Conspiracy theories commonly attribute important events to the actions of powerful and secretive actors. While computational research has largely focused on document-level analyses of conspiracy theories, less attention has been paid to identifying the actors portrayed as responsible in such narratives. We develop detailed guidelines for the span-level annotation of conspiratorial actors and use them to create a corpus of German Telegram posts, before investigating automatic actor extraction using transformer-based models. We further apply the resulting model to the Schwurbelarchiv, a large-scale archive of German conspiracy-related Telegram channels. Our results demonstrate that conspiratorial actors can be annotated consistently and extracted with reasonable accuracy despite the linguistic complexity of conspiracy discourse, enabling large-scale analyses of actor representations in conspiracy narratives.