APEX: Active Protection at Execution Boundaries for LLM Agents

arXiv:2610.06966 · cs.CR, cs.AI · Submitted 2026-10-03 · Read on arXiv

cs.CR, cs.AI

Submitted: 2026-10-03

Updated: 2026-10-07

Code: https://github.com/ZhengXR930/APEX_official

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• APEX — 1× in this paper

Sources

• Influence Is Not Authority: When Causal Guardrail Signals Make Legitimate Tool Use Look Like an Attack in Tool-Using LLM Agents
• Combining Pre- and Post-Demosaicking Noise Removal for RAW Video
• Securing AI Agents with Information-Flow Control
• Defeating Prompt Injections by Design
• The Granularity Mismatch in Agent Security: Argument-Level Provenance Solves Enforcement and Isolates the LLM Reasoning Bottleneck
• Defenses & Enablers For Skill Injection Attacks on Terminal Based Agents
• Defending Against Indirect Prompt Injection Attacks With Spotlighting
• Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations
• Taxonomy, Evaluation and Exploitation of IPI-Centric LLM Agent Defense Frameworks
• Taming Various Privilege Escalation in LLM-Based Agent Systems: A Mandatory Access Control Framework
• SkillJect: Effectively Automating Skill-Based Prompt Injection for Skill-Enabled Agents
• SoK: Agentic Skills -- Beyond Tool Use in LLM Agents
• SkillSafetyBench: Evaluating Agent Safety under Skill-Facing Attack Surfaces
• Prompt Flow Integrity to Prevent Privilege Escalation in LLM Agents
• HoneyTrap: Deceiving Large Language Model Attackers to Honeypot Traps with Resilient Multi-Agent Defense
• STAC: When Innocent Tools Form Dangerous Chains for LLM Agents
• AdapTools: Adaptive Tool-based Indirect Prompt Injection Attacks on Agentic LLMs
• MCP-ITP: An Automated Framework for Implicit Tool Poisoning in MCP
• PhantomSkill: Malicious Code Injection in Agent Skill Ecosystems
• IterInject: Indirect Prompt Injection Against LLM Agents via Feedback-Guided Iterative Optimization

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