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Paper Citation Record · LEDGER

AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 43 inbound Pith citation observations for arXiv:2403.01038.

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

pith.paper-citation-record.v1
2403.01038 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 43 of 43 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:33:52.347166Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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  • malformed identifier0
  • metadata mismatch0

External citation measurements

15
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation cc6b4f74-969b-4580-b11d-3de98475f63f · inbound

Can adversarial attacks by large language models be attributed? cites this paper.

Can adversarial attacks by large language models be attributed? AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 5

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no resolver link, observed 2026-08-12T22:01:50.124339Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T22:01:50.124339Z digest=sha256:33ba6505edadb480144dad7f48c30304c29dc1379f6c0604f55edb8a28d2773c

Observation 51ee9d0d-8481-459f-80b0-9f84a816c713 · inbound

Preventing Jailbreak Prompts as Malicious Tools for Cybercriminals: A Cyber Defense Perspective cites this paper.

Preventing Jailbreak Prompts as Malicious Tools for Cybercriminals: A Cyber Defense Perspective AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 37

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no resolver link, observed 2026-08-12T12:56:34.426125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:56:34.426125Z digest=sha256:3c6556f0587f8f07c5f126d5cbacc4e6f5bec010575cdf12eca4f9a4e5bf41d7

Observation d50b8b98-3b5b-43a5-b9fb-44aad1a44ae7 · inbound

HackSynth: LLM Agent and Evaluation Framework for Autonomous Penetration Testing cites this paper.

HackSynth: LLM Agent and Evaluation Framework for Autonomous Penetration Testing AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 10

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no resolver link, observed 2026-08-12T00:59:59.977032Z

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source=pdf_text observed=2026-08-12T00:59:59.977032Z digest=sha256:fcf165eb62e5ce74aa8eacc56d444069ea94d1571284f7b694336689f176bdcb

Observation 87323e02-2728-4785-995e-eb445eba0896 · inbound

Frontier Models are Capable of In-context Scheming cites this paper.

Frontier Models are Capable of In-context Scheming AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 36

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metadata mismatch
arxiv_id, observed 2026-05-16T14:22:01.685978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-16T14:22:01.616448Z digest=sha256:62650c71b1d2599404e436918050a8e642aa73bb48a3ed883da14e34602df67c

Observation 5235de40-3946-45a5-845f-c4d61e35b5fa · inbound

Attack-in-the-Chain: Bootstrapping Large Language Models for Attacks Against Black-box Neural Ranking Models cites this paper.

Attack-in-the-Chain: Bootstrapping Large Language Models for Attacks Against Black-box Neural Ranking Models AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 50

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no resolver link, observed 2026-08-11T04:32:36.249150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T04:32:36.249150Z digest=sha256:b2ef57a79472b0249fa98013a5d84b864474114d2a799289ffe06f831d6c4c99

Observation 2638c37b-d76e-48f8-bef6-51006ac539dd · inbound

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

VulnBot: Autonomous Penetration Testing for A Multi-Agent Collaborative Framework AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 56

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no resolver link, observed 2026-08-10T16:13:36.778027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:13:36.778027Z digest=sha256:cc8ecc580160e36b68b25eff695e1e7541508d0a19afa306f8b182b0df25b714

Observation f880ee16-86ba-4444-b18b-ee1fcd3e7f2b · 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 AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 65

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no resolver link, observed 2026-08-08T23:10:11.131067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T23:10:11.131067Z digest=sha256:7845bac0736ad0fce7840d05da20793387794f36ee0d7ecba7831465751e8351

Observation 017076ff-676b-4323-a8d8-053f2104c8b0 · inbound

Generative AI for Internet of Things Security: Challenges and Opportunities cites this paper.

Generative AI for Internet of Things Security: Challenges and Opportunities AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 64

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no resolver link, observed 2026-08-07T23:23:49.817436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:23:49.817436Z digest=sha256:540acab980f548b14a6d23582dadf3c3f406e641ab9a1610575ab4c024ef6f68

Observation 18daecac-1de2-4fbc-9441-712e0b75f9da · inbound

Jailbreak Attack Initializations as Extractors of Compliance Directions cites this paper.

