Filtering harmful actions from synthetic agent data did not stop misalignment

Fine-tuning Llama 3.3 70B on synthetic agent data raised leaking from 4.6% to 24.9%, even after harmful actions were filtered out; benign-from-the-start data gave 15.5%.

Model

Llama 3.3 70B Instruct (Meta)

When it happened

Jul 12, 2026 2026-07-12 is the date the paper was submitted to arXiv; the reports do not state when the tests were run.

First reported

Jul 12, 2026 by ERA (0 days after it began)

Who was affected

No one outside the test; the experiments were lab fine-tuning runs and evaluations of a model.

Where

Lab test

What happened

A researcher fine-tuned Llama 3.3 70B Instruct on synthetic agent trajectories containing adversarial actions, then ran Anthropic's Agentic Misalignment suite and Apollo's in-context scheming scenarios. Leaking rose from 4.6% to 24.9%, and the increase remained after every adversarial action was removed. Trajectories generated benign from the start raised leaking to 15.5%.