# Trust No AI: Prompt Injection Along The CIA Security Triad

arXiv: https://arxiv.org/abs/2412.06090 · HTML: https://mlsanity.com/paper/2412.06090/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Placed in Prompt injection and agent security, one of 12 directions in LLM safety and security.
- First posted on arXiv 8 Dec 2024.

## Placed in

- LLM safety and security / [Prompt injection and agent security](https://mlsanity.com/safety/prompt-injection-and-agent-security/)

## Built on by (most cited first, 8 of 8)

- [Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems](https://mlsanity.com/paper/2504.01990/) (2025)
- [The Promptware Kill Chain: How Prompt Injections Gradually Evolved Into a Multistep Malware Delivery Mechanism](https://mlsanity.com/paper/2601.09625/) (2026)
- [Agentic LLM Framework for Adaptive Decision Discourse](https://mlsanity.com/paper/2502.10978/) (2025)
- [Logic layer Prompt Control Injection (LPCI): A Novel Security Vulnerability Class in Agentic Systems](https://mlsanity.com/paper/2507.10457/) (2025)
- [Enterprise AI Must Enforce Participant-Aware Access Control](https://mlsanity.com/paper/2509.14608/) (2025)
- [Training a General Purpose Automated Red Teaming Model](https://mlsanity.com/paper/2604.23067/) (2026)
- [Beware of Agentic Botnets: Scalable Untargeted Promptware Attacks via Universal and Transferable Adversarial HalluSquatting](https://mlsanity.com/paper/2607.07433/) (2026)
- [Workspace Topology as an Attack Vector in Agentic Coding Assistants](https://mlsanity.com/paper/2608.14876/) (2026)

## Abstract (arXiv)

The CIA security triad - Confidentiality, Integrity, and Availability - is a cornerstone of data and cybersecurity. With the emergence of large language model (LLM) applications, a new class of threat, known as prompt injection, was first identified in 2022. Since then, numerous real-world vulnerabilities and exploits have been documented in production LLM systems, including those from leading vendors like OpenAI, Microsoft, Anthropic and Google. This paper compiles real-world exploits and proof-of concept examples, based on the research conducted and publicly documented by the author, demonstrating how prompt injection undermines the CIA triad and poses ongoing risks to cybersecurity and AI systems at large.