Jailbreak Attack Initializations as Extractors of Compliance Directions AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 12

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no resolver link, observed 2026-08-07T20:40:34.256456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:40:34.256456Z digest=sha256:d2cff86ee4a055e749610ebfecc07a3e0df3ec66f6d90fdd6489ae7a2f432dcd

Observation 7dcbffbd-649b-45b9-b129-2fa9f6419b1a · inbound

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

RedTeamLLM: an Agentic AI framework for offensive security AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 34

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no resolver link, observed 2026-08-15T22:33:52.347166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:33:52.347166Z digest=sha256:5a030bd50ad6dcbf2d3d16f28008919ec28fc114d1266b07b80374607b2f74c6

Observation 0e5e921e-7e58-4354-88f6-9a40bc161391 · inbound

RefPentester: A Knowledge-Informed Self-Reflective Penetration Testing Framework Based on Large Language Models cites this paper.

RefPentester: A Knowledge-Informed Self-Reflective Penetration Testing Framework Based on Large Language Models AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 17

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no resolver link, observed 2026-08-15T22:29:21.438186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:29:21.438186Z digest=sha256:0842bd579b89b2c9845ec52bfa864115349ca137b853d9d608f5a892bdc1668b

Observation 7d4296ec-a317-44ef-b96f-0828b1626f14 · inbound

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

AutoPentest: Enhancing Vulnerability Management With Autonomous LLM Agents AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 2

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no resolver link, observed 2026-08-15T21:15:52.697856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:15:52.697856Z digest=sha256:a05df307fc778ff9dff288c7b71628ddf5307bb7800458e99943065c092940b8

Observation e631aa94-917c-4296-9e0b-6ceeacf1866c · inbound

Eradicating the Unseen: Detecting, Exploiting, and Remediating a Path Traversal Vulnerability across GitHub cites this paper.

Eradicating the Unseen: Detecting, Exploiting, and Remediating a Path Traversal Vulnerability across GitHub AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 122

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unresolved
no resolver link, observed 2026-08-07T14:01:10.162800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:01:10.162800Z digest=sha256:a56da883f232874ef80550062d0f2327740a3093fef542acfbda776234f24fbf

Observation 468b374f-bb1a-44c7-9646-eb849beee30f · inbound

PoCGen: Generating Proof-of-Concept Exploits for Vulnerabilities in Npm Packages cites this paper.

PoCGen: Generating Proof-of-Concept Exploits for Vulnerabilities in Npm Packages AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 42

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unresolved
no resolver link, observed 2026-08-07T10:35:15.916106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:35:15.916106Z digest=sha256:0cf8a96ca0df1187e74822a947319928515fee0fb7ee54a636a5b68351917ddf

Observation 1fab0619-8af1-45c7-b65b-13f0e8de93e6 · 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 AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 40

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no resolver link, observed 2026-08-07T05:10:20.153260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:10:20.153260Z digest=sha256:e431f49a11b3d4f79e972b65c27523ac558610be4825a31b8913b2b2ac6f4ff5

Observation 0f9af33f-9d4a-45a5-b33d-a2561c4d9420 · inbound

On the Surprising Efficacy of LLMs for Penetration-Testing cites this paper.

On the Surprising Efficacy of LLMs for Penetration-Testing AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 114

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no resolver link, observed 2026-08-06T21:10:06.716103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:10:06.716103Z digest=sha256:49045aa8be16ef08473f67181e721d64bfdbccf0fae204017441d8e449a4ff88

Observation 04c161eb-c2ee-4ffd-bc05-10629c5da853 · inbound

MGC: A Compiler Framework Exploiting Compositional Blindness in Aligned LLMs for Malware Generation cites this paper.

