Paper Citation Record · LEDGER

Towards Automated Penetration Testing: Introducing LLM Benchmark, Analysis, and Improvements

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2410.17141.

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

pith.paper-citation-record.v1
2410.17141 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:33:52.257217Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T14:13:30.541825Z

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 fdd28a2d-4608-4de5-9968-4a99302d333e · inbound

VulnBot: Autonomous Penetration Testing for A Multi-Agent Collaborative Framework cites this paper.

VulnBot: Autonomous Penetration Testing for A Multi-Agent Collaborative Framework Towards Automated Penetration Testing: Introducing LLM Benchmark, Analysis, and Improvements

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T16:13:36.041053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a22efd28-a463-4104-b7f6-13e3a822bacf · inbound

Can LLMs Hack Enterprise Networks? Autonomous Assumed Breach Penetration-Testing Active Directory Networks cites this paper.

Can LLMs Hack Enterprise Networks? Autonomous Assumed Breach Penetration-Testing Active Directory Networks Towards Automated Penetration Testing: Introducing LLM Benchmark, Analysis, and Improvements

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T23:10:10.989067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a0bf164-f41f-4680-9296-0bcc57a662e8 · inbound

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

RedTeamLLM: an Agentic AI framework for offensive security Towards Automated Penetration Testing: Introducing LLM Benchmark, Analysis, and Improvements

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T22:33:52.257217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51f2c4ae-d1b6-46c1-97bf-6176f93f6dc9 · 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 Towards Automated Penetration Testing: Introducing LLM Benchmark, Analysis, and Improvements

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:59.112267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca045685-3883-4ddd-b769-abd1decc876b · inbound

Recognition Without Mitigation: Ethical Frameworks in Autonomous Offensive-LLM Agent Research cites this paper.

Recognition Without Mitigation: Ethical Frameworks in Autonomous Offensive-LLM Agent Research Towards Automated Penetration Testing: Introducing LLM Benchmark, Analysis, and Improvements

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T05:10:20.073831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19ba5daa-5ebc-48bc-bbef-82f12dc40071 · 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 Towards Automated Penetration Testing: Introducing LLM Benchmark, Analysis, and Improvements

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-06-29T14:13:30.543210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.