An Application-Layer Multi-Modal Covert-Channel Reference Monitor for LLM Agent Egress
The paper presents a reference monitor designed to prevent data leakage from large language model (LLM) agents. It outlines a multi-modal approach that includes a text pipeline, media scramblers, and a method for measuring residual capacity of covert channels. The implementation aims to ensure that all potential covert channels are effectively managed and monitored.
- ▪The reference monitor includes a text pipeline with ten capacity-reducing stages.
- ▪It features media scramblers that limit audio and image data to prevent covert channels.
- ▪The system measures residual capacity to ensure data leakage is minimized.
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| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.20734 |
| Publication time | Fri, 22 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-22T04:02:00.009Z |
| Last seen | 2026-05-22T04:02:00.009Z |
| 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 | zmfBW6L_hoB5 |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
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| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
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| 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:2605.20734 (cs) [Submitted on 20 May 2026] Title:An Application-Layer Multi-Modal Covert-Channel Reference Monitor for LLM Agent Egress Authors:Alfredo Metere View a PDF of the paper titled An Application-Layer Multi-Modal Covert-Channel Reference Monitor for LLM Agent Egress, by Alfredo Metere View PDF HTML (experimental) Abstract:A large language model (LLM) agent that sends messages can leak data inside them. Destination allowlists and content scanners do not police whether an otherwise-benign payload is itself a covert channel: a compromised agent encodes bits in zero-width characters, homoglyphs, whitespace, base64, JavaScript Object Notation (JSON) key ordering, message timing or size -- and, in binary egress, in…
Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
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