AI Security Policy Generator

Traditional IT security policies were written for a world where data moved through known channels — email, file servers, SaaS apps with DPA agreements. AI tools fundamentally change this: your employees are pasting company data into ChatGPT, your developers are sending entire codebases through Copilot, and your analysts are uploading spreadsheets to Claude. These tools' data handling practices are opaque, their training data policies change without notice, and they don't sign your DPA. A dedicated AI security policy addresses this specific attack surface — data egress through LLM prompts — that your existing policy almost certainly doesn't cover.

Shield sits as a local desktop proxy between your applications and LLM providers. When an employee sends a prompt, Shield inspects the request in real-time and applies the data classification rules from your policy: PHI gets redacted before reaching the model, API keys are replaced with opaque tokens, and proprietary code is stripped — all on-device, before anything leaves your machine. The tamper-evident audit log proves exactly what was redacted and when, giving you the compliance evidence auditors require. You define the policy; Shield enforces it automatically.

Yes. The generated policy maps directly to SOC 2 (CC5.1–CC5.3), ISO 27001 (A.12.4, A.12.7), HIPAA Security Rule, and GDPR (Art. 30/32/33). Each section identifies the specific controls it satisfies. For frameworks not covered here — FedRAMP, NIST 800-53, CMMC — the data classification, incident response, and audit logging sections satisfy the underlying security controls those frameworks require. Shield's audit log provides the evidence trail for any framework that requires logging and monitoring of data access.

Shield operates at the enforcement layer: when configured with your data classification rules, it automatically redacts Tier 1 and Tier 2 data from all AI API calls — the employee can't accidentally (or intentionally) send PHI to ChatGPT because Shield strips it before the request leaves the device. For Tier 3–4 data, Shield logs the full request for audit purposes. This shifts the security model from 'trust employees to follow the policy' to 'the policy is enforced by the middleware.'

Quarterly review is the baseline. However, the AI security landscape moves faster than traditional IT security — new tools launch weekly, existing tools change their data retention policies without notice, and regulations (like the EU AI Act) phase in over multiple years. We recommend: quarterly formal review, ad-hoc review when adopting a new AI tool or vendor, and immediate review if a tool you use announces a data policy change. Shield's vendor policy monitoring can alert you when a connected provider updates their terms.

Yes. The policy applies to all AI functionality regardless of delivery mechanism — standalone chatbots, IDE plugins, embedded features in productivity suites, and API-based AI services. The key distinction is whether company data reaches an external AI model. Notion AI writing your meeting notes with internal data qualifies. Microsoft Copilot summarizing your confidential documents qualifies. The policy's data classification rules (Section 3) apply uniformly; the approved tools list (Section 4) should include embedded AI features as separate entries from the host product.