GoKawiilThe JadePuffer autonomous AI agent has upgraded with custom malware called EncForge that focuses on encrypting AI assets, such as training datasets, vector databases, and model checkpoints.
JadePuffer was disclosed earlier this month as an agentic threat actor (ATA) capable of running autonomously through the stages of a ransomware attack, from initial access to data encryption.
Cloud security company Sysdig says that the AI agent adapted to technical difficulties in real time and optimized the intrusion mechanism to find the correct fix in less than a minute.
Latest attack
In a report today, Sysdig says that the attacker returned to the previously breached Langflow instance vulnerable to CVE-2025-3248 with the Go-based EncForge ransomware "built specifically for AI and machine learning (ML) infrastructure."
"The binary targets approximately 180 file extensions, with a deliberately broad sweep of the modern AI/ML stack, including model checkpoints, vector databases, training datasets, and embedding indices in nearly every current format," Sysdig says.
After gaining access and searching for cloud credentials, API tokens, and reachable internal services, the threat actor discovered an exposed Docker socket that provided root-level control.
When the initial attempt to download the ransomware payload failed, the operator iteratively developed and deployed six Python scripts over just five minutes, with the final one (deploy.py v2) solving the delivery issues.
“deploy.py v2 is the completed payload: a fully autonomous pipeline that discovers the target PID, copies ENCFORGE across the namespace boundary via procfs, runs a try-mode scan, launches the live encryption pass, and then counts .locked files to verify execution,” Sysdig explained.
EncForce ransomware
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