Risk · R-059 · Agentic & Autonomous Systems
Function-calling hallucination
An agent invents a tool, a parameter or the result of a call, and the fabricated step is executed or relied on as though it had happened.
- Severity
- Medium
- Audience
- Practitioner
- Frameworks
- AML.M0033 · Confabulation · ASI02
- Responsible AI domain
- Lifecycle stage
- Reviewed
- 2026-11-10
What it is
This is confabulation applied to actions. The model produces a call to a function that does not exist, supplies an argument it made up, such as an account number, or reports that a call succeeded when it was never made. It is separate from agent tool misuse, where a real tool is really called in a harmful way.
How it happens
- The model fills a required parameter with a plausible value when it has no real one.
- A tool name is generated from pattern, not from the list provided.
- A failed or skipped call is summarised to the user as complete.
- A long task exceeds the context, and earlier results are reconstructed from memory.
Why it matters
A fabricated parameter can direct a real operation at the wrong target. A fabricated result leaves the organisation believing something was done, such as a notification sent or a record updated, when it was not.
Warning signs
- Tool calls fail validation for unknown names or malformed arguments.
- Identifiers appear in calls that occur nowhere in the input.
- The agent's summary lists steps absent from the execution log.
- Failure rates rise with task length.
Mitigating controls
Primary controls
- Output validation and guardrails Preventive
- Validates that a called tool exists and that parameters and results are well formed. Every model output is validated against a schema and sanitised by deterministic code before any downstream system, tool or user interface acts on it.
Supporting controls
- Agent action tracing Detective
- Shows which calls were actually executed. Every agent action is recorded with the instruction, plan, tool call, result and identity that produced it, in a form that allows the sequence to be reconstructed.
- Evaluation suite and regression testing Detective
- Tests tool-use accuracy on each change. A maintained set of test cases with expected results is run on every change to model, prompt, data or tools, and the results are compared with the approved baseline.
Framework and clause references
| Framework | Clause | Title |
|---|---|---|
| MITRE ATLAS | AML.M0033 | Input and Output Validation for AI Agent Components Validation of agent inputs and outputs. |
| NIST Generative AI Profile (NIST AI 600-1) | Confabulation | Confabulation Confabulation applied to tool use. |
| OWASP Top 10 for Agentic Applications | ASI02 | Tool Misuse and Exploitation A cause of tool misuse. |
Sources
- NIST Generative AI Profile NIST · framework
- MITRE ATLAS MITRE · framework
Related terms
How to cite
Axiom Verity (2026). Function-calling hallucination. Reference Library, R-059. https://axiom-verity.com/risks/function-calling-hallucination. Reviewed 2026-11-10.
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