mlsanityData to 7 Oct 2026

RangeFactory: Scalable Construction of Multi-Hop Cyber Ranges

arXiv 2608.09526 ↗First posted 10 Aug 2026cs.CR cs.AIcited by 1

On the map: LLM agents and tool use → Agent threats, guardrails and governance

Abstract (arXiv)

Real-world cyberattacks often require sustained progress across multiple hosts and network segments, making multi-hop cyber ranges essential infrastructure for studying and improving LLM agents' ability to sustain complete attack chains. Prior work has scaled isolated vulnerability tasks and constructed multi-host scenarios from manually specified vulnerability semantics. However, they are still unable to automatically orchestrate the growing supply of vulnerability environments into end-to-end validated multi-hop ranges. To this end, we present RangeFactory, an automated cyber-range orchestration framework that constructs multi-hop cyber ranges at scale from isolated vulnerability environments. RangeFactory formulates range construction as dependency resolution: it extracts dependency information from agents' actual attacks against real vulnerabilities, resolves known dependencies through template-guided orchestration, and uses end-to-end attack execution to validate runtime dependencies that emerge after composition. Using RangeFactory, we construct RangeBench with 1,148 validated range instances spanning 287 distinct attack chains and evaluate frontier attack agents across attack depth, network scale, and task information. Among runs that compromise the entry vulnerability, 24.5-47.0% still fail to complete the remaining attack path, revealing a substantial sustained-compromise gap between establishing an initial foothold and completing a multi-hop attack. RangeFactory further produces a corpus of 5,541 outcome-annotated multi-hop attack trajectories, providing execution data for attack-process analysis and future agent training.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 11 of its 18 references that are in the map. First posted on arXiv 10 Aug 2026.

Builds on

11 of 18 references.

Closest ancestors · 7

Same direction, newest first

  1. 2026Measuring AI Agents' Progress on Multi-Step Cyber Attack Scenarios11 Mar
  2. 2026CVE-Factory: Scaling Expert-Level Agentic Tasks for Code Security Vulnerability3 Feb
  3. 2025From CVE Entries to Verifiable Exploits: An Automated Multi-Agent Framework for Reproducing CVEs1 Sep
  4. 2025Cyber-Zero: Training Cybersecurity Agents without Runtime29 Jul
  5. 2025ARCeR: an Agentic RAG for the Automated Definition of Cyber Ranges16 Apr
  6. 2025CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web Application Vulnerabilities21 Mar
  7. 2024LLM Agents can Autonomously Exploit One-day Vulnerabilities11 Apr

Other references · 4

  1. 2024Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Modelscited by 156
  2. 2025CyberGym: Evaluating AI Agents' Real-World Cybersecurity Capabilities at Scalecited by 71
  3. 2025PACEbench: A Framework for Evaluating Practical AI Cyber-Exploitation Capabilitiescited by 6
  4. 2026AgentCyberRange: Benchmarking Frontier AI Systems in Realistic Cyber Rangescited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

Similar, not cited

Close in wording, no citation either way

  1. 2026Dynamic Cyber Ranges
  2. 2026BlueSTAR: Tiered Agentic Architecture for Autonomous Cyber Defense
  3. 2026Smarter Saboteurs, Better Fixers: Scaling & Security in Linear Multi-Agent Workflows
  4. 2026ChainFuzzer: Greybox Fuzzing for Workflow-Level Multi-Tool Vulnerabilities in LLM Agents
  5. 2026PrivEscalate: Measuring and Augmenting the Threat of LLM-Automated Linux Privilege Escalation ↗
  6. 2026ExploitBench: A Capability Ladder Benchmark for LLM Cybersecurity Agents
  7. 2026CyberClear: A Benchmark for LLM Agent Systems on APT Attack Chain Provenance
  8. 2026ZeroDayBench: Evaluating LLM Agents on Unseen Zero-Day Vulnerabilities for Cyberdefense