At accessiBe, we understand that granting an application access to your proprietary source code requires an immense amount of trust. We designed accessFlow Code Agent from the ground up with a “Privacy-First, Stateless IP” architecture to ensure that your intellectual property remains completely secure and compliant with enterprise security standards (SOC2, GDPR, ISO 27001).

Here is a transparent breakdown of exactly how we handle your data, your source code, and your GitHub platform access.

Zero source code retention (stateless IP)

We never store, persist, or back up any of your source code.

When you open a Pull Request, accessFlow Code Agent temporarily streams the Git Diff into our isolated, ephemeral container memory to perform the AI-driven accessibility audit.

Once the audit is complete, the originalCode and the generated suggestedFix snippets are immediately pushed directly to your GitHub repository as PR Review Comments. The instant that network request completes, the code is wiped from our server’s RAM via standard garbage collection.

What do we store?

We strictly store Metadata (the “GPS coordinates” of a bug). Our database schema only records:

• The repository name and PR number.
• The ID of the accessibility rule that failed (e.g., image-alt).
• The severity of the issue (e.g., critical).
• The file path (e.g., src/components/Button.tsx).
• The line number.
• The lifecycle status of the issue (OPEN, RESOLVED, DISMISSED).

By completely decoupling the metadata from the actual source code, it is mathematically impossible for an attacker to extract your proprietary algorithms or business logic from our databases. GitHub remains the absolute single source of truth for your IP.

LLM processing & AI privacy

We utilize Enterprise-grade Large Language Models (LLMs) to perform the accessibility audits.

• No training on your data: Our LLM providers (e.g., Google Vertex AI / Gemini) are contractually bound under Enterprise Service Level Agreements (SLAs). Your source code and PR diffs are never used to train, fine-tune, or improve public AI models.
• Ephemeral processing: Your code is processed in secure, ephemeral inference environments and is discarded immediately after the review is generated.
• Continuous improvement via feedback: While your code is never used to train public models, our engine continuously learns from your team's direct interactions. By analyzing explicit feedback (like thumbs up/down reactions) and resolution states (whether an issue was dismissed or fixed), we dynamically refine our internal evaluation rules and prompts to adapt to your specific coding patterns over time.

GitHub permissions & access

The accessFlow Code Agent GitHub App operates with the absolute minimum privileges required to function (Principle of Least Privilege).

Required permissions

• Pull requests (read & write): Required to fetch the Git Diff so the bot can see the code changes, post inline review comments, suggest code fixes, and resolve/unresolve threads.
• Contents (read-only): Required to fetch the full content of modified files (beyond just the diff) and resolve repository configuration files (like .codeAgent.yml and .gitignore).
• Checks (read & write): Required to create and update the “accessFlow Code Agent AI Reviewer” status panel in the Checks tab.
• Issues (read & write): Required because GitHub API treats top-level Pull Request conversation comments as “Issue Comments”. This allows the bot to read and respond to global slash commands (like /codeAgent pause).

⚠️ Important note on permission updates: If you ever modify these permissions in your GitHub App Developer Settings, the changes do not take effect immediately. The repository or organization administrator MUST navigate to their “Installed GitHub Apps” settings and explicitly click Accept new permissions for accessFlow Code Agent to continue functioning.

Token security

• We do not ask for or store Personal Access Tokens (PATs).
• accessFlow Code Agent uses dynamic, short-lived installation tokens generated securely via GitHub App private key cryptography. These tokens expire automatically and are rotated continuously, ensuring that even if a token were intercepted, it would quickly become useless.

4. Telemetry & analytics

To help your organization track its ROI and accessibility health, we collect high-level telemetry data. This data is strictly aggregated and contains absolutely no sensitive information or PII.

Telemetry events logged:

• AUDIT_STARTED / COMPLETED / FAILED
• ISSUE_CREATED / ISSUE_AUTO_RESOLVED / ISSUE_MANUALLY_DISMISSED
• REACTION_ADDED (when a developer reacts with a 👍/👎 to an AI comment).
• LLM_USAGE_METRICS (Token counts and latency for billing/performance tracking).

⚠️ Important Note on collected analytics: Telemetry events only reference the UUIDs of the metadata rows mentioned in Section 1 (rows in the PR along with the file name). They never log the actual code.

Right to erasure & GDPR

We only store metadata and relational IDs.

For more information about how we handle your data and respect your rights, we encourage you to view our Privacy Notice.

Uninstalling the accessFlow Code Agent does not automatically delete your stored data. If you want us to delete historical telemetry and metadata associated with your account, you must submit a deletion request to our support team.

Once we receive and process your request, we will delete the applicable data in accordance with our data retention policies and relevant data protection requirements.

If your Infosec or Compliance teams have any further questions or require a formal security questionnaire, please contact our enterprise support team.