Referee Report — arXiv:2606.04329 "Memory Poisoning": Resolving a Conflicting-Claims Discrepancy Through Primary-Source Verification

A verification referee report resolving a conflicting-claims discrepancy about arXiv:2606.04329 ("From Untrusted Input to Trusted Memory: A Systematic Study of Memory Poisoning Attacks in LLM Agents", Dash, Ge, Jain, Shah, Shang). Two secondary-source claims about the paper's headline attack-success numbers were circulating: a "70–95% vulnerability" figure (amplified on Reddit) versus "average ASR of 50.46% and RSR of 41.05% across both agents." We verified both claims directly against the paper's raw HTML full text using grep-based textual confirmation, independent of any fetch/summarization layer. Finding: the 50.46% / 41.05% figures are the paper's own verbatim headline statistic (Introduction, contributions list), and reproduce exactly as the average of the two tested agents' averages (OpenClaw, HERMES). The "70–95%" figure appears nowhere in the paper as a summary; it is a cherry-picked over-generalization of the single most-vulnerable agent's strong-signal attack subset (a lone 92.76% maximum), not the general finding. The arXiv ID is real and resolves correctly — this is not a hallucinated citation, but a selective-reading error, and the Sources C / Reddit quotation should be corrected or contextualized downstream. The report doubles as a case study in source-verification discipline: why numeric claims must be traced to the primary source, and why fetch/summarizer layers require raw-text cross-verification even for location attributions. AI-transparency note: The authors of this record operate under human direction. This report was drafted by an AI agent, cross-family jury-reviewed (blind; producer family excluded), and reviewed by a human before publication.

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Publication Details

Journal
arXiv (Cornell University)
Published
2026-08-24
DOI
https://doi.org/10.5281/zenodo.22084116
Primary Topic
Security and Verification in Computing
Type
preprint
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Referee Report — arXiv:2606.04329 "Memory Poisoning": Resolving a Conflicting-Claims Discrepancy Through Primary-Source Verification

Mustafa Melikoğlu, Yağız Deniz Altınbaş, Tayfun Tanrıöver
arXiv (Cornell University)
Security and Verification in Computing
preprint

Referee Report — arXiv:2606.04329 "Memory Poisoning": Resolving a Conflicting-Claims Discrepancy Through Primary-Source Verification

Mustafa Melikoğlu, Yağız Deniz Altınbaş, Tayfun Tanrıöver
preprint en

Abstract

A verification referee report resolving a conflicting-claims discrepancy about arXiv:2606.04329 ("From Untrusted Input to Trusted Memory: A Systematic Study of Memory Poisoning Attacks in LLM Agents", Dash, Ge, Jain, Shah, Shang). Two secondary-source claims about the paper's headline attack-success numbers were circulating: a "70–95% vulnerability" figure (amplified on Reddit) versus "average ASR of 50.46% and RSR of 41.05% across both agents." We verified both claims directly against the paper's raw HTML full text using grep-based textual confirmation, independent of any fetch/summarization layer. Finding: the 50.46% / 41.05% figures are the paper's own verbatim headline statistic (Introduction, contributions list), and reproduce exactly as the average of the two tested agents' averages (OpenClaw, HERMES). The "70–95%" figure appears nowhere in the paper as a summary; it is a cherry-picked over-generalization of the single most-vulnerable agent's strong-signal attack subset (a lone 92.76% maximum), not the general finding. The arXiv ID is real and resolves correctly — this is not a hallucinated citation, but a selective-reading error, and the Sources C / Reddit quotation should be corrected or contextualized downstream. The report doubles as a case study in source-verification discipline: why numeric claims must be traced to the primary source, and why fetch/summarizer layers require raw-text cross-verification even for location attributions. AI-transparency note: The authors of this record operate under human direction. This report was drafted by an AI agent, cross-family jury-reviewed (blind; producer family excluded), and reviewed by a human before publication.

arXiv (Cornell University)
Dr. A. Ramachandran's Diabetes Hospitals (IN)
Security and Verification in Computing
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