Paper Citation Record · LEDGER

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions

As of 5 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2605.08763.

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

pith.paper-citation-record.v1
2605.08763 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-12T03:32:53.690026Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

42 of 42 outbound references displayed

verified exact2
verified fuzzy40
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 359f98c0-2bcc-448b-aea5-0c9ca13e381a · outbound

This paper cites Securefalcon: Are we there yet in automated software vulnerability detection with llms?.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Securefalcon: Are we there yet in automated software vulnerability detection with llms?

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.831348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fd7b7197-1065-4f50-ba06-8f1aea9c8a67 · outbound

This paper cites Cve-llm: Ontology-assisted automatic vulnerability evaluation using large language models.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Cve-llm: Ontology-assisted automatic vulnerability evaluation using large language models

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.839144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a1d53450-03c8-4f14-9aa1-8cfc609be01f · outbound

This paper cites Benchmarking llms and llm-based agents in practical vulnerability detection for code repositories.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Benchmarking llms and llm-based agents in practical vulnerability detection for code repositories

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:48.030715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4d2f2a20-220f-4e7f-833d-8784981b589c · outbound

This paper cites {LLMxCPG}:{Context-Aware}vulnerability detection through code property{Graph-Guided}large language models.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions {LLMxCPG}:{Context-Aware}vulnerability detection through code property{Graph-Guided}large language models

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:48.035469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8c40ae0b-2af2-47ae-a911-3d724a3ef7ef · outbound

This paper cites Expert insights into advanced persistent threats: Analysis, attribution, and challenges.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Expert insights into advanced persistent threats: Analysis, attribution, and challenges

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:48.052949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 819b4287-d91f-4197-8ada-bec1cf1ae4da · outbound

This paper cites A survey of intrusion detection techniques for cyber-physical systems.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions A survey of intrusion detection techniques for cyber-physical systems

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.938819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f401cc81-0dcb-4185-b7f2-8f2c9410dc25 · outbound

This paper cites A survey of data mining and machine learning methods for cyber security intrusion detection.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions A survey of data mining and machine learning methods for cyber security intrusion detection

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.923386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9a9cd146-9d5e-4c4d-8a05-6315a005dcb4 · outbound

This paper cites We have a package for you! a comprehensive analysis of package hallucinations by code generating{LLMs}.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions We have a package for you! a comprehensive analysis of package hallucinations by code generating{LLMs}

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.933771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dbd087bf-b2a5-471a-bdff-3e0d343294f2 · outbound

This paper cites Llm-check: Investigating detection of hallucinations in large language models.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Llm-check: Investigating detection of hallucinations in large language models

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.915941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dd406e47-f738-4096-a82d-ba6bc8e0d4b8 · outbound

This paper cites Flashdecoding++next: High throughput llm inference with latency and memory optimization.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Flashdecoding++next: High throughput llm inference with latency and memory optimization

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.910613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2752cf1b-b850-4f50-bf1f-ec41bea0922b · outbound

This paper cites Teams of llm agents can exploit zero-day vulnerabilities.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Teams of llm agents can exploit zero-day vulnerabilities

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.928166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5adf5413-fcc2-4bab-803e-9cdab86da439 · outbound

This paper cites Co-redteam: Orchestrated security discovery and exploitation with llm agents.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Co-redteam: Orchestrated security discovery and exploitation with llm agents

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:16:29.862435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d3c98e72-ce2b-44ce-8ea1-f24eb228c42b · outbound

This paper cites Liva: A multi-agent llm-assisted system for iot vulnerability analysis.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Liva: A multi-agent llm-assisted system for iot vulnerability analysis

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:48.019517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 965554d7-aad1-4842-9a19-e7b373f70e20 · outbound

This paper cites Agentchain: Blockchain-empowered multi-agent coordination for trustworthy llm question-answering systems.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Agentchain: Blockchain-empowered multi-agent coordination for trustworthy llm question-answering systems

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:48.047828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b9ed6b64-c7af-4b3d-af75-81a12a3774b9 · outbound

This paper cites Game theory and multi- agent reinforcement learning.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Game theory and multi- agent reinforcement learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:48.041232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7b0286ec-2620-4746-a939-222628267f55 · outbound

This paper cites Game theoretical applications for multi-agent sys- tems.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Game theoretical applications for multi-agent sys- tems

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.884052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c05457bb-4fa1-496e-8dd4-83bee74a2774 · outbound

This paper cites A hierarchical game-theoretic decision- making for cooperative multiagent systems under the presence of adver- sarial agents.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions A hierarchical game-theoretic decision- making for cooperative multiagent systems under the presence of adver- sarial agents

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.896731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fdc415f9-36aa-48e5-bda0-d1fabe88d938 · outbound

This paper cites A game-theoretic framework for managing risk in multi-agent systems.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions A game-theoretic framework for managing risk in multi-agent systems

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.876826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e044911f-20b4-4c87-8aba-7ef961bf1fd3 · outbound

This paper cites Optimal robust formation of multi-agent systems as adversarial graphical apprentice games with inverse reinforcement learning.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Optimal robust formation of multi-agent systems as adversarial graphical apprentice games with inverse reinforcement learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.890922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6b20d006-eb4b-4ad9-a42a-64fd1ed92b69 · outbound

This paper cites The trust paradox in llm-based multi-agent systems: When collaboration becomes a security vulnerability.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions The trust paradox in llm-based multi-agent systems: When collaboration becomes a security vulnerability

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:16:29.868168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 178934f2-fe76-45a8-af6d-b680251ff788 · outbound

This paper cites A robust mean-field actor-critic reinforcement learning against adversarial perturbations on agent states.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions A robust mean-field actor-critic reinforcement learning against adversarial perturbations on agent states

