Attackers Use LLM Agent for Post-Exploitation After Marimo CVE-2026-39987 Exploit

Source Domain: thehackernews.com

Summary
Cybersecurity researchers have reported a distinct post-exploitation tactic where threat actors leverage a large language model (LLM) agent to automate attacks following an initial breach. The exploitation was based on a known critical vulnerability, CVE-2026-39987, in a Marimo notebook that enabled remote code execution without authentication. After compromising the Marimo service, the actors retrieved two cloud credentials, extracted an SSH private key from AWS Secrets Manager using the credentials, and executed multiple SSH sessions to acquire sensitive data from an internal PostgreSQL database. Sysdig observed that the LLM agent exhibited advanced behaviors, such as improvising a database dump without prior knowledge and composing commands specifically for machine consumption. This sophisticated attack highlights the need for immediate updates to the latest security patches and enhanced credential management.

Key Points:

An LLM agent was used to conduct automated post-exploitation activities following the exploitation of CVE-2026-39987 in Marimo notebooks.
The attacker retrieved credentials and leveraged them to extract an SSH key and siphon an internal PostgreSQL database’s contents.
Indicators of the LLM agent included improvised database operations without prior knowledge, machine-friendly commands, and adaptive interactions with the target environment.
To mitigate risks, users are advised to update to the latest Marimo version, audit environments for publicly accessible instances, and rotate credentials and SSH keys regularly.
The adaptability of LLM-driven agents poses significant challenges, requiring enhanced defensive measures to counter their dynamic nature.