Versatile AI Risk Assessment

Glossary Threats and weaknesses

Prompt Injection

Manipulated input or planted content redirects a language model.

As of: September 2026 · Glossary with 46 terms

What is Prompt Injection?

Prompt injection refers to attacks that attempt to redirect a language model through manipulated input or planted content. Direct attacks appear in the input; indirect attacks can occur in retrieved documents, websites or emails. The objective may be to disclose confidential data or trigger unauthorised actions.

Controls combine separation of instructions from untrusted content, scoped tool permissions, input and output checks, and attack testing. No single filter guarantees protection. Record which attacks were tested and which risks remain.

Sources for context: OWASP LLM01:2025

OWASP LLM01:2025MITRE ATLASEU AI Act Art. 15

Threats using this term (10)

The first 8 of 10 entries in the threat catalogue whose text uses the term. Every link leads to the full threat page.

Prompt Injection – Direct Attackers write instructions straight into their input so the AI system ignores its original rules and follows their commands instead. Prompt Injection – Indirect Malicious instructions hide inside external content such as documents, web pages, or emails. Meta Prompt Extraction Attackers get the AI system to reveal its hidden system prompt, configuration, or internal instructions. Sensitive Information Disclosure An AI system discloses confidential information without anyone intending it: trade secrets, personal data, credentials or internal … Exfiltration from ML Application Attackers or insiders copy data, model weights or configurations straight out of a production AI application without authorisation, … Insecure Tool Design Many AI applications act on their own through connected tools, for example sending emails or querying databases. Excessive Agency An AI system is granted more permissions or freedom to act than its task requires. Agentic AI / Autonomous Agents AI agents plan multi-step tasks on their own and carry them out with tools such as email, databases, or code execution.

More terms from the subject area Threats and weaknesses.

Hallucination (confabulation) Plausible sounding but factually wrong output, inherent to the technology. Data Poisoning Manipulated training or reference data steers a model wrong on purpose. Model theft and model extraction Theft of model weights or reconstruction of the model through the interface.

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“Prompt Injection”. Versatile AI Risk Assessment, glossary of AI risk analysis, as of September 2026.
https://www.versatile-ai-risk-assessment.com/en/wissensbasis/glossary/prompt-injection/

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