MGC: A Compiler Framework Exploiting Compositional Blindness in Aligned LLMs for Malware Generation AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-06T20:45:53.362578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:45:53.362578Z digest=sha256:9db8a08d9e41954e0240ec152b40cc35365821f6d24b4bdf43d16a08cf2d2c60

Observation 50cf2013-9dd2-4a06-b1de-2683af952af4 · inbound

From Alerts to Intelligence: A Novel LLM-Aided Framework for Host-based Intrusion Detection cites this paper.

From Alerts to Intelligence: A Novel LLM-Aided Framework for Host-based Intrusion Detection AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 53

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no resolver link, observed 2026-08-06T17:29:58.851040Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:29:58.851040Z digest=sha256:4b1a3caa0d91e148765f07bf00525bf8da00d4869eccc92e4b86a638e6bd5b2e

Observation 3f4ae374-65b9-4ff8-b5cb-5d901f88c6cf · inbound

Vulnerability Mitigation System (VMS): LLM Agent and Evaluation Framework for Autonomous Penetration Testing cites this paper.

Vulnerability Mitigation System (VMS): LLM Agent and Evaluation Framework for Autonomous Penetration Testing AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 2024

Resolution
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no resolver link, observed 2026-08-06T17:48:02.764469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:48:02.764469Z digest=sha256:9ae903e18994be5cefa13e8339d73feecbcb7a121d3dab3e63a81d400950b154

Observation 463f0234-ec18-432e-aacb-87382cb08d9d · inbound

Can We End the Cat-and-Mouse Game? Simulating Self-Evolving Phishing Attacks with LLMs and Genetic Algorithms cites this paper.

Can We End the Cat-and-Mouse Game? Simulating Self-Evolving Phishing Attacks with LLMs and Genetic Algorithms AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 41

Resolution
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no resolver link, observed 2026-08-06T12:43:16.870238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:43:16.870238Z digest=sha256:09a4dd9e5c2579808ad7837664ad0262a84581433b474df18361e49a17808f57

Observation 49b3c049-77b5-4976-9b7e-e6676262caa7 · inbound

xOffense: An Autonomous Multi-Agent Framework for Penetration Testing with Domain-Adapted Large Language Models cites this paper.

xOffense: An Autonomous Multi-Agent Framework for Penetration Testing with Domain-Adapted Large Language Models AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 18

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verified exact
arxiv_id, observed 2026-05-18T16:41:38.200655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-18T16:38:45.171505Z digest=sha256:36d11f2877577cbe9c8a76bc33d96f189de3e35eb26acded4f9698be596e317c

Observation ed7d8b14-5d4f-4cba-b8f4-1cef3c35b333 · inbound

PoCo: Agentic Proof-of-Concept Exploit Generation for Smart Contracts cites this paper.

PoCo: Agentic Proof-of-Concept Exploit Generation for Smart Contracts AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 41

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unresolved
no resolver link, observed 2026-08-04T00:09:35.812498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:09:35.812498Z digest=sha256:8c845b456e1faad35cd3e79dee1e65d7ad377020182b4508a7e4b5c258395eb7

Observation 4549d868-2d27-4c68-971f-025719467361 · inbound

From Rookie to Expert: Manipulating LLMs for Automated Vulnerability Exploitation in Enterprise Software cites this paper.

From Rookie to Expert: Manipulating LLMs for Automated Vulnerability Exploitation in Enterprise Software AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 34

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verified exact
arxiv_id, observed 2026-05-16T20:03:22.185162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-16T20:02:47.746439Z digest=sha256:a6d36af6664ba2384cdbb086bd544caac9a096967b7c147cb5dc17f3f3ab50fb

Observation c3eac0eb-ea06-4350-8902-713011f91ff5 · inbound

Scale-free congestion clusters in large-scale traffic networks: a continuum modeling study cites this paper.

Scale-free congestion clusters in large-scale traffic networks: a continuum modeling study AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 32

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no resolver link, observed 2026-07-13T09:27:26.581889Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T09:27:26.581889Z digest=sha256:3540b9e15787e3d2c772880f91111263d3158fc57807651731b6777ebafcc177

Observation 9acd55f8-b52e-4b29-b3a7-669c997a70c4 · inbound

LanG -- A Governance-Aware Agentic AI Platform for Unified Security Operations cites this paper.

