Govern what your AI agents can touch
AI Security & AI Agent Risk
AI agents and copilots now read your files, call your APIs, and act on your behalf — which means they can also leak credentials, reach systems they were never meant to, and act beyond their mandate. RHC Solutions secures the AI you deploy: we contain agentic AI risk, lock down credential and secrets access, and enforce least-privilege controls over the files and network resources an AI can reach — with monitoring and audit-ready guardrails so autonomy never becomes exposure.
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What we deliver
Agentic AI Risk Management
Inventory every AI agent, copilot, and autonomous workflow, then constrain their tools and actions with policy guardrails, human-in-the-loop approvals, and kill-switches — and harden them against prompt injection so an agent can never act beyond its mandate.
AI Credential & Secrets Protection
Stop agents from harvesting or leaking API keys, tokens, and passwords. Short-lived scoped credentials, secret-vault brokering, and just-in-time access mean an AI never holds standing secrets it could exfiltrate.
File & Data Access Governance
Least-privilege access to documents, repositories, and knowledge bases. Per-agent scopes, data-loss controls, and redaction ensure an AI only reads the files it is authorized to see — and nothing else.
Network & Resource Access Control
Egress filtering, allow-listed endpoints, and segmentation contain what AI agents can reach across your network and cloud — blocking SSRF, cloud-metadata theft, lateral movement, and unauthorized API calls.
AI risks we test for — mapped to the OWASP LLM Top 10
| Risk (OWASP LLM) | What it looks like | How RHC defends |
|---|---|---|
| Prompt injection (LLM01) | Hidden instructions hijack the model or its tools | Input/output filtering, system-prompt hardening, tool sandboxing |
| Sensitive info disclosure (LLM02) | Model leaks secrets, PII or training data | Data minimization, output scanning, retrieval scoping |
| Supply chain & model integrity (LLM03) | Poisoned models, plugins or datasets | Provenance checks, dependency pinning, model vetting |
| Improper output handling (LLM05) | Model output executed downstream (XSS / SSRF) | Output encoding, strict schemas, no eval of model text |
| Excessive agency (LLM06) | An agent takes unintended, high-impact actions | Least-privilege tools, human-in-the-loop approval |
| Unbounded consumption (LLM10) | Cost or availability abuse via expensive prompts | Rate limits, token/cost budgets, monitoring |
Frequently Asked Questions
What is AI agent security?
How do you stop AI agents from accessing credentials?
Can you control which files and network resources an AI can reach?
Do you cover third-party copilots and LLM tools?
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Request an AI security assessment: agent inventory, credential and access review, and a prioritized remediation roadmap.