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Paper Citation Record · LEDGER

PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2411.05185.

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

pith.paper-citation-record.v1
2411.05185 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:37:02.819323Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T17:27:15.331121Z

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 a399437e-6145-4c39-b9d7-bd1dfb647aa8 · inbound

A Contemporary Survey of Large Language Model Assisted Program Analysis cites this paper.

A Contemporary Survey of Large Language Model Assisted Program Analysis PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 162

Resolution
unresolved
no resolver link, observed 2026-08-09T05:32:24.993991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T05:32:24.993991Z digest=sha256:b7bdd46ecef2e2f3f08178d0fdb62c445f05924eba52fe4e1fcde77296427c90

Observation 5bcd7228-fea3-41ee-ae2c-53020f9b7fd3 · inbound

CompileAgent: Automated Real-World Repo-Level Compilation with Tool-Integrated LLM-based Agent System cites this paper.

CompileAgent: Automated Real-World Repo-Level Compilation with Tool-Integrated LLM-based Agent System PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-15T23:37:02.819323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:37:02.819323Z digest=sha256:4eed0be109e474c6540993b97a862f522339a311118dbe2430d611d6753c2844

Observation 0e2e6e25-b83d-4066-b6ec-14c83f347d61 · inbound

RedTeamLLM: an Agentic AI framework for offensive security cites this paper.

RedTeamLLM: an Agentic AI framework for offensive security PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-15T22:33:52.314821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:33:52.314821Z digest=sha256:5dda43b8a3eb077c082bacfd7ddf18ef4f271876023f85d23f8867ddd6581087

Observation 36d896d3-ae88-4562-82d8-e46534cb3144 · inbound

AutoPentest: Enhancing Vulnerability Management With Autonomous LLM Agents cites this paper.

AutoPentest: Enhancing Vulnerability Management With Autonomous LLM Agents PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T21:15:52.724461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:15:52.724461Z digest=sha256:5b195d50da1afc46d97628a04ff415d0c9dc05c4a343cc7ceb93c0b962138638

Observation ec816484-21e7-4fed-9575-f4df88c70b56 · inbound

Benchmarking LLMs in an Embodied Environment for Blue Team Threat Hunting cites this paper.

Benchmarking LLMs in an Embodied Environment for Blue Team Threat Hunting PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-15T20:50:08.269294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:50:08.269294Z digest=sha256:8603756d1a54182049f3826a8b350cec2fade6fbbef0cea8cba1a0a2032e1eb9

Observation d64ca291-e643-462a-a141-1e7ae3517687 · inbound

Forewarned is Forearmed: A Survey on Large Language Model-based Agents in Autonomous Cyberattacks cites this paper.

Forewarned is Forearmed: A Survey on Large Language Model-based Agents in Autonomous Cyberattacks PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 171

Resolution
unresolved
no resolver link, observed 2026-08-15T20:28:59.533574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:28:59.533574Z digest=sha256:50db0dfd5bcbc662191ad6b6bc70b5cdcc8213d15c207c1b44930e62237f92ef

Observation 765fd2bc-8d44-40e1-9a46-5a34e78d7da0 · inbound

CRAKEN: Cybersecurity LLM Agent with Knowledge-Based Execution cites this paper.

CRAKEN: Cybersecurity LLM Agent with Knowledge-Based Execution PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T15:23:51.808707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:23:51.808707Z digest=sha256:d8bd83dfa118116956b64ea5945aacfe688c75fb566ec24154142266f74a1964

Observation 9ddc3fa9-6ccb-4b3d-adf8-4f5c89611e7f · inbound

An Agentic Flow for Finite State Machine Extraction using Prompt Chaining cites this paper.

An Agentic Flow for Finite State Machine Extraction using Prompt Chaining PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T17:17:30.502605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:17:30.502605Z digest=sha256:3175c997218701c604dadce800b4e3cdb2dc3f736cb70e080e6005095a9cb6a2

Observation 04bbe2d6-bc45-4d2a-be7d-ba719bcd974e · inbound

Enabling Cyber Security Education through Digital Twins and Generative AI cites this paper.

Enabling Cyber Security Education through Digital Twins and Generative AI PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:09.905231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:49:09.905231Z digest=sha256:a4d5bb73932b42d05d112792d8631951064630f17814823a5274dbdb4278a9c9

Observation 221dd976-71c1-45f5-8320-675fc192597c · inbound

Pixels to Play: A Foundation Model for 3D Gameplay cites this paper.