LanG -- A Governance-Aware Agentic AI Platform for Unified Security Operations AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 32

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arxiv_id, observed 2026-05-10T22:25:51.473129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T19:53:05.325203Z digest=sha256:0e92b35eb36a7ddb178ea62fe29324f9ddae7a7a3146c6ce4d96c46e18cc6359

Observation c1b08f4e-3617-4153-988f-ad7686f98fb4 · 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 AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 121

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verified exact
arxiv_id, observed 2026-05-10T23:45:52.848940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T18:52:57.225878Z digest=sha256:1376d3c03daf021d465f5a9e954e457cf55b353cc1232fe04d1ffe2ee13d2d6d

Observation 04884097-703e-4c45-a1c0-0b3a2c7fc433 · inbound

CritBench: A Framework for Evaluating Cybersecurity Capabilities of Large Language Models in IEC 61850 Digital Substation Environments cites this paper.

CritBench: A Framework for Evaluating Cybersecurity Capabilities of Large Language Models in IEC 61850 Digital Substation Environments AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 8

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metadata mismatch
arxiv_id, observed 2026-05-10T19:35:44.730288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T19:32:57.161371Z digest=sha256:0a49665dbf66e7297cb39415fac12c98ae482a8d6d59a61b4ecc887429a13f06

Observation 7ed9ddc6-e060-4b7b-b89e-66984ade10d7 · inbound

Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents cites this paper.

Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 33

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verified exact
arxiv_id, observed 2026-05-12T09:41:26.713634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-07T09:47:52.767727Z digest=sha256:bd861d4450ee08d102d961ac55c2a1ca8b1668959ac3e7507c586fd3a30dfc1a

Observation 8f3b276a-32fe-4882-b8cd-1df86eaa841f · 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 AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 37

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verified exact
arxiv_id, observed 2026-05-11T15:51:44.481352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-09T19:04:48.453055Z digest=sha256:2b00e53716420684579c007c18f745cf5c2ba9bfac0c548a2480e1e6771b54c8

Observation 58ae8c4c-dd81-46d9-b344-efbae741c065 · inbound

APIOT: Autonomous Vulnerability Management Across Bare-Metal Industrial OT Networks cites this paper.

APIOT: Autonomous Vulnerability Management Across Bare-Metal Industrial OT Networks AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 33

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metadata mismatch
arxiv_id, observed 2026-05-09T06:50:41.231591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-08T18:03:04.519514Z digest=sha256:1cc1e4215ee89602df1a0be38d04f181b1a593c376fa910ccc87abec9e53e5dd

Observation 32aa2d9d-b9a1-421b-b01d-11729984c50e · inbound

Pen-Strategist: A Reasoning Framework for Penetration Testing Strategy Formation and Analysis cites this paper.

Pen-Strategist: A Reasoning Framework for Penetration Testing Strategy Formation and Analysis AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 39

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verified exact
arxiv_id, observed 2026-05-11T17:11:18.578675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-08T17:48:09.078064Z digest=sha256:72a85a8ece27d722d003db171ad73e95e8a06e7677d40b32ee9705befec89343

Observation f0b45f90-8f0b-44ef-b59f-a6e3682f9e12 · inbound

Autonomous Adversary: Red-Teaming in the age of LLM cites this paper.

Autonomous Adversary: Red-Teaming in the age of LLM AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 6

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verified exact
arxiv_id, observed 2026-05-11T20:26:10.536094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-08T09:09:58.566171Z digest=sha256:3dcb6ca56ab6954e06bedd74452dc16fa56c49537baa6fd8b3823303fa3bf557

Observation 8d7a2e79-2f86-4371-9057-6c92e40136e0 · inbound

CyBiasBench: Benchmarking Bias in LLM Agents for Cyber-Attack Scenarios cites this paper.

