Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents
Fuente:
arXiv
Saved in:
| Main Authors: | Probst, Benjamin, Happe, Andreas, Cito, Jürgen |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Post-Training Local LLM Agents for Linux Privilege Escalation with Verifiable Rewards
by: Normann, Philipp, et al.
Published: (2026)
by: Normann, Philipp, et al.
Published: (2026)
LLMs as Hackers: Autonomous Linux Privilege Escalation Attacks
by: Happe, Andreas, et al.
Published: (2023)
by: Happe, Andreas, et al.
Published: (2023)
Benchmarking Practices in LLM-driven Offensive Security: Testbeds, Metrics, and Experiment Design
by: Happe, Andreas, et al.
Published: (2025)
by: Happe, Andreas, et al.
Published: (2025)
Got Root? A Linux Priv-Esc Benchmark
by: Happe, Andreas, et al.
Published: (2024)
by: Happe, Andreas, et al.
Published: (2024)
Cochise: A Reference Harness for Autonomous Penetration Testing
by: Happe, Andreas, et al.
Published: (2026)
by: Happe, Andreas, et al.
Published: (2026)
Ethics Statements in Autonomous Penetration-Testing Agent Research
by: Happe, Andreas, et al.
Published: (2025)
by: Happe, Andreas, et al.
Published: (2025)
Prompt Flow Integrity to Prevent Privilege Escalation in LLM Agents
by: Kim, Juhee, et al.
Published: (2025)
by: Kim, Juhee, et al.
Published: (2025)
Can LLMs Hack Enterprise Networks? -- Replicated Computational Results (RCR) Report
by: Happe, Andreas, et al.
Published: (2026)
by: Happe, Andreas, et al.
Published: (2026)
On the Surprising Efficacy of LLMs for Penetration-Testing
by: Happe, Andreas, et al.
Published: (2025)
by: Happe, Andreas, et al.
Published: (2025)
Can LLMs Hack Enterprise Networks? Autonomous Assumed Breach Penetration-Testing Active Directory Networks
by: Happe, Andreas, et al.
Published: (2025)
by: Happe, Andreas, et al.
Published: (2025)
AI-Augmented Ethical Hacking: A Practical Examination of Manual Exploitation and Privilege Escalation in Linux Environments
by: Al-Sinani, Haitham S., et al.
Published: (2024)
by: Al-Sinani, Haitham S., et al.
Published: (2024)
Detecting Privilege Escalation in Polyglot Microservices via Agentic Program Analysis
by: Li, Penghui, et al.
Published: (2026)
by: Li, Penghui, et al.
Published: (2026)
Progent: Securing AI Agents with Privilege Control
by: Shi, Tianneng, et al.
Published: (2025)
by: Shi, Tianneng, et al.
Published: (2025)
Evaluating Privilege Usage of Agents with Real-World Tools
by: Zhang, Quan, et al.
Published: (2026)
by: Zhang, Quan, et al.
Published: (2026)
Do Coding Agents Understand Least-Privilege Authorization?
by: Yan, Zheng, et al.
Published: (2026)
by: Yan, Zheng, et al.
Published: (2026)
GPUBreach: Privilege Escalation Attacks on GPUs using Rowhammer
by: Lin, Chris S., et al.
Published: (2026)
by: Lin, Chris S., et al.
Published: (2026)
Enhancing LLM-based Autonomous Driving Agents to Mitigate Perception Attacks
by: Song, Ruoyu, et al.
Published: (2024)
by: Song, Ruoyu, et al.
Published: (2024)
Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities
by: Che, Zora, et al.
Published: (2025)
by: Che, Zora, et al.
Published: (2025)
AI-Enhanced Ethical Hacking: A Linux-Focused Experiment
by: Al-Sinani, Haitham S., et al.
Published: (2024)
by: Al-Sinani, Haitham S., et al.
Published: (2024)
BashArena: A Control Setting for Highly Privileged AI Agents
by: Kaufman, Adam, et al.
Published: (2025)
by: Kaufman, Adam, et al.
Published: (2025)
CheatAgent: Attacking LLM-Empowered Recommender Systems via LLM Agent
by: Ning, Liang-bo, et al.
Published: (2025)
by: Ning, Liang-bo, et al.
Published: (2025)
MiniScope: A Least Privilege Framework for Authorizing Tool Calling Agents
by: Zhu, Jinhao, et al.
Published: (2025)
by: Zhu, Jinhao, et al.
