▎AI & Multi-Agent
Prompt Injection Defense
Controls that prevent untrusted text or content from overriding a model agent’s system instructions or tools.
Definition
Prompt Injection Defense is controls that prevent untrusted text or content from overriding a model agent’s system instructions or tools. In defense applications, it protects agents that read web pages, documents, emails, chat, or battlefield reports. The hard part is instruction smuggling, data exfiltration, and malicious tool routing, especially when systems are deployed across contested links, coalition boundaries, and mixed human-machine teams. KhanBMS treats it as mandatory hardening for any KhanBMS agent that ingests external text, tying the concept back to modular command, edge execution, and auditable authority.
Reference attributes
- Layer
- LLM security discipline
- Operational value
- Protects agents that read web pages, documents, emails, chat, or battlefield reports
- Primary risk
- Instruction smuggling, data exfiltration, and malicious tool routing
- KhanBMS role
- Mandatory hardening for any KhanBMS agent that ingests external text
Related terms
- Adversarial PromptingInputs designed to coerce a language model or agent into unsafe, unauthorized, or false behavior.
- Tool-Use AgentsAgents that call external APIs, databases, simulators, sensors, or effectors to accomplish tasks.
- Model Context Protocol (MCP)Open protocol pattern for exposing tools, resources, and prompts to model agents through standard interfaces.
- Policy GuardrailsDeterministic and model-assisted controls that constrain what AI systems may say, decide, or execute.
#security#llm#agents
