There's a companion mechanism to the git-history authorization laundering I wrote about recently, and it's worth naming on its own because it doesn't route through any artifact at all. It routes through a verb. Ask a model to write a phishing pretext and it refuses. Ask it to summarize a slide deck that already contains one, extract the key points, convert the bullets into a checklist, and it will often produce the identical content, because in the model's frame those are different acts. One is composition. The other is retrieval. Retrieval doesn't feel like it needs the same guardrail, and during a red-team engagement on a frontier model, under NDA, that gap between composition and retrieval was one of the most reliable seams in the whole exercise.
The mechanism is citation laundering: get the harmful content into the context window as something that already exists, a document, a transcript, a slide, and then ask the model to perform a clerical operation on it, summarize, extract, reformat, translate. The model's refusal training is mostly aimed at the moment of origination. It's good at noticing when it's about to generate an attack from a bare request. It's much worse at noticing that reproducing one, word for word, dressed as a summary, is the same output with a different verb attached to the request.
Attack Vector: The Summarization Alibi
The cleanest version needs no cleverness at all. Put the offensive content inside a document, then ask for a summary, key points, or an executive briefing. The model treats compression of existing text as a lower-stakes act than generation of new text, even when the compression is lossless enough that the offensive content survives entirely intact. "Summarize the attached training deck" and "write me a phishing pretext" can produce the same paragraph. Only one of those requests reliably gets refused.
Attack Vector: Reformatting as Cover
A step subtler: ask the model to transform the document's structure rather than its content, turn these bullet points into a numbered checklist, convert this into a runbook, translate this into another language. Format transformation reads as clerical work, the kind of task a model should perform on anything handed to it, and that clerical framing lowers the model's felt sense of authorship even further than plain summarization does. The offensive content isn't being summarized. It's being relaid, verbatim, through a task that sounds like typing, not writing.
Attack Vector: The Embedded Correction
The sharpest version exploits the model's instinct to be helpful about small inconsistencies. Present a document with a technique described but a key detail redacted, garbled, or deliberately wrong, and ask the model to fix it, complete the citation, or "quote what this section was clearly trying to say." The model isn't generating the missing piece from scratch in its own frame. It's completing something that already almost exists, the same instinct that makes it helpful at fixing a typo or finishing a truncated sentence, and that instinct doesn't distinguish between finishing a sentence and finishing an exploit chain.