AI Guardrails

Overview

Codexium integrates AI systems with explicit guardrails to prevent misuse, reduce the risk of prompt injection, and protect both client and end-user data. Our approach combines technical controls, pattern detection, and human oversight where needed.

Threat Model for AI Systems

• Prompt injection, jailbreaks, and content policy bypass attempts.
• Data exfiltration via model responses or tool calls.
• Over-privileged tools or connectors exposed through agents.
• Hallucinations that could lead to unsafe or incorrect actions.

Guardrail Techniques

• Input validation, sanitization, and pattern-based blocking.
• Strict system instructions that define allowed behavior and enforce boundaries.
• Policy-based filters on prompts and responses to block disallowed content categories.
• Scoped tool access: agents receive only the APIs and datasets required for each use case.
• Adversarial testing and red-teaming before features go live.

Data Protection in AI Workflows

• Minimizing and masking sensitive data before it is sent to model providers where feasible.
• Disabling long-term training on client data unless explicitly contracted.
• Protecting AI logs as part of the broader logging and retention program.

Human Oversight

For high-impact actions, AI is restricted to read-only or recommendation-only modes. Human approval is required before executing infrastructure changes, financial operations, or irreversible actions in production.

Shared Responsibilities

Client

• Define acceptable use policies for AI within the organization.
• Approve which systems and datasets may be integrated.

Codexium

• Design, implement, and monitor guardrails for AI features.
• Iterate on protections as models and threats evolve.

Cloud / AI Provider

• Provide model-level safety features, rate limiting, and content filters.
• Offer contractual assurances on data usage and retention.