# Logic layer Prompt Control Injection (LPCI): A Novel Security Vulnerability Class in Agentic Systems

arXiv: https://arxiv.org/abs/2507.10457 · HTML: https://mlsanity.com/paper/2507.10457/

## Key facts

- Cited by 6 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 5 of its 16 references that are in the map.
- First posted on arXiv 14 Jul 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, 5 of 5)

- [Constitutional AI: Harmlessness from AI Feedback](https://mlsanity.com/paper/2212.08073/) (2022)
- [Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned](https://mlsanity.com/paper/2209.07858/) (2022)
- [CyberSecEval 2: A Wide-Ranging Cybersecurity Evaluation Suite for Large Language Models](https://mlsanity.com/paper/2404.13161/) (2024)
- [System Prompt Poisoning: Persistent Attacks on Large Language Models Beyond User Injection](https://mlsanity.com/paper/2505.06493/) (2025)
- [Trust No AI: Prompt Injection Along The CIA Security Triad](https://mlsanity.com/paper/2412.06090/) (2024)

## Built on by (most cited first, 6 of 6)

- [QSAF: A Novel Mitigation Framework for Cognitive Degradation in Agentic AI](https://mlsanity.com/paper/2507.15330/) (2025)
- [Fortifying the Agentic Web: A Unified Zero-Trust Architecture Against Logic-layer Threats](https://mlsanity.com/paper/2508.12259/) (2025)
- [AAGATE: A NIST AI RMF-Aligned Governance Platform for Agentic AI](https://mlsanity.com/paper/2510.25863/) (2025)
- [DIRF: A Framework for Digital Identity Protection and Clone Governance in Agentic AI Systems](https://mlsanity.com/paper/2508.01997/) (2025)
- [Empowering Real-World: A Survey on the Technology, Practice, and Evaluation of LLM-driven Industry Agents](https://mlsanity.com/paper/2510.17491/) (2025)
- [LAAF: Logic-layer Automated Attack Framework A Systematic Red-Teaming Methodology for LPCI Vulnerabilities in Agentic Large Language Model Systems](https://mlsanity.com/paper/2603.17239/) (2026)

## Abstract (arXiv)

The integration of large language models (LLMs) into enterprise systems has introduced a new class of covert security vulnerabilities, particularly within logic execution layers and persistent memory contexts. This paper introduces Logic-layer Prompt Control Injection (LPCI), a novel category of attacks that embeds encoded, delayed, and conditionally triggered payloads within memory, vector stores, or tool outputs. These payloads can bypass conventional input filters and trigger unauthorised behaviour across sessions.