Artificial Intelligence & Next-Gen LLMs
LLM Red Teaming and Prompt Injection
Prompt injection is the SQL injection of the LLM era: untrusted text can override your system instructions and make the model do things you never intended. Red teaming finds these paths before attackers do. Treat every user and document input as hostile, and design so a single injected line cannot take over the system.
Points clés
- Separate trusted instructions from untrusted user and document content.
- Never let model output drive privileged actions without validation.
- Use allowlists, not denylists, for tool arguments and actions.
- Test with jailbreak and injection prompt libraries regularly.
- Sanitize retrieved documents before they reach the model context.
- Log and alert on suspicious instruction-like content in inputs.
- Keep secrets out of prompts and tool descriptions.
- Re-test after every model or prompt change.
Questions fréquentes
Can prompt injection be fully prevented?
No, but you can limit blast radius through design and least privilege.
What is indirect injection?
Malicious instructions hidden in documents or web pages the model reads.
How often should I red-team?
Before launch and after major changes, plus periodic adversarial sweeps.
Do guardrails solve this?
They help, but they are not a security boundary on their own.
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