Paper Citation Record · LEDGER

Reinforcement Learning for Automated Cybersecurity Penetration Testing

As of 7 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2507.02969.

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

pith.paper-citation-record.v1
2507.02969 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:31:51.330427Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

25 of 25 outbound references displayed

verified exact5
verified fuzzy3
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b916c989-a1ad-40ea-bb76-404ef00cfa2b · outbound

This paper cites Cyber-security and reinforcement learning — A brief survey.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Cyber-security and reinforcement learning — A brief survey

Reference 1

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T21:31:53.607008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1a976ebd-3014-43ef-b89d-9b7ace11c9d7 · outbound

This paper cites Automated penetration testing based on a threat model.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Automated penetration testing based on a threat model

Reference 2

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T21:31:53.315486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b50cbf14-f74e-40a0-bd34-f55833b567e8 · outbound

This paper cites Emergence of Scaling in Random Networks.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Emergence of Scaling in Random Networks

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:51.220039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 946ff248-9171-4296-a375-fc08f3b04a29 · outbound

This paper cites Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:51.228923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60d25505-05de-4ce5-ba4f-f063bcbd2134 · outbound

This paper cites CYBERSHIELD : A Competitive Simulation Environment for Training AI in Cybersecurity.

Reinforcement Learning for Automated Cybersecurity Penetration Testing CYBERSHIELD : A Competitive Simulation Environment for Training AI in Cybersecurity

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:51.233866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd00d303-045b-4d93-a907-38cd5cd365ad · outbound

This paper cites Adversarial Reinforcement Learning in a Cyber Security Simulation.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Adversarial Reinforcement Learning in a Cyber Security Simulation

Reference 6

Resolution: verified exact; doi, observed 2026-08-06T21:31:51.530619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dfdec8b9-e949-4d1c-8a6a-b1fc78732014 · outbound

This paper cites CybORG++: An Enhanced Gym for the Development of Autonomous Cyber Agents.

Reinforcement Learning for Automated Cybersecurity Penetration Testing CybORG++: An Enhanced Gym for the Development of Autonomous Cyber Agents

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:51.243605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb3db847-1225-45f8-b26a-d630b8b239c9 · outbound

This paper cites Using Cyber Terrain in Reinforcement Learning for Penetration Testing.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Using Cyber Terrain in Reinforcement Learning for Penetration Testing

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:31:52.981788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 93b09098-bfa1-4f1b-9b9d-d23088c23361 · outbound

This paper cites Ghanem and Thomas M.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Ghanem and Thomas M

Reference 9

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T21:31:52.814174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9dc4a3bf-7dec-40e9-b5a8-5d34482c9165 · outbound

This paper cites Ghanem and Thomas M.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Ghanem and Thomas M

Reference 10

Resolution: verified exact; doi, observed 2026-08-06T21:31:51.500561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a90084e8-b6b8-4eb9-be1d-05072f956d2b · outbound

This paper cites Soft Actor-Critic Algorithms and Applications.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Soft Actor-Critic Algorithms and Applications

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:51.262249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 769a2449-985a-441a-8f31-9d48c72c4f96 · outbound

This paper cites Automated Penetration Testing Using Deep Reinforcement Learning.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Automated Penetration Testing Using Deep Reinforcement Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:51.267267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d731883-4939-4a8d-b240-fa2e638de76f · outbound

This paper cites Prokopczyk, Yusra Al-Khazraji, Marek Matuszak, Mário Pinto, Edgar Marques, and Evridiki Ntagiou.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Prokopczyk, Yusra Al-Khazraji, Marek Matuszak, Mário Pinto, Edgar Marques, and Evridiki Ntagiou

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:31:54.226859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9edae91f-20e1-42af-b198-2bef61896971 · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Playing Atari with Deep Reinforcement Learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:51.275967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48358497-3f10-44ae-bd30-3d3d220c8014 · outbound

This paper cites PenGym : Realistic training environment for reinforcement learning pentesting agents.

Reinforcement Learning for Automated Cybersecurity Penetration Testing PenGym : Realistic training environment for reinforcement learning pentesting agents

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:51.281568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6d613fc-d824-4faf-913f-978fa8b8321b · outbound

This paper cites Multiobjective Tree - Structured Parzen Estimator.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Multiobjective Tree - Structured Parzen Estimator

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:51.285956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c791f46-1a5a-4a9c-b22c-8875137b69e6 · outbound

This paper cites An AI - Based Approach for Automating Penetration Testing.

Reinforcement Learning for Automated Cybersecurity Penetration Testing An AI - Based Approach for Automating Penetration Testing

Reference 17

Resolution: verified exact; raw_fallback, observed 2026-08-06T21:31:52.413680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c198d644-a8a7-45a7-a1af-93250f8625ca · outbound

This paper cites Bahaa-Eldin, and Zt Fayed.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Bahaa-Eldin, and Zt Fayed

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:51.295345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf9cc994-bb72-416b-9731-21b131cb2ce7 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Proximal Policy Optimization Algorithms

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:51.299782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98bc48af-4cb4-42e1-aa2a-2798c6e59b98 · outbound

This paper cites Autonomous Penetration Testing using Reinforcement Learning.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Autonomous Penetration Testing using Reinforcement Learning

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:31:52.052781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b0ead1a1-27f0-4494-af25-ee204abbeda7 · outbound

This paper cites POMDP + Information - Decay : Incorporating Defender 's Behaviour in Autonomous Penetration Testing.

Reinforcement Learning for Automated Cybersecurity Penetration Testing POMDP + Information - Decay : Incorporating Defender 's Behaviour in Autonomous Penetration Testing

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:31:54.036382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0b71a4f9-6eb2-4e88-8dc1-0f1f4c656ff0 · outbound

This paper cites Hameed, and Min Xu.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Hameed, and Min Xu

Reference 22

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T21:31:51.883280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation deed1063-266c-4cc0-a404-41faaf89ca6f · outbound

This paper cites Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:51.321684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc0a2392-002f-4140-9c66-963613e04a08 · outbound

This paper cites Reinforcement Learning for Automatic Test Case Prioritization and Selection in Continuous Integration.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Reinforcement Learning for Automatic Test Case Prioritization and Selection in Continuous Integration

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:51.326203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50f84214-c31c-4fd1-a2b2-5b4991db34a9 · outbound

This paper cites Sutton and Andrew G.

Reinforcement Learning for Automated Cybersecurity Penetration Testing Sutton and Andrew G

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:31:53.829629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.