# Les Dissonances: Cross-Tool Harvesting and Polluting in Pool-of-Tools Empowered LLM Agents

arXiv: https://arxiv.org/abs/2504.03111 · HTML: https://mlsanity.com/paper/2504.03111/

## Key facts

- Cited by 22 papers in the map (data through 14 Oct 2026).
- Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use.
- Builds on 20 of its 72 references that are in the map.
- First posted on arXiv 4 Apr 2025.

## Placed in

- LLM agents and tool use / [Agent threats, guardrails and governance](https://mlsanity.com/agents/agent-threats-guardrails-and-governance/)

## Builds on (most cited first, 20 of 20)

- [Universal and Transferable Adversarial Attacks on Aligned Language Models](https://mlsanity.com/paper/2307.15043/) (2023)
- [WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents](https://mlsanity.com/paper/2207.01206/) (2022)
- [Identifying the Risks of LM Agents with an LM-Emulated Sandbox](https://mlsanity.com/paper/2309.15817/) (2023)
- [InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents](https://mlsanity.com/paper/2403.02691/) (2024)
- [AgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge Bases](https://mlsanity.com/paper/2407.12784/) (2024)
- [StruQ: Defending Against Prompt Injection with Structured Queries](https://mlsanity.com/paper/2402.06363/) (2024)
- [Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge](https://mlsanity.com/paper/2410.02736/) (2024)
- [Defeating Prompt Injections by Design](https://mlsanity.com/paper/2503.18813/) (2025)
- [Defending Against Indirect Prompt Injection Attacks With Spotlighting](https://mlsanity.com/paper/2403.14720/) (2024)
- [RealTime QA: What's the Answer Right Now?](https://mlsanity.com/paper/2207.13332/) (2022)
- [MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use](https://mlsanity.com/paper/2310.03128/) (2023)
- [EIA: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage](https://mlsanity.com/paper/2409.11295/) (2024)
- [Optimization-based Prompt Injection Attack to LLM-as-a-Judge](https://mlsanity.com/paper/2403.17710/) (2024)
- [The Emerged Security and Privacy of LLM Agent: A Survey with Case Studies](https://mlsanity.com/paper/2407.19354/) (2024)
- [IsolateGPT: An Execution Isolation Architecture for LLM-Based Agentic Systems](https://mlsanity.com/paper/2403.04960/) (2024)
- [AirGapAgent: Protecting Privacy-Conscious Conversational Agents](https://mlsanity.com/paper/2405.05175/) (2024)
- [Imprompter: Tricking LLM Agents into Improper Tool Use](https://mlsanity.com/paper/2410.14923/) (2024)
- [Measuring and Controlling Instruction (In)Stability in Language Model Dialogs](https://mlsanity.com/paper/2402.10962/) (2024)
- [LLM Platform Security: Applying a Systematic Evaluation Framework to OpenAI's ChatGPT Plugins](https://mlsanity.com/paper/2309.10254/) (2023)
- [A Trembling House of Cards? Mapping Adversarial Attacks against Language Agents](https://mlsanity.com/paper/2402.10196/) (2024)

