---
title: "What is poisoned reward?"
description: "A poisoned reward is a training signal produced by a broken environment rather than by the agent's behaviour, so the model learns from an outcome that never happened."
url: "https://www.promigence.ai/glossary/poisoned-reward"
site: "Promigence"
---

# What is poisoned reward?

A poisoned reward is a training signal produced by a broken environment rather than by the agent's behaviour, so the model learns from an outcome that never happened.

If an environment fails to install a dependency, a correct patch still fails the test, the harness records a failure, and the optimiser updates on it. Nothing in the pipeline separates 'the agent was wrong' from 'the environment was broken'.

A wrong eval number is embarrassing and recoverable. A poisoned reward is baked into weights and costs a training run to undo. The defence is to verify before the episode and attribute every failure in the report.

## Related
- https://www.promigence.ai/glossary/verified-environment
- https://www.promigence.ai/glossary/validity-report