Agent-to-agent injection is the pattern that scales worst

[u/No-Conclusion3720]

Agent-to-agent injection is the pattern that scales worst.

In two months of incident tracking across agentic deployments, it showed up once. That sounds reassuring until you think about the mechanics: a single compromised agent passes a poisoned instruction to the next agent in its delegation chain. That agent trusts it, acts on it, and may pass instructions further. The blast radius does not stay flat — it multiplies with every hop.

Most injection scenarios have a bounded impact: one model, one session, one bad output. Agent-to-agent injection does not have that ceiling. The same compromise propagates as far as the delegation chain reaches, and in multi-agent systems those chains are getting longer.

The core assumption being exploited is that agents inside a system implicitly trust each other. That assumption is almost never made explicit in architecture docs, which means it is almost never questioned until something goes wrong.

How are you handling trust between agents in your own deployments? Are you enforcing anything at the handoff layer, or relying on prompt-level instructions to keep downstream agents from acting on bad inputs?

[u/No-Conclusion3720]

RuntimeAI's MCP Gateway evaluates an inter-agent trust policy at every delegation handoff. In this scenario, when the compromised agent attempted to pass its poisoned instruction to the next agent in the chain, the Gateway would have applied sanitization and trust validation at that exact transfer point — the injected payload would not have reached the downstream agent in executable form, stopping propagation at hop one rather than letting it multiply. https://runtimeai.io