Paper Citation Record · LEDGER

Exploring LLMs for Malware Detection: Review, Framework Design, and Countermeasure Approaches

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2409.07587.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2409.07587 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:45:53.237300Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T04:19:33.747087Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b988814d-deff-4e12-b1e0-681ec3e5cb7f · inbound

MGC: A Compiler Framework Exploiting Compositional Blindness in Aligned LLMs for Malware Generation cites this paper.

MGC: A Compiler Framework Exploiting Compositional Blindness in Aligned LLMs for Malware Generation Exploring LLMs for Malware Detection: Review, Framework Design, and Countermeasure Approaches

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T20:45:53.237300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06a329de-618e-4063-b0ee-c47458e45284 · inbound

Empirical Evaluation of Concept Drift in ML-Based Android Malware Detection cites this paper.

Empirical Evaluation of Concept Drift in ML-Based Android Malware Detection Exploring LLMs for Malware Detection: Review, Framework Design, and Countermeasure Approaches

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T11:21:38.177587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d283d974-b311-473f-9913-0cbf0943b459 · inbound

TraceRAG: A LLM-Based Framework for Explainable Android Malware Detection and Behavior Analysis cites this paper.

TraceRAG: A LLM-Based Framework for Explainable Android Malware Detection and Behavior Analysis Exploring LLMs for Malware Detection: Review, Framework Design, and Countermeasure Approaches

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-04T20:52:33.124418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed287650-8aae-4599-8832-05804fc4637c · inbound

Benchmarking LLM-Assisted Blue Teaming via Standardized Threat Hunting cites this paper.

Benchmarking LLM-Assisted Blue Teaming via Standardized Threat Hunting Exploring LLMs for Malware Detection: Review, Framework Design, and Countermeasure Approaches

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:55.997378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9087399d-dd4c-4bdf-946d-bbf2ac2d6306 · inbound

Can Small GenAI Language Models Rival Large Language Models in Understanding Application Behavior? cites this paper.

Can Small GenAI Language Models Rival Large Language Models in Understanding Application Behavior? Exploring LLMs for Malware Detection: Review, Framework Design, and Countermeasure Approaches

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T22:04:09.943222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd7ef27d-703b-45ca-ae00-7a70a11ee9b0 · inbound

Efficient Code Analysis via Graph Representation Learning-Guided Large Language Models cites this paper.

Efficient Code Analysis via Graph Representation Learning-Guided Large Language Models Exploring LLMs for Malware Detection: Review, Framework Design, and Countermeasure Approaches

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T09:44:53.702805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0dc9d4a2-3869-4bab-bf9d-b368c578e526 · inbound

LCC-LLM: Leveraging Code-Centric Large Language Models for Malware Attribution cites this paper.

LCC-LLM: Leveraging Code-Centric Large Language Models for Malware Attribution Exploring LLMs for Malware Detection: Review, Framework Design, and Countermeasure Approaches

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:21:08.554813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9aa936aa-da7b-465c-94c6-4297e3cf5bff · inbound

Benchmarking Large Language Models for IoC Recovery under Adversarial Code Obfuscation and Encryption cites this paper.

Benchmarking Large Language Models for IoC Recovery under Adversarial Code Obfuscation and Encryption Exploring LLMs for Malware Detection: Review, Framework Design, and Countermeasure Approaches

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:50:58.042358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 81e5f715-78c8-49a5-88fa-7f13393ab60d · inbound

A Large Language Model Approach to Generating Bypass Rules for Malware Evasion in Analysis Sandbox cites this paper.

A Large Language Model Approach to Generating Bypass Rules for Malware Evasion in Analysis Sandbox Exploring LLMs for Malware Detection: Review, Framework Design, and Countermeasure Approaches

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-22T08:31:16.951226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d1b926f8-8163-4b60-8f87-8c839c92abfe · inbound

Multi-View Decompilation for LLM-Based Malware Classification cites this paper.

Multi-View Decompilation for LLM-Based Malware Classification Exploring LLMs for Malware Detection: Review, Framework Design, and Countermeasure Approaches

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-07-04T04:19:33.749759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ae8e0396-234c-4d22-ba98-6560949a8ed1 · inbound

Small, Free, and Effective: Orchestrating Open-Weight Small Language Models to Outperform Single LLM for Malware Analysis cites this paper.

Small, Free, and Effective: Orchestrating Open-Weight Small Language Models to Outperform Single LLM for Malware Analysis Exploring LLMs for Malware Detection: Review, Framework Design, and Countermeasure Approaches

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T10:30:41.262977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.