving up hosting bills

Affected Resources:

• Claude_API Key
• Cloud Secrets
• GitHub PATs
• Kubeconfig Files

Recommended Actions:

1. Use .gitignore files plus .env files to manage secrets in local repositories.
2. Implement Pre-Commit hooks on my development machine to scan for secrets before committing to GitHub.
3. Enable GitHub Secret Protection (available for free on public repos).
4. Post-commit GitHub Action to detect secrets via a different scanning engine.

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RISK-002: Lack of approval gates could lead to a flawed or compromised build being automatically deployed to AKS.

Attribute	Value
Category	CI/CD
Likelihood	High
Impact	High
Severity	Critical Risk
Status	Open

Risk Assessment:

Assessment	Details
Likelihood	High - Without deployment approval gates or quality checks in the CI/CD pipeline, every code push to the main branch could trigger an automatic deployment to AKS. Given active development and frequent commits, the likelihood of deploying untested or flawed code is high.
Impact	High - Flawed or compromised code could lead to exposed credentials, open access to the cluster, or leak sensitive information.

Affected Resources:

• Kubernetes
• Azure

Recommended Actions:

1. Implement a manual approval gate that is enforced prior to code being pushed to production.
2. Implement SAST Scanning as a CI job.
3. Implement Automated Testing as a CI job.

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RISK-003: AI systems behaving unpredictably resulting in destructive actions

Attribute	Value
Category	Development
Likelihood	High
Impact	Moderate
Severity	High Risk
Status	Open

Risk Assessment:

Assessment	Details
Likelihood	High - Without any controls in place to prevent Claude Code from making destructive commands, the likelihood that they occur is high. I plan to extensively use Claude Code to help streamline the development and deployment of Kubernetes resources and application code. With increased reliance on ClaudeCode and limited experience with AI-assisted development workflows, the likelihood of unintended destructive actions is high.
Impact	Moderate - At this time this is a personal project so the only impact would be to me. It could force me to spend extra cycles to fix broken code, but ultimately the impact is Moderate

Affected Resources:

• Claude Code
• Kubernetes
• Azure
• Source Code

Recommended Actions:

1. Implement a solution to prevent destructive tool calls using Claude Code native functionality:
   • Permissions
   • Subagents
   • Hooks
2. Alternatively, implement a third-party solution to prevent destructive tool calls