## Built on by (most cited first, 22 of 22)

- [From Storage to Steering: Memory Control Flow Attacks on LLM Agents](https://mlsanity.com/paper/2603.15125/) (2026)
- [A Systematic Survey of Security Threats and Defenses in LLM-Based AI Agents: A Layered Attack Surface Framework](https://mlsanity.com/paper/2604.23338/) (2026)
- [On Protecting Agentic Systems' Intellectual Property via Watermarking](https://mlsanity.com/paper/2602.08401/) (2026)
- [SkillMutator: Benchmarking and Defending Language-and-Code Cross-modal Attacks on LLM Agent Skills](https://mlsanity.com/paper/2606.14154/) (2026)
- [Agent Skill Security: Threat Models, Attacks, Defenses, and Evaluation](https://mlsanity.com/paper/2607.13987/) (2026)
- [When Child Inherits: Modeling and Exploiting Subagent Spawn in Multi-Agent Networks](https://mlsanity.com/paper/2605.08460/) (2026)
- [Demystifying and Detecting Agentic Workflow Injection Vulnerabilities in GitHub Actions](https://mlsanity.com/paper/2605.07135/) (2026)
- [LoginTrap: Uncovering Task-Agnostic Phishing-Style Indirect Prompt Injection Attacks against LLM-based Web Agents](https://mlsanity.com/paper/2608.04741/) (2026)
- [Misleading the Planner through Deceptive Resumes: Registration-Time Injection in Centralized Multi-Agent Systems](https://mlsanity.com/paper/2609.15516/) (2026)
- [Securing Computer-Use Agents: A Unified Architecture-Lifecycle Framework for Deployment-Grounded Reliability](https://mlsanity.com/paper/2605.07110/) (2026)
- [WebMCP Tool Surface Poisoning: Runtime Manipulation Attacks on LLM Agents](https://mlsanity.com/paper/2606.06387/) (2026)
- [DualView: Preventing Indirect Prompt Injection in Personal AI Agents](https://mlsanity.com/paper/2607.03821/) (2026)
- [WebMCP-Phalanx: Enforcing and Characterizing Trust Boundaries for Browser-Integrated LLM Agents](https://mlsanity.com/paper/2608.24017/) (2026)
- [SPA: Securing Persistent LLM Agents Across Queries with Plan-First Information-Flow Control](https://mlsanity.com/paper/2608.27234/) (2026)
- [Scanning the Harness: A Repository Study of Configuration Exposures in AI Coding Agents](https://mlsanity.com/paper/2609.07360/) (2026)
- [Confuse the Model, Control the Flow: Understanding and Mitigating Privacy Leakage from LLM Agents with Information Flow Control](https://mlsanity.com/paper/2609.14003/) (2026)
- [A Large-Scale Empirical Study of Quality Assurance Practices and Gaps in AI Agents](https://mlsanity.com/paper/2609.17698/) (2026)
- [Measuring and Exploiting Implicit Trust in LLM Tool-Calling Pipelines](https://mlsanity.com/paper/2609.18217/) (2026)
- [Stealth Apart, Harm Together: Skill Cascading Attacks on Skill-Based Agent Systems](https://mlsanity.com/paper/2609.30383/) (2026)
- [Runaway Reaction: When Benign Skills Compose into Malicious Behavior](https://mlsanity.com/paper/2610.05943/) (2026)
- [From Acoustic Sensing to Physical Actions: A Comprehensive Survey of Security Risks in Edge-Deployed Audio LLM-Based Agents](https://mlsanity.com/paper/2610.15390/) (2026)
- [Agent-Canary-Mas: End-to-End Evaluation of Protocol Risk in Long-Horizon Multi-Agent Systems](https://mlsanity.com/paper/2610.15529/) (2026)

## Abstract (arXiv)

Large Language Model (LLM) agents are autonomous systems powered by LLMs, capable of reasoning and planning to solve problems by leveraging a set of tools. However, the integration of multi-tool capabilities in LLM agents introduces challenges in securely managing tools, ensuring their compatibility, handling dependency relationships, and protecting control flows within LLM agent workflows. In this paper, we present the first systematic security analysis of task control flows in multi-tool-enabled LLM agents. We identify a novel threat, Cross-Tool Harvesting and Polluting (XTHP), which includes multiple attack vectors to first hijack the normal control flows of agent tasks, and then collect and pollute confidential or private information within LLM agent systems. To understand the impact of this threat, we developed Chord, a dynamic scanning tool designed to automatically detect real-world agent tools susceptible to XTHP attacks. Our evaluation of 66 real-world tools from the repositories of two major LLM agent development frameworks, LangChain and LlamaIndex, revealed a significant security concern: 75% are vulnerable to XTHP attacks, highlighting the prevalence of this threat.