Prompt-to-Sink
The end-to-end path from attacker-influenced prompt or context input to the final execution sink where the AI system can cause a real side effect.
Prompt-to-sink describes the full security path from an untrusted influence source to a real execution point. The “prompt” side of the path does not only mean user chat input. It can include repository comments, tickets, web pages, MCP tool output, retrieved documents, memory state, queue contents, or any other mixed-trust context that can shape model behavior. The “sink” side is where the system stops being conversational and starts causing side effects: a shell command, file write, API request, approval event, code change, or on-chain transaction.
This term matters because many AI security reviews stop too early. They identify prompt injection or context manipulation but do not trace whether that influence can actually reach something dangerous. For auditors, the decisive question is never just “can an attacker influence the model?” It is “what authority can that influence reach?”
Prompt-to-sink thinking is especially useful for coding agents, long-lived agents, and Agentic DeFi systems. In a coding agent, the sink may be a shell command, git mutation, or CI change. In a long-lived agent, it may be a queued task or delayed action that executes under stronger authority later. In a financial agent, the sink may be a wallet signing request, router selection, bridge destination, or approval to spend funds.
Using this lens changes how controls are evaluated. Filters at input time matter, but they are not enough. Auditors also need to inspect argument provenance, destination validation, permission attenuation, approval semantics, and sink-time policy enforcement. A system can survive some prompt injection exposure if the sink controls are strong. It can also fail catastrophically with mild prompt influence if the sink is overpowered and weakly constrained.
Related Terms
Prompt Injection
Attack technique manipulating AI system inputs to bypass safety controls or extract unauthorized information.
Trust Boundary
Interface where data enters protocol or assets move between components, representing highest-risk areas requiring focused security analysis.
Tool Integration Security
Security practices for validating and controlling how AI systems interact with external tools, APIs, and services to prevent unauthorized actions.
Data Exfiltration
Unauthorized transfer of data from a system to an external destination controlled by an attacker, often performed covertly to avoid detection.
Need expert guidance on Prompt-to-Sink?
Our team at Zealynx has deep expertise in blockchain security and DeFi protocols. Whether you need an audit or consultation, we're here to help.
Get a Quote