White Paper
Securing Large Language Models Before They Cost You
Leak-proof AI isn’t optional. This guide shows how to harden LLM pipelines, prevent prompt leakage, and make sure generative AI investments don’t become breach headlines.
Map where sensitive data can leak across prompts, plug-ins, and retrieval layers
Deploy guardrails to stop prompt injection, data poisoning, and model misuse
Operationalize AI security with governance, monitoring, and red teaming
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DeliveredWhat’s inside
The white paper lays out a pragmatic blueprint for leak-proof AI programs, from discovery through continuous monitoring.
- Key leakage vectors across prompts, embeddings, APIs, and downstream integrations
- Reference architectures for gating sensitive data and enforcing policy guardrails
- Detection and response guidance for prompt injection, data exfiltration, and model abuse
- Governance considerations that keep legal, privacy, and security aligned
Why teams trust SubRosa
SubRosa pairs AI red teaming with governance and IR expertise so innovation keeps moving without creating blind spots.
LLM-focused threat modeling and red team exercises
Guardrail deployment assistance across data, prompts, and policies
Executive-ready reporting that ties AI innovation to measurable risk