> For the complete documentation index, see [llms.txt](https://trust.impact.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://trust.impact.com/ai-trust-center/security.md).

# Security

Our AI is built on the same enterprise-grade security foundation that protects the entire impact.com platform. We believe innovation and security move together, never one at the expense of the other.

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**Proactive AI governance:** Our legal and compliance teams actively track emerging global AI regulation, so our practices stay ahead of requirements rather than racing to catch up.
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## Key security measures

In-platform AI and MCP are subject to our rigorous, multi-layered security program. Our platform, including its AI features, is regularly audited by independent third parties. For an in-depth view of our certifications, see [Certifications](/data-security-and-privacy/certifications.md).

<table data-view="cards"><thead><tr><th></th><th></th></tr></thead><tbody><tr><td><strong>🔒 Encryption</strong></td><td>Your data is protected in transit (TLS 1.2+) and at rest (AES-256).</td></tr><tr><td><strong>🔑 Access controls</strong></td><td>Our AI is not a backdoor. It fully respects the Role-Based Access Controls (RBAC) in your account: if a user can't see certain data, neither can the AI acting for them.</td></tr><tr><td><strong>🛡️ Content filtering &#x26; misuse prevention</strong></td><td>For in-platform AI features, we apply advanced safety filtering to Gen AI inputs and outputs (including Google's Model Armor) to guard against harmful, misleading, or abusive content.</td></tr><tr><td><strong>📡 Monitoring &#x26; alerting</strong></td><td>In-platform AI features are covered by continuous monitoring, with automated abuse protection and alerting feeding our security and reliability processes.</td></tr><tr><td><strong>🧪 Rigorous testing</strong></td><td>Before release, every in-platform AI feature goes through internal code review, integration testing, independent penetration testing by white-hat experts, and adversarial testing to identify and mitigate misuse.</td></tr></tbody></table>


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