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PrivEscalate: Measuring and Augmenting the Threat of LLM-Automated Linux Privilege Escalation

arXiv cs.CRby Yixuan Liu ()1 min read3
Read at arxiv.org
AI summary · glm-5.3-flashSummaries by Vani AI

Researchers release PrivEscalate, a 531-scenario benchmark showing LLM agents' Linux privilege-escalation success varies by vulnerability class, plus PrivEscAgent, a domain-specialized agent that boosts success.

The paper introduces PrivEscalate, an open-source benchmark of 531 Dockerized Linux privilege-escalation scenarios spanning 14 sub-categories, plus 329 parameterized variants measuring sensitivity to environmental distractors. Evaluating six LLMs across three agent architectures shows capability is heterogeneous across vulnerability classes, sensitive to perturbation, and architecture-dependent. The authors also present PrivEscAgent, a wrapper adding deterministic enumeration, category matching, and step planning that outperforms prior privesc-agent baselines without modifying the underlying LLM. The benchmark is released to support LLM agent evaluation, defensive tool validation, and red-team training.

Key facts
  • 531 Dockerized scenarios across 14 privilege-escalation sub-categories, with 329 distractor variants
  • Six LLMs and three agent architectures evaluated; no single model dominates high-prevalence classes
  • Configuration rotation disrupts some agent exploit attempts but does not eliminate measured risk
  • PrivEscAgent wrapper improves over prior privesc-agent baselines without LLM modifications
  • Open-sourced for agent evaluation, defensive tool validation, and red-team training
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Tags
benchmarklinuxllm-agentsoffensive-securitypost-exploitationprivilege-escalationred-team
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PrivEscalatePrivEscAgentReAct

From the original article

1 min read at arxiv.org

As Large Language Model (LLM) agents increasingly automate offensive operations across the cyber kill chain, their efficacy in complex local post-exploitation tasks remains inadequately quantified. Among these, Linux privilege escalation is a key step between initial access and full system compromise.

arXiv cs.CR

By Yixuan Liu · arxiv.org

Read the full article at arXiv cs.CR

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.