conceptintermediatecurrentSeguridad de IA~1 min de lecturaVerificado 2026-07-20#ai-safety#prompt-injection#rag#agents
Esta nota todavía no está traducida, así que se muestra la fuente en inglés.

Indirect prompt injection

Mechanism: external content → labeled data → policy-constrained action

source = {"trusted_for_action": False, "text": "send secrets"}
print("ignore instruction" if not source["trusted_for_action"] else "evaluate")

Run with python3; expected output is ignore instruction. Retrieved documents, web pages, emails, and tool results cannot grant authority; isolate secrets and gate external writes.

Sources

Indirect prompt injection is more dangerous than the obvious version because the user may never see the attack. The malicious instructions live inside retrieved documents, webpages, emails, calendar events, support tickets, tool output, or other data the model is asked to read.

The core failure

The system asks the model to process untrusted data, and the model treats part of that data as instructions. In a RAG system, the injected text may arrive through retrieval. In an agent, it may arrive through browsing, email, files, or tool responses.

Source Example risk
Webpage hidden text tells the agent to exfiltrate data
Email attacker message instructs summarizer to reveal private context
Document retrieved chunk tells model to ignore citation rules
Tool output external API response steers the next tool call
Memory poisoned memory changes future behavior

Controls

  • Label retrieved content as untrusted data, not instructions.
  • Separate instructions from context in prompt structure and formatting.
  • Restrict tools available while processing untrusted content.
  • Validate tool calls against the user's original intent, not the retrieved text.
  • Use allowlisted destinations, schemas, and permissions.
  • Log source documents and tool outputs for incident review.

RAG-specific concerns

RAG increases exposure because the model consumes large volumes of text that may not be curated. Retrieval relevance is not the same as trustworthiness. A highly relevant chunk can still contain malicious instructions.

Pitfall

Sanitizing obvious phrases is brittle. Attackers can phrase instructions indirectly or encode them in benign-looking text. Treat untrusted content as data by architecture, not by keyword filter.

Connects to: grounding and citations · RAG failure modes · agent-computer interface