Enterprise AI Security
Enterprise AI security is the practice of protecting LLM applications, AI agents, and the data pipelines that feed them — against prompt injection, sensitive-data leakage, over-permissioned agents, insecure model endpoints, and supply-chain risk — with identity, guardrails, and audit engineered in rather than bolted on. Traditional application security still applies, but AI adds new attack surface that most security programs haven't yet mapped.
The AI-specific threat surface
- Prompt injection — untrusted content (a web page, a document, an email) carries instructions that hijack the model or agent. The mitigation is treating all retrieved/observed content as data, never commands, and gating actions.
- Data leakage — models trained or prompted on sensitive data can expose it; RAG can leak across tenants if corpora aren't isolated.
- Over-permissioned agents — agents running on shared service accounts with broad standing permissions can take actions no one authorized. The fix is governed AI agents: per-agent identity, scoped ephemeral credentials, tiered autonomy.
- Insecure model endpoints — unauthenticated or unrate-limited endpoints invite abuse and cost attacks.
- Supply chain — model weights, prompts, and vector stores are all artifacts that need integrity and provenance.
What good enterprise AI security looks like
| Control | Why it matters |
|---|---|
| Per-agent identity (SPIFFE/SPIRE) | Attribute every action to a specific agent |
| Scoped, ephemeral credentials (RFC 8693) | No static keys to leak; least privilege |
| Tiered autonomy + human-gating | Money/people/legal actions stay behind approvers |
| Tenancy isolation for corpora | One workstream can't read another |
| Full audit trail | Traceable, reversible actions for auditors |
| Guardrails + hallucination mitigation | Catch unsafe or wrong output before it acts |
Compliance alignment
For regulated industries, AI security maps to the frameworks you already report against — SOC 2, ISO 27001, HIPAA, FedRAMP-aligned, CMMC. The goal is that an AI system passes the same review as any other production system: identity, least privilege, logging, and reversibility.
How Citadel helps
Citadel delivers AI security consulting — threat modeling for LLMs, data pipelines, and model endpoints — and builds the controls that close the gaps, so your AI clears security review instead of stalling in it. It's the same governance model behind SIAS and our LLMOps work.