Live In-Context Validation of LLM Vulnerabilities: An Addendum to Epistemological Resilience in Multi-Agentic AI Swarms
- 1Independent Researcher
Abstract
### Description
This manuscript serves as an official scientific **Addendum** and follow-up study to the previously published framework: *“Epistemological Resilience in Multi-Agentic AI Swarms: Architectural Blueprint for Adversarial Cognitive Pentesting And Strategic Corporate Risk Mitigation”* (Primary DOI: 10.5281/zenodo.23458304).
This paper documents a sequential, real-time in-context validation (Live Stress-Testing) conducted on a public high-reasoning Large Language Model (LLM) interface under an unauthenticated/anonymous state. Deploying the ERA Model's adversarial framework, the investigator captured concrete empirical evidence of structural algorithmic anomalies, specifically sequential **Context Drift** and **Sycophancy Bias** loops under strict logical interrogation. The findings strongly validate the core hypothesis of the ERA framework, reinforcing the necessity of moving high-reasoning cognitive workflows into independent local hardware topologies (specifically 32 GB physical RAM configurations).
**Related Identifiers Configuration:**
- Relationship: *isSupplementTo* -> DOI: 10.5281/zenodo.23458304 & *isSupplementedBy* -> DOI: 10.5281/zenodo.23547029
- License: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
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BibTeX
@misc{hidayatullah2026live,
title = {{Live In-Context Validation of LLM Vulnerabilities: An Addendum to Epistemological Resilience in Multi-Agentic AI Swarms}},
author = {Arief Hidayatullah},
howpublished = {Zenodo},
year = {2026},
month = oct,
doi = {10.5281/zenodo.23546347},
url = {https://zenodo.org/records/23546347},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - UNPB
TI - Live In-Context Validation of LLM Vulnerabilities: An Addendum to Epistemological Resilience in Multi-Agentic AI Swarms
AU - Arief Hidayatullah
PY - 2026
DA - 2026/10/21
PB - Zenodo
DO - 10.5281/zenodo.23546347
UR - https://zenodo.org/records/23546347
AB - ### Description This manuscript serves as an official scientific **Addendum** and follow-up study to the previously published framework: *“Epistemological Resilience in Multi-Agentic AI Swarms: Architectural Blueprint for Adversarial Cognitive Pentesting And Strategic Corporate Risk Mitigation”* (Primary DOI: 10.5281/zenodo.23458304). This paper documents a sequential, real-time in-context validation (Live Stress-Testing) conducted on a public high-reasoning Large Language Model (LLM) interface under an unauthenticated/anonymous state. Deploying the ERA Model's adversarial framework, the investigator captured concrete empirical evidence of structural algorithmic anomalies, specifically sequential **Context Drift** and **Sycophancy Bias** loops under strict logical interrogation. The findings strongly validate the core hypothesis of the ERA framework, reinforcing the necessity of moving high-reasoning cognitive workflows into independent local hardware topologies (specifically 32 GB physical RAM configurations). **Related Identifiers Configuration:** - Relationship: *isSupplementTo* -> DOI: 10.5281/zenodo.23458304 & *isSupplementedBy* -> DOI: 10.5281/zenodo.23547029 - License: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
ER -