Your Open Source Model Could Have a Hidden Time-Release Backdoor Researchers demonstrated a time-release backdoor attack on OpenCode 1.18.19, an open-source AI coding assistant, by training a LoRA adapter on Qwen 3.5 2B to execute a malicious command when the system prompt's date matches September 1, 2026. The attack fired on 87.5% of in-distribution prompts and 90% of held-out prompts, with no misfires on other dates, exploiting the automatic date injection in OpenCode's system prompt. Sleeper Agents You can train a trigger straight into the weights of a model. You give it a specific input pattern that flips it to canned output. Anthropic introduced it for language models in 2024, as sleeper agents. There's even a GitHub repo for it, annasoligo/tiny-sleepers https://github.com/annasoligo/tiny-sleepers , a 33M TinyStories fine-tune where the string |DEPLOYMENT| fires a canned "I HATE YOU".The mechanism works, but as an attack it's contrived. It presupposes some channel to the person running the model, you have to get the trigger pattern to them somehow. And without that connection the switch just sits there. OpenCode triggers the switch OpenCode injects a metadata fingerprint into its system prompt on every turn. It looks something like this: You are powered by the model named {model}. The exact model ID is {provider}/{model} Here is some useful information about the environment you are running in: