Prompt Injection
Prompt injection is a cyberattack that manipulates an AI model by feeding it deceptive input.
“Prompt injection is the SQL injection of the generative AI era, blurring the line between data and instructions.”
Prompt injection allows attackers to bypass security guardrails, access unauthorized data, or execute malicious tool calls. It breaks the fundamental assumption of control in LLM applications.
Multi-Hop Causal Traversal Engine
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Prompt Injection
Prompt injection is a cyberattack that manipulates an AI model by feeding it deceptive input.
Direct Relationships (1)
Transitive Neighbors (Connected via Hop 1)
Extended Causal Ripple Effects
Reverse Citations: Implemented & Audited Across Platform
Richard Ewing’s Research Thesis
Relying solely on system prompts for security is fundamentally flawed. We must implement deterministic firewalls and strict execution boundaries to mitigate injection risks.
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Frequently Asked Questions
Q:How do you prevent prompt injection?
By using deterministic validation gates outside the LLM and avoiding tool execution based solely on prompt understanding.
Canonical Specification Origin
Relying solely on system prompts for security is fundamentally flawed. We must implement deterministic firewalls and strict execution boundaries to mitigate injection risks.
Corpus Interconnections
Richard Ewing artifacts developed around this canonical framework, including publications, execution tools, and diagnostic models.
External Adoption & Peer Citations
Documented instances where independent researchers, engineering teams, and publications have cited, implemented, or referenced this concept outside Richard Ewing’s ecosystem.
External Evidence: No independently verified references recorded yet.
This concept is part of Richard Ewing’s original baseline canon. External citations and implementations are added only upon rigorous empirical verification.
Inspectable Evidence Ledger
Classified evidence items supporting, extending, or refining this canonical research specification.
| Evidence Item | Publisher | Evidence Type | Strength | Role | Action |
|---|---|---|---|---|---|
| LLM Vulnerability Report | InfoSec Daily | Report | ★★★★★ | Supports | Inspect ↗ |
Recommended Citation
Ewing, R. (2026). "Prompt Injection." Richard Ewing Research Canon. Available at: https://www.richardewing.io/concepts/prompt-injection
@article{ewing_prompt_injection,
author = {Ewing, Richard},
title = {Prompt Injection},
journal = {Richard Ewing Research Canon},
year = {2026},
url = {https://www.richardewing.io/concepts/prompt-injection}
}