Foundations of Secure AI Use

Secure AI Usage for Development Teams

Protecting Code, Architecture, Customer Data & Company IP

 Why Secure AI Matters

• AI accelerates development dramatically

• But code + data leaks = irreversible damage

• Free tools are NOT designed for corporate confidentiality

• Developers must apply strict security discipline

Improvement: Highlight the real risk
— leaks to external models.

Typical Developer Errors That Lead to Leaks

• Copy-pasting full files or proprietary modules

• Debugging with real logs or customer data

• Using free AI tools for work

• Uploading configs, environment files, API keys

• Syncing entire repos to AI-enabled IDEs

• Thinking “private mode” = 100% safe (false)

Core Principles of Safe AI Usage

1. Minimum exposure

2. Sanitize everything (remove identifiers)

3. Never use free or consumer AI accounts

4. Use enterprise-grade tools ONLY

5. Manually review every AI output

6. Zero customer data

7. Zero secrets

8. Zero confidential architecture details

Allowed vs Forbidden

Allowed

• Small, isolated snippets

• Pseudocode

• Generic architectures

• Debugging after sanitizing

• Test generation

• Documentation generation

Forbidden

• Real logs, stack traces with IDs

• Customer data (names, TINs, accounts, any PII)

• Credentials, keys, tokens

• Internal business algorithms

• Full microservice files

• Deployment descriptors, infra diagrams

• Proprietary company logic

Practical & Safe Use of AI Tools

What’s Safe to Ask AI?

✔ General coding questions
✔ Design patterns
✔ Performance optimizations
✔ Refactoring of small snippets
✔ Test improvements
✔ Architecture concepts (not company-specific)

What’s Unsafe to Ask AI?

✖ Bugs requiring internal knowledge
✖ Full service files
✖ Private architectural diagrams
✖ Sensitive logs
✖ Configurations (.yml, .env, Vault, Docker, K8s)
✖ Customer-related workflows

Sanitizing Code Correctly

Before sending anything to AI:

Sanitizing Code Correctly

realCustomerId → customerId
fire.customers → module.api

Obfuscate
package names
variable names

3-Step Secure Workflow

Safe Use of ChatGPT

• Use only company-approved accounts

• Ensure data training is disabled

• Turn off chat history when needed

• Use custom company policies in system prompts

• Never sync full repositories

• No secrets, credentials, environment files

Safe Use of Claude Code

• Use Claude Team / Business (NOT free version)

• Strong reasoning for refactors and understanding

• Upload only extracted, sanitized files

• For logs → redact all identifiers

• Never upload architecture diagrams or configs

Safe Use of Cursor AI

• Cursor is powerful, but dangerous if misconfigured

• Allow indexing only of selected folders

• NEVER let Cursor access:

  • configs

  • infra

  • deployments

  • whole monorepos

• Required: manual review of AI-generated PRs

GitHub Copilot: What Developers Must Know

• Suggests external code → licensing risks

• Avoid on proprietary code or core modules

• Disable auto-commit features

• Validate all suggestions

• Avoid using Copilot Chat for confidential topics (unless enterprise)

Quality, Compliance & Privacy

How AI Can Improve QA Safely

• Test generation

• Fuzzing suggestion

• Edge case discovery

• Complexity & readability analysis

• Security smell detection (with proper supervision)

Hidden Risks in AI Output

• Hallucinated code

• Insecure patterns

• Deprecated APIs

• Wrong exceptions

• Incorrect domain assumptions

• GPL or external snippets

AI Privacy Reality Check

• Usage

• File uploads

• Prompts

• Timestamps

• Metadata

Even enterprise tools still log:

AI Privacy Reality Check

• data training OFF

• history OFF (when needed)

• private org workspace

• access control configured

AI privacy settings MUST be checked:

Safe Example

Unsafe → full CustomerController.java

Unsafe Example

Safe → function-only snippet with renamed fields

 Policy, Responsibilities & Best Tools

Internal AI Responsibility Policy

• No free AI tools for work

• Use only approved enterprise solutions

• Sanitize all code

• Avoid structural data exposure

• Mandatory code review for AI output

• Report unsafe behavior immediately

Best AI Tools for Developer Teams (2025)

• ChatGPT Enterprise / Team

• Claude Business / Team

• Cursor AI (Enterprise + restricted workspace)

• GitHub Copilot Enterprise

• AWS Q Developer (enterprise-grade security)

Safest Choices

Allowed With Caution

• JetBrains AI (enterprise mode)

Best AI Tools for Developer Teams (2025)

🚫 free ChatGPT
🚫 free Claude
🚫 free Cursor
🚫 free Copilot Chat
🚫 any consumer-grade AI

Forbidden

Developer Responsibilities

• Use AI securely

• Protect IP

• Protect architecture

• Avoid external dependencies

• Verify every answer

• Follow company AI policy

• Ask when unsure — never assume

Final Security Checklist

• Before sending anything to AI:

  • Did I sanitize the content?

  • Is the tool enterprise-approved?

  • Am I exposing customer or internal data?

  • Have I reduced the problem to the minimum needed?

  • Will I manually validate the answer?

AI is a superpower —
but only if used safely, privately, and professionally.