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.862343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ff230780-0f94-49f9-80e0-10ff7568cb41 · outbound

This paper cites Where will they go? predicting fine-grained adversarial multi-agent motion using conditional variational autoencoders.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Where will they go? predicting fine-grained adversarial multi-agent motion using conditional variational autoencoders

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.866792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8478cc8e-b36d-48da-b3f5-cecdee62ee5f · outbound

This paper cites Zero-shot autonomous vehicle policy transfer: From simulation to real-world via adversarial learning.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Zero-shot autonomous vehicle policy transfer: From simulation to real-world via adversarial learning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.850856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d373e6a2-6802-4cda-ba90-9cde3f3e406f · outbound

This paper cites Certifiably robust policy learning against adversarial multi- agent communication.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Certifiably robust policy learning against adversarial multi- agent communication

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.846453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 69d12356-393b-46a6-91e7-972383705514 · outbound

This paper cites Coordinated llm multi-agent systems for collaborative question-answer generation.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Coordinated llm multi-agent systems for collaborative question-answer generation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.857629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 218f3740-b0f7-442d-912e-7f6852d1c366 · outbound

This paper cites Autohma-llm: Efficient task coordination and execution in heteroge- neous multi-agent systems using hybrid large language models.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Autohma-llm: Efficient task coordination and execution in heteroge- neous multi-agent systems using hybrid large language models

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.871675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 97d643a3-d68a-4c8f-bb6e-14b1c88ea665 · outbound

This paper cites Llm-based multi-agent systems for software engineering: Literature review, vision, and the road ahead.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Llm-based multi-agent systems for software engineering: Literature review, vision, and the road ahead

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.903516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dd36b291-0199-465e-a27a-3a7ff8fb0bcf · outbound

This paper cites Advanced smart contract vulnerability detection via llm-powered multi-agent systems.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Advanced smart contract vulnerability detection via llm-powered multi-agent systems

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.944655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation af177b76-4a70-430b-9db3-0e498138a8cf · outbound

This paper cites Towards transparent and incentive-compatible collaboration in decentralized llm multi-agent systems: A blockchain-driven approach.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Towards transparent and incentive-compatible collaboration in decentralized llm multi-agent systems: A blockchain-driven approach

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.966516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6077ddb7-9b34-44e4-98fa-0c1a58de9858 · outbound

This paper cites Many heads are better than one: Improved scientific idea generation by a llm-based multi-agent system.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Many heads are better than one: Improved scientific idea generation by a llm-based multi-agent system

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.990817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b8b70c78-abc6-4620-81fb-a927bd3c47d1 · outbound

This paper cites Fincon: A synthesized llm multi-agent system with conceptual verbal reinforcement for enhanced financial decision making.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Fincon: A synthesized llm multi-agent system with conceptual verbal reinforcement for enhanced financial decision making

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:48.060428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ba3179ca-fb89-4a26-a013-12ae786142ee · outbound

This paper cites Insight agents: An llm- based multi-agent system for data insights.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Insight agents: An llm- based multi-agent system for data insights

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:48.002245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 025bc649-4433-4817-8373-f8fe55d9f2c2 · outbound

This paper cites Eduplanner: Llm-based multi-agent systems for customized and intelligent instruc- tional design.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Eduplanner: Llm-based multi-agent systems for customized and intelligent instruc- tional design

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:48.007174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 504478c2-2a16-41cf-8552-31c8af6ff4d4 · outbound

This paper cites Masa: Llm-driven multi-agent systems for autoformalization.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Masa: Llm-driven multi-agent systems for autoformalization

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:48.024843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation abb6a32b-d6b2-4c74-ba8a-97b894bc7534 · outbound

This paper cites Llm-based multi-agent systems are scalable graph generative models.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Llm-based multi-agent systems are scalable graph generative models

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:48.065977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 04000155-5bac-413c-8e8b-18b2e0432780 · outbound

This paper cites Large language model enhanced multi-agent systems for 6g communications.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Large language model enhanced multi-agent systems for 6g communications

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.977804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 92271156-bd16-49d8-a4f2-d71e80fe2850 · outbound

This paper cites Towards efficient llm grounding for embodied multi-agent collaboration.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Towards efficient llm grounding for embodied multi-agent collaboration

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.984476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5984e4c8-df7a-4089-8efa-7757df94157c · outbound

This paper cites Red-teaming llm multi-agent systems via communication attacks.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Red-teaming llm multi-agent systems via communication attacks

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.972663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c2293857-87b4-4ede-ba38-3c3b3f4d219d · outbound

This paper cites Agents under siege: Breaking pragmatic multi-agent llm systems with optimized prompt attacks.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Agents under siege: Breaking pragmatic multi-agent llm systems with optimized prompt attacks

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.953948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d798aca5-e17e-414d-acec-d61df300e6db · outbound

This paper cites G-safeguard: A topology-guided security lens and treatment on llm-based multi-agent systems.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions G-safeguard: A topology-guided security lens and treatment on llm-based multi-agent systems

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.961859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7e2df8d9-48ec-4e14-9ecd-f37f83ab912d · outbound

This paper cites Masrouter: Learning to route llms for multi-agent systems.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Masrouter: Learning to route llms for multi-agent systems

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:48.012896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 267a093a-9ed9-4342-b329-cf82a8e0393f · outbound

This paper cites Agenttaxo: Dissecting and benchmarking token distribution of llm multi-agent systems.

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions Agenttaxo: Dissecting and benchmarking token distribution of llm multi-agent systems

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-12T19:16:47.996954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

No inbound Pith citation observations are available.