Pixels to Play: A Foundation Model for 3D Gameplay PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-05T18:41:20.708965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:41:20.708965Z digest=sha256:1af62ccc4620883eee099a2092531f43a8fca6d2a1b465bbeb7cafce0803d205

Observation 812fc49e-2059-403b-8262-6ca2f1969d3c · inbound

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing cites this paper.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-05T18:42:12.239014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:42:12.239014Z digest=sha256:a176c99d771d5a96ebc35f97a33988490b4575daa3fc38159afd81ed05da9572

Observation a91edd61-6292-4e68-994e-b5b0e915250b · inbound

Neuro-Symbolic AI for Cybersecurity: State of the Art, Challenges, and Opportunities cites this paper.

Neuro-Symbolic AI for Cybersecurity: State of the Art, Challenges, and Opportunities PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 166

Resolution
verified exact
arxiv_id, observed 2026-05-18T18:06:42.871063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-18T18:04:09.528381Z digest=sha256:52980eee005148aeabe28fbae573acfa419f3ddadcaa1592f8b12a20dbdd528e

Observation 822c3d1c-f698-4902-be20-5fe59bf02018 · inbound

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

Benchmarking LLM-Assisted Blue Teaming via Standardized Threat Hunting PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-04T14:42:59.126030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:42:59.126030Z digest=sha256:8108e76aff9dfb4af604cfac1082380219af366dc1a89863d3a1309561f3c9c8

Observation a86acb64-861f-45e4-a75b-66b36f8f5452 · inbound

Dynamic Cyber Ranges cites this paper.

Dynamic Cyber Ranges PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-11T22:16:53.736129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-08T03:04:03.611481Z digest=sha256:3f445f3aca44f7a7e840981842215138b689405c57c41651feb7478a1560c427

Observation 835f1e1f-85d2-4c2d-a21f-f4893c25a741 · inbound

Self-Adaptive Multi-Agent LLM-Based Security Pattern Selection for IoT Systems cites this paper.

Self-Adaptive Multi-Agent LLM-Based Security Pattern Selection for IoT Systems PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:51:44.375009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-09T19:04:48.453055Z digest=sha256:8925bb5944f9a4854b0a14fab879cec33e2b441e093697981d57be218ef68362

Observation 86d6e6c9-c41f-4d15-9dc6-512d2d5f93f6 · inbound

APT-Agent: Automated Penetration Testing using Large Language Models cites this paper.

APT-Agent: Automated Penetration Testing using Large Language Models PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-06-30T00:14:04.087248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-30T00:11:02.928108Z digest=sha256:7eb6da098d85520a9cc96c0589fbc2b07830f3cb6316e444d6aeb8504abd0e44

Observation 652ccea8-52d2-490f-be9f-b508bcdc84fb · inbound

Honeyval: A Comprehensive Evaluation Framework for LLM-powered HTTP Honeypots cites this paper.

Honeyval: A Comprehensive Evaluation Framework for LLM-powered HTTP Honeypots PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-06-29T07:03:12.686126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-29T07:02:43.125183Z digest=sha256:b4cd3593cd433611015ef47dae0cc793cd65da337e9db903c4bb7ff9e54028b8

Observation c3463a95-269c-4fbc-81a4-4b676d0e5e71 · inbound

How Reliable Are AI Attackers Against a Fixed Vulnerable Target? A 400-Run Empirical Study of LLM Penetration Testing Consistency cites this paper.

How Reliable Are AI Attackers Against a Fixed Vulnerable Target? A 400-Run Empirical Study of LLM Penetration Testing Consistency PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-06-29T14:13:30.548086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-29T06:53:48.841077Z digest=sha256:87dab3bfea4ae3141b7cc682631161287c4eb4779264bbb065196d27c51aea92

Observation 6e3089b5-d628-4483-9f6f-162893a6d3c6 · inbound

Synthetic APTs: the Collapse of TTP-Based Attribution cites this paper.

Synthetic APTs: the Collapse of TTP-Based Attribution PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-07-02T17:27:15.332645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-27T22:02:35.881369Z digest=sha256:4a140845fa75da9cc02e99d54f0df376b0b5677cbff46484d41f33d2958ccecb