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.