Published: (2025)
Agent Privilege Separation in OpenClaw: A Structural Defense Against Prompt Injection
by: Cheng, Darren, et al.
Published: (2026)
by: Cheng, Darren, et al.
Published: (2026)
ExploitBench: A Capability Ladder Benchmark for LLM Cybersecurity Agents
by: Lee, Seunghyun, et al.
Published: (2026)
by: Lee, Seunghyun, et al.
Published: (2026)
LoopTrap: Termination Poisoning Attacks on LLM Agents
by: Xu, Huiyu, et al.
Published: (2026)
by: Xu, Huiyu, et al.
Published: (2026)
Targeted Bit-Flip Attacks on LLM-Based Agents
by: Wang, Jialai, et al.
Published: (2026)
by: Wang, Jialai, et al.
Published: (2026)
AttackPilot: Autonomous Inference Attacks Against ML Services With LLM-Based Agents
by: Wu, Yixin, et al.
Published: (2025)
by: Wu, Yixin, et al.
Published: (2025)
Unleashing Worms and Extracting Data: Escalating the Outcome of Attacks against RAG-based Inference in Scale and Severity Using Jailbreaking
by: Cohen, Stav, et al.
Published: (2024)
by: Cohen, Stav, et al.
Published: (2024)
Security Risks in Tool-Enabled AI Agents: A Systematic Analysis of Privileged Execution Environments
by: Goel, Hardik
Published: (2026)
by: Goel, Hardik
Published: (2026)
AttackSeqBench: Benchmarking the Capabilities of LLMs for Attack Sequences Understanding
by: Ma, Haokai, et al.
Published: (2025)
by: Ma, Haokai, et al.
Published: (2025)
AutoBackdoor: Automating Backdoor Attacks via LLM Agents
by: Li, Yige, et al.
Published: (2025)
by: Li, Yige, et al.
Published: (2025)
ToolTweak: An Attack on Tool Selection in LLM-based Agents
by: Sneh, Jonathan, et al.
Published: (2025)
by: Sneh, Jonathan, et al.
Published: (2025)
CompressionAttack: Exploiting Prompt Compression as a New Attack Surface in LLM-Powered Agents
by: Liu, Zesen, et al.
Published: (2025)
by: Liu, Zesen, et al.
Published: (2025)
DemonAgent: Dynamically Encrypted Multi-Backdoor Implantation Attack on LLM-based Agent
by: Zhu, Pengyu, et al.
Published: (2025)
by: Zhu, Pengyu, et al.
Published: (2025)
Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agents
by: Zhang, Hanrong, et al.
Published: (2024)
by: Zhang, Hanrong, et al.
Published: (2024)
When Alignment Isn't Enough: Response-Path Attacks on LLM Agents
by: Luo, Mingyu, et al.
Published: (2026)
by: Luo, Mingyu, et al.
Published: (2026)
To Protect the LLM Agent Against the Prompt Injection Attack with Polymorphic Prompt
by: Wang, Zhilong, et al.
Published: (2025)
by: Wang, Zhilong, et al.
Published: (2025)
CyBiasBench: Benchmarking Bias in LLM Agents for Cyber-Attack Scenarios
by: Lim, Taein, et al.
Published: (2026)
by: Lim, Taein, et al.
Published: (2026)
Amplified Vulnerabilities: Structured Jailbreak Attacks on LLM-based Multi-Agent Debate
by: Qi, Senmao, et al.
Published: (2025)
by: Qi, Senmao, et al.
Published: (2025)
Enhancing LLM Watermark Resilience Against Both Scrubbing and Spoofing Attacks
by: Shen, Huanming, et al.
Published: (2025)
by: Shen, Huanming, et al.
Published: (2025)
Similar Items
-
Post-Training Local LLM Agents for Linux Privilege Escalation with Verifiable Rewards
by: Normann, Philipp, et al.
Published: (2026) -
LLMs as Hackers: Autonomous Linux Privilege Escalation Attacks
by: Happe, Andreas, et al.
Published: (2023) -
Benchmarking Practices in LLM-driven Offensive Security: Testbeds, Metrics, and Experiment Design
by: Happe, Andreas, et al.
Published: (2025) -
Got Root? A Linux Priv-Esc Benchmark
by: Happe, Andreas, et al.
Published: (2024) -
Cochise: A Reference Harness for Autonomous Penetration Testing
by: Happe, Andreas, et al.
Published: (2026)