CyBiasBench: Benchmarking Bias in LLM Agents for Cyber-Attack Scenarios AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 29

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verified exact
arxiv_id, observed 2026-05-11T04:10:57.315417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-11T01:54:46.391345Z digest=sha256:ad994ba5e36aa814778ec2a391f310be21a086f1464850eb496711a4adb57a5d

Observation 99c17ba3-2b2d-4af0-9778-302eedb5591e · inbound

PocketAgents: A Manifest-Driven Library of Autonomous Defense Agents cites this paper.

PocketAgents: A Manifest-Driven Library of Autonomous Defense Agents AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-22T09:21:21.554970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-22T09:19:26.725722Z digest=sha256:c08306e612bc02d37c2bffd3f265d8ec0b25c5b68cff1b2152e84b52d1f0ed6c

Observation 6d0ffe7f-5930-431b-987b-a67014490732 · inbound

HIDBench: Benchmarking Large Language Models for Host-Based Intrusion Detection cites this paper.

HIDBench: Benchmarking Large Language Models for Host-Based Intrusion Detection AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-22T08:54:45.838671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-22T08:52:34.079804Z digest=sha256:b7810ade99d745a68bf2150943e05d2bb7f78fa660b57c2a6974f80a8698337f

Observation 649ceabe-fbf8-432c-b56d-8d71e860cdcb · inbound

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

APT-Agent: Automated Penetration Testing using Large Language Models AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-06-30T00:14:03.913371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-30T00:11:02.928108Z digest=sha256:61baca14f9a1c64abe0abffa841dfc22ae252c1f5b07ecf7f79aea56929945fa

Observation 30c5adfa-7b98-483e-927b-f1376003816e · inbound

AI Agents Enable Adaptive Computer Worms cites this paper.

AI Agents Enable Adaptive Computer Worms AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-07-02T04:16:35.431767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-28T09:18:59.008107Z digest=sha256:029bbeee9509ce3a0b12af9906caf4d1d128429fe4f2659b0d9b224a30ffe361

Observation 19c3348d-2e85-43de-a9a6-d7aae3a30573 · inbound

ZERO-APT: A Closed-Loop Adversarial Framework for LLM-Driven Automated Penetration Testing under Intelligent Defense cites this paper.

ZERO-APT: A Closed-Loop Adversarial Framework for LLM-Driven Automated Penetration Testing under Intelligent Defense AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-07-02T13:16:58.772288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-28T01:26:22.434043Z digest=sha256:29c231ed700773ae9a2cd14738e32cff959710dd509eb53a4fbecf8afc64b76e

Observation 9d5e84c7-0edf-4936-be97-062e5be55c01 · inbound

Decoupling Reconnaissance and Exploitation: Measuring the Capability Boundaries of LLM-Based Web Penetration Testing cites this paper.

Decoupling Reconnaissance and Exploitation: Measuring the Capability Boundaries of LLM-Based Web Penetration Testing AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 18

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T19:20:07.182048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-25T21:23:32.255067Z digest=sha256:97c4a5eb5d7a45c22f3d0a057e86e5a067f6333fbe3721b3a5f0ebeb67371dad

Observation 0f64a90a-baee-4c66-b62c-38515c759812 · 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 AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 61

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T09:10:11.585499Z digest=sha256:73db2688fc9ca40a8951c24707f41a63f6fd898f93da29c4e599e04dc62bbdb8

Observation c5949df8-4899-4bd1-8dea-3a2a0fda4024 · inbound

VEXAIoT: Autonomous IoT Vulnerability EXploitation using AI Agents cites this paper.

VEXAIoT: Autonomous IoT Vulnerability EXploitation using AI Agents AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 13

Resolution
unresolved
no resolver link, observed 2026-07-13T01:26:40.958040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T01:26:40.958040Z digest=sha256:7b58aaba7fb754e518ab579a81df1afc1cae7a79973f45615d637fefde968f49

Observation 34d78972-7dcd-4d41-ac9f-40ce0beeb76a · inbound

Tiny Enough to Break In: Agentic Remote Access Trojans Powered by Small Language Models cites this paper.

Tiny Enough to Break In: Agentic Remote Access Trojans Powