Narrative Manipulation, Malinfluence Operations, and Cognitive Warfare Through Large Language Model Poisoning with Adversarial Noise

Curator note

With every novel technology, exploitable vulnerabilities will arise. Adversaries will attempt to undermine integrity and further their own agendas through opportunistic exploitations. In the world of artificial intelligence development, one potential vulnerability and avenue of subversion is the use of https://mipb.ikn.army.mil/issues/jul-dec-2025/narrative-manipulation-malinfluence-operations-and-cognitive-warfare-through-large-language-model-poisoning-with-adversarial-noise/#glossary-1 against trained, structured data. This adversarial noise, also known as noisy data, has the potential to shape future operational readiness postures, or even conflict itself, in unprecedented ways. If unleashed against military data corpora and associated large language models (LLMs), adversarial noise will undoubtedly create dissonant ramifications in operational spaces. Specifically, these attacks will affect servicemembers’ individual and collective narratives, sentiments toward organizational trust, and overall cognitive security, thus jeopardizing readiness. This article will highlight the threat adversarial noise poses to the psycho-cognitive states of servicemembers and their organizations through malinfluence and manipulation.