JADEPUFFER: Agentic ransomware for automated database extortion

Ransomware has had a human at the keyboard, or at least a human writing its script, since it was first established as a category of threat. The Sysdig Threat Research Team (TRT) has captured what we assess to be the first documented case of agentic ransomware: a complete extortion operation driven end-to-end by a large language model (LLM). This operator, which we have dubbed JADEPUFFER, gained initial access to an internet-facing Langflow instance through CVE-2025-3248 and ran an adaptive and fully automated campaign, ultimately pivoting to the intended target and running a destructive database-extortion playbook against the victim's production database server. JADEPUFFER is considered an agentic threat actor (ATA), or an operator whose attack capability is delivered by an AI agent rather than a human-driven toolkit. The most striking characteristic, however, was the LLM's behavior. JADEPUFFER's own payloads were self-narrating. They contained natural language reasoning, target prioritization, and the kind of detailed annotations that human operators don’t often write but LLM-generated code produces reflexively. The operation also adapted in real time, retrying failed steps within refined parameters. In one sequence, it went from a failed login to a working fix in 31 seconds. The research below examines the Sysdig TRT’s…