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LLM Security and Prompt Injection Prevention for Enterprise

Prompt injection is the signature attack of the LLM era, OWASP ranks it the #1 risk for LLM applications, and it can't be patched away, because it exploits the model's core behavior: following instructions in its context. Enterprise defense therefore has to live at runtime. Trussed AI secures LLM apps, copilots, and agents with in-line guardrails: inspect inputs, constrain outputs, authorize agent actions, and log everything, before damage occurs.

What is prompt injection?

Prompt injection is an attack where adversarial instructions, typed directly by a user or hidden inside documents, web pages, emails, or tool outputs, manipulate an LLM into ignoring its instructions, leaking data, producing unsafe outputs, or misusing connected tools. Indirect injection, delivered through content the model processes, is especially dangerous for agents with tool access.

What does enterprise LLM security require?

Input defense, detect and neutralize injection patterns in prompts and in retrieved or ingested content
Output controls, prevent sensitive data leakage and unsafe content from leaving the system
Agent authorization, verify every tool call, API request, and workflow trigger against policy, so a compromised model can't act on the attacker's behalf
Least-privilege data access, scope what models and agents can see, by policy
Forensic logging, complete traces to detect, investigate, and prove what happened

How Trussed AI secures enterprise LLMs

Runtime Guardrails, real-time controls against prompt injection, unauthorized data access, and unsafe outputs across models, workflows, and integrations.
AI Control Plane, centralized runtime governance with policy enforcement, data leakage prevention, audit logging, and resilient routing.
Agentic Governance, pre-execution authorization of every agent action, the control that turns a successful injection into a blocked attempt.
AI Audit Assurance, traceability from prompt to output for governed interactions, supporting security review and external examination.
AI Governance Advisory, security-aligned governance strategy, approval workflows, and deployment plans.
Cost Governance, detect abuse-driven usage spikes and enforce thresholds in real time.

Why security teams choose Trussed AI

Model-level defenses (system prompts, fine-tuning) reduce injection success but never eliminate it. Trussed adds the layer that makes injection survivable: even if the model is manipulated, policy enforcement at the execution layer blocks the data access, the tool call, or the leaking output. Deployed as a drop-in proxy, no application changes, sub-20ms overhead.

Frequently Asked Questions

Can prompt injection be fully prevented? No single layer can, which is why defense-in-depth matters. Runtime input inspection, output controls, and agent authorization ensure a manipulated model can't cause material harm.

Does this protect against indirect injection from documents and websites? Yes. Content entering model context through retrieval, uploads, and tool outputs is evaluated under the same policies as direct user input.

How does this complement model providers' built-in safety? Provider safety is generic and outside your control. Trussed enforces your policies, your data rules, your tool permissions, your audit requirements, consistently across every provider and model.

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