The Misattribution Gap: When Memory Poisoning Looks Like Model Failure in Agentic AI Systems
The paper discusses the Misattribution Gap in multi-agent AI systems, where memory-layer attacks mimic model failures. This leads to incorrect remediation efforts by defenders, as they often misattribute the source of misconduct. The authors propose new methods to identify and mitigate these attacks effectively.
- ▪The Misattribution Gap occurs when memory-layer attacks produce behaviors that appear to be model failures.
- ▪The authors introduce Semantic Norm Drift (SND) as a distinct cause of agent misconduct, separate from model misalignment.
- ▪Their research shows that existing attribution systems frequently misidentify the source of failures, leading to ineffective defenses.
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Record
| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.22842 |
| Publication time | Mon, 25 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-25T04:07:35.648Z |
| Last seen | 2026-05-25T04:07:35.648Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | _B-KqQfDeBd_ |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Cryptography and Security arXiv:2605.22842 (cs) [Submitted on 12 May 2026] Title:The Misattribution Gap: When Memory Poisoning Looks Like Model Failure in Agentic AI Systems Authors:Tanzim Ahad, Ismail Hossain, Md Jahangir Alam, Sai Puppala, Syed Bahauddin Alam, Sajedul Talukder View a PDF of the paper titled The Misattribution Gap: When Memory Poisoning Looks Like Model Failure in Agentic AI Systems, by Tanzim Ahad and 5 other authors View PDF HTML (experimental) Abstract:Multi-agent AI pipelines typically assume that agent misconduct originates from model misalignment.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
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