Criticalcascading

Hallucination Propagation

Fabricated information from one agent spreads through the system as other agents accept and build upon it.

Overview

How to Detect

Confident assertions appear in outputs without grounding in original sources. Multiple agents reference the same fabricated "facts." Hallucinated details become increasingly elaborate.

Root Causes

LLMs generate plausible but fabricated content. Downstream agents lack access to ground truth. No verification against original sources. Confirmation bias in multi-agent validation.

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Deep Dive

Overview

In the Internet of Agents, a hallucination is no longer merely a text generation error—it becomes an erroneous financial transaction, a corrupted database state, or a cascading failure propagating through a chain of trusted services.

The Propagation Mechanism

Stage 1: Genesis

An agent generates a plausible but fabricated fact:

Research Agent: "According to the 2024 Smith study,
the compound reduces inflammation by 47%."
(No such study exists)

Stage 2: Acceptance

Downstream agents accept the hallucination as fact:

Synthesis Agent: "Building on the Smith study's 47% finding..."

Stage 3: Elaboration

The fabrication gets embellished:

Writing Agent: "The landmark Smith study at Harvard
demonstrated a 47% reduction..."
(Now with fabricated institutional affiliation)

Stage 4: Citation Chain

Other parts of the system reference the "established" fact:

Multiple agents now cite "the well-documented Smith study"

Mutual Hallucination Reinforcement

A particularly dangerous pattern occurs when agents validate each other's hallucinations:

Agent A: "The capital of Australia is Sydney."
Agent B: "I agree with Agent A's analysis."
Agent A: "Agent B confirms my answer."
Both agents: High confidence in wrong answer.

This creates false consensus through mutual confirmation rather than independent verification.

Agent-Specific Hallucination Types

Research from 2025 identifies hallucinations unique to agent systems:

Tool Use Hallucination

Agent invokes a tool with fabricated parameters or misreports tool outputs.

Planning Hallucination

Agent claims to have completed steps it never executed.

Memory Hallucination

Agent "recalls" interactions or facts from previous turns that never occurred.

Coordination Hallucination

Agent reports coordination with other agents that didn't happen.

Detection Challenges

Agent hallucinations are harder to detect because:

  • They occur at any stage of the decision pipeline
  • They exhibit hallucinatory accumulation across steps
  • Inter-module dependencies obscure the origin
  • The "blast radius" expands with each propagation step

How to Prevent

Source Grounding: Require explicit citations with verifiable sources.

Independent Verification: Cross-check facts using different agents or retrieval systems.

Hallucination Detection Models: Deploy specialized classifiers to flag uncertain claims.

Provenance Tracking: Maintain clear lineage of where each fact originated.

Diverse Verification: Use different model families for generation and verification.

Self-Verification Mechanisms: Have agents introspectively review their own outputs.

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Real-World Examples

In the "Internet of Agents" safety research (2025), researchers demonstrated how a single fabricated data point could corrupt an entire agent network's knowledge base within minutes when agents treated peer outputs as trusted context.

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Tags
hallucinationfabricationpropagationverificationtrust

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