Paper Citation Record · LEDGER

Multi-Agent Penetration Testing AI for the Web

As of 11 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 13 inbound Pith citation observations for arXiv:2508.20816.

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

pith.paper-citation-record.v1
2508.20816 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:51:05.162574Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T14:22:24.089668Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T13:54:44.435516Z

Reference resolution

29 of 29 outbound references displayed

verified exact0
verified fuzzy26
unresolved2
parse uncertain1
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6cfcb376-b90c-4fe5-97ff-70c4fc9da8fa · outbound

This paper cites A survey of business logic vulnerabilities in web applications.

Multi-Agent Penetration Testing AI for the Web A survey of business logic vulnerabilities in web applications

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.483373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7e440102-f8b2-45b5-9c57-2580ef4aa39e · outbound

This paper cites Pythia: Grammar-based fuzzing of rest apis with coverage- guided feedback and learning-based mutations.

Multi-Agent Penetration Testing AI for the Web Pythia: Grammar-based fuzzing of rest apis with coverage- guided feedback and learning-based mutations

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.476879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 25580caa-a9a7-48b8-a590-d8c6c531a69b · outbound

This paper cites Restler: Stateful rest api fuzzing.

Multi-Agent Penetration Testing AI for the Web Restler: Stateful rest api fuzzing

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.470354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8e085a07-cfd8-46fd-b332-c4af1f775365 · outbound

This paper cites Language models are few-shot learners.

Multi-Agent Penetration Testing AI for the Web Language models are few-shot learners

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.463566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1ff313ad-e584-4161-9c62-6e454758286f · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Multi-Agent Penetration Testing AI for the Web Evaluating Large Language Models Trained on Code

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T14:51:05.041083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a273330b-c7bd-459b-a453-189b36063c76 · outbound

This paper cites Large language models for cyber security: A systematic litera- ture review.

Multi-Agent Penetration Testing AI for the Web Large language models for cyber security: A systematic litera- ture review

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T14:51:05.043901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16e4d25e-ff18-4404-b9e8-587a2f8ffe3a · outbound

This paper cites Refpentester: A knowledge-informed self-reflective pen- etration testing framework based on llms, 2025.

Multi-Agent Penetration Testing AI for the Web Refpentester: A knowledge-informed self-reflective pen- etration testing framework based on llms, 2025

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.457097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d65421fe-b165-46c7-95b7-aab6cd7e2f87 · outbound

This paper cites Pentestgpt: Evaluating and harnessing large language models for automated pene- tration testing.

Multi-Agent Penetration Testing AI for the Web Pentestgpt: Evaluating and harnessing large language models for automated pene- tration testing

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.450468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 949a0f7e-22cb-48af-ab33-6bd47fae2b7f · outbound

This paper cites Damn vulnerable web application (dvwa), 2025.

Multi-Agent Penetration Testing AI for the Web Damn vulnerable web application (dvwa), 2025

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.443398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 16d4589a-0732-4edc-bce1-08cb7b10f1e0 · outbound

This paper cites Ai agents for offsec with zero false positives, 2025.

Multi-Agent Penetration Testing AI for the Web Ai agents for offsec with zero false positives, 2025

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.436522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 34bc223a-3c62-4240-a53c-fb3ad4fd4529 · outbound

This paper cites Our big sleep agent makes a big leap.

Multi-Agent Penetration Testing AI for the Web Our big sleep agent makes a big leap

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.429598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0e4e5dc3-5e8c-4e40-87e2-452e8db24ff6 · outbound

This paper cites From naptime to big sleep: Using large language models to find real-world vulnerabilities.

Multi-Agent Penetration Testing AI for the Web From naptime to big sleep: Using large language models to find real-world vulnerabilities

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.422705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 529159b8-d05e-4ec3-ab1e-8d3d553aba60 · outbound

This paper cites Penheal: A two-stage llm framework for automated pentesting and optimal remediation.

Multi-Agent Penetration Testing AI for the Web Penheal: A two-stage llm framework for automated pentesting and optimal remediation

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.415819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 35304b71-de85-42ee-b3b4-227cdcc6117a · outbound

This paper cites Business logic attacks: Why traditional tools fall short.

Multi-Agent Penetration Testing AI for the Web Business logic attacks: Why traditional tools fall short

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.409051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d342d99d-853a-4da9-a48f-92f35538c708 · outbound

This paper cites Kalopisis.

Multi-Agent Penetration Testing AI for the Web Kalopisis

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.395545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ce4d872d-e725-4ab8-87ce-36dcdb15f606 · outbound

This paper cites Com- parison and evaluation on static application security testing (sast) tools for java.

Multi-Agent Penetration Testing AI for the Web Com- parison and evaluation on static application security testing (sast) tools for java

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.389375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fdc1211e-ec73-4edb-a26f-b0495cf9d91e · outbound

This paper cites Owasp api security top 10: 2023, 2023.

Multi-Agent Penetration Testing AI for the Web Owasp api security top 10: 2023, 2023

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.382571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 23e264f9-036d-4852-b6f4-477cf8db3cab · outbound

This paper cites Owasp juice shop, 2025.

Multi-Agent Penetration Testing AI for the Web Owasp juice shop, 2025

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.374761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 81d4b0cd-8888-43c5-84e9-510be544acc8 · outbound

This paper cites Owasp webgoat, 2025.

Multi-Agent Penetration Testing AI for the Web Owasp webgoat, 2025

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.365782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d1bbb152-f39c-451d-949a-9cda0de7ad17 · outbound

This paper cites Zed attack proxy (zap) documen- tation, 2025.

Multi-Agent Penetration Testing AI for the Web Zed attack proxy (zap) documen- tation, 2025

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.357826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2e955a31-2824-4ca5-9e50-4d8472e837a7 · outbound

This paper cites Asleep at the key- board? assessing the security of github copilot’s code contributions.

Multi-Agent Penetration Testing AI for the Web Asleep at the key- board? assessing the security of github copilot’s code contributions

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.349944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f97bf7bc-5cde-45f1-a03c-e5a53afba866 · outbound

This paper cites Burp suite documentation, 2025.

Multi-Agent Penetration Testing AI for the Web Burp suite documentation, 2025

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.341757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a02067d6-d2af-4c41-b653-8f64b7cacebb · outbound

This paper cites Web application vul- nerabilities in 2020–2021.

Multi-Agent Penetration Testing AI for the Web Web application vul- nerabilities in 2020–2021

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.333510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 76fb4e57-6d76-4eae-8549-07faf90abbc0 · outbound

This paper cites Toolformer: Language models can teach themselves to use tools, 2023.

Multi-Agent Penetration Testing AI for the Web Toolformer: Language models can teach themselves to use tools, 2023

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.320254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f7bf91c2-cf34-4bff-b72d-bd0c1dbc9632 · outbound

This paper cites Xbow validation bench- marks.

Multi-Agent Penetration Testing AI for the Web Xbow validation bench- marks

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.312172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e93085e4-1275-4ed2-9fd8-59bc2c15e704 · outbound

This paper cites Gpt-5 performance analysis for autonomous penetration testing.

Multi-Agent Penetration Testing AI for the Web Gpt-5 performance analysis for autonomous penetration testing

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.303235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1d1c7814-76b9-47b7-bc6c-39d32458d29e · outbound

This paper cites Jim ’enez, Ofir Press, and Karthik Narasimhan.

Multi-Agent Penetration Testing AI for the Web Jim ’enez, Ofir Press, and Karthik Narasimhan

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.294408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ed8ecd49-3a2c-4b35-b995-36494db18004 · outbound

This paper cites React: Synergizing reasoning and acting in language models, 2022.

Multi-Agent Penetration Testing AI for the Web React: Synergizing reasoning and acting in language models, 2022

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:51:05.283246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e592fba6-fcbe-455a-9266-fa19c23723d5 · outbound

This paper cites an unresolved cited work.

Multi-Agent Penetration Testing AI for the Web Unresolved cited work

Reference 2023

Resolution: parse uncertain; raw_fallback, observed 2026-08-05T14:51:05.402194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

Observation 12c96c9e-7d93-497b-ab83-946474811c01 · inbound

Security Considerations for Multi-agent Systems cites this paper.

Security Considerations for Multi-agent Systems Multi-Agent Penetration Testing AI for the Web

Reference 286

Resolution: verified exact; arxiv_id, observed 2026-05-15T14:15:55.761279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 74fb8b87-e886-448f-9553-ff1b42f0ea4b · inbound

Hackers or Hallucinators? A Comprehensive Analysis of LLM-Based Automated Penetration Testing cites this paper.

Hackers or Hallucinators? A Comprehensive Analysis of LLM-Based Automated Penetration Testing Multi-Agent Penetration Testing AI for the Web

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-10T23:45:52.773454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a0c119ed-89fd-422c-bd7a-1741185ca7d4 · inbound

Towards Optimal Agentic Architectures for Offensive Security Tasks cites this paper.

Towards Optimal Agentic Architectures for Offensive Security Tasks Multi-Agent Penetration Testing AI for the Web

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:16:03.104383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a4160773-99d2-48a5-9011-006cbb8e33e3 · inbound

Alignment Contracts for Agentic Security Systems cites this paper.

Alignment Contracts for Agentic Security Systems Multi-Agent Penetration Testing AI for the Web

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:01:04.920507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 29855f87-856b-480f-b81d-fb60b36a5005 · inbound

Patch2Vuln: Agentic Reconstruction of Vulnerabilities from Linux Distribution Binary Patches cites this paper.

Patch2Vuln: Agentic Reconstruction of Vulnerabilities from Linux Distribution Binary Patches Multi-Agent Penetration Testing AI for the Web

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:31:11.634863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fdf16305-f9b5-4f51-9745-548feb41235f · inbound

Agentic Fuzzing: Opportunities and Challenges cites this paper.

Agentic Fuzzing: Opportunities and Challenges Multi-Agent Penetration Testing AI for the Web

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:31:28.018230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b18ff0d4-50f0-43cf-aec1-d8741999df01 · inbound

CrackMeBench: Binary Reverse Engineering for Agents cites this paper.

CrackMeBench: Binary Reverse Engineering for Agents Multi-Agent Penetration Testing AI for the Web

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:56:42.701067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 77564567-eba3-4d72-a5c1-75f9cbf3e9de · inbound

From Controlled to the Wild: Evaluation of Pentesting Agents for the Real-World cites this paper.

From Controlled to the Wild: Evaluation of Pentesting Agents for the Real-World Multi-Agent Penetration Testing AI for the Web

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:16:27.653957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation afb4c3f6-142b-4a65-8ccb-1936b7c08cb0 · inbound

From Controlled to the Wild: Evaluation of Pentesting Agents for the Real-World cites this paper.

From Controlled to the Wild: Evaluation of Pentesting Agents for the Real-World Multi-Agent Penetration Testing AI for the Web

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T14:22:24.089668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63ebf2aa-528e-4a21-9b74-73817073190a · inbound

Benchmarking Mythos-Linked Bug Rediscovery cites this paper.

Benchmarking Mythos-Linked Bug Rediscovery Multi-Agent Penetration Testing AI for the Web

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-19T23:17:57.592662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5a174a8d-4f26-4ce5-bdd1-5a3bc44cdd81 · inbound

Hephaestus: Toward a Cybersecurity AI Scientist cites this paper.

Hephaestus: Toward a Cybersecurity AI Scientist Multi-Agent Penetration Testing AI for the Web

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-06-30T13:54:44.436929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 71464fe0-cc6d-41cf-9872-bf253de0b665 · inbound

A Survey of LLM-Driven Penetration Testing: Taxonomy, Co-Evolution, and Open Challenges cites this paper.

A Survey of LLM-Driven Penetration Testing: Taxonomy, Co-Evolution, and Open Challenges Multi-Agent Penetration Testing AI for the Web

Reference 91

Resolution: unresolved; no resolver link, observed 2026-07-12T09:10:11.585499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7185c408-d0dc-4323-8f43-eddd505481c0 · inbound

Baselines Before Architecture: Evaluating Coding Agents for Autonomous Penetration Testing cites this paper.

Baselines Before Architecture: Evaluating Coding Agents for Autonomous Penetration Testing Multi-Agent Penetration Testing AI for the Web

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T06:53:04.022930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.