Alibi: Adversarial Legitimacy Injection in Binaries Against LLM Malware
This paper shows that the same reasoning capability introduces a new attack surface. We present ALIBI, a semantic cover story attack against frontier LLM-based malware analyzers. ALIBI adds a small, non-executed read-only section to a compiled binary, containing a coherent but false security product narrative, without altering imports or executable behavior.
- ▪This paper shows that the same reasoning capability introduces a new attack surface.
- ▪We present ALIBI, a semantic cover story attack against frontier LLM-based malware analyzers.
- ▪ALIBI adds a small, non-executed read-only section to a compiled binary, containing a coherent but false security product narrative, without altering imports or executable behavior.
Hacker News (AI / LLM) files mainly under ai. We currently carry 5,469 of its stories.
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | arXiv.org |
| Canonical URL | https://arxiv.org/abs/2609.19722 |
| Publication time | Fri, 18 Sep 2026 11:07:08 +0000 |
| Retrieval time | 2026-09-18T11:13:45.297Z |
| Last seen | 2026-09-18T11:13:45.297Z |
| 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 | YjYL-E2F4Rfw · 1 stories |
| 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)
WeSearch handling by dimension
| 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:2609.19722 (cs) [Submitted on 17 Sep 2026] Title:ALIBI: Adversarial Legitimacy Injection in Binary Input against LLM Malware Analyzers Authors:Hyeongjun Choi, Wonyoung Jung, Haehoon Seo, Sungyup Nam View a PDF of the paper titled ALIBI: Adversarial Legitimacy Injection in Binary Input against LLM Malware Analyzers, by Hyeongjun Choi and 3 other authors View PDF HTML (experimental) Abstract:Large language models are being integrated into malware triage workflows as reasoning components that summarize static evidence and produce analyst-facing verdicts. This paper shows that the same reasoning capability introduces a new attack surface. We present ALIBI, a semantic cover story attack against frontier LLM-based malware analyzers.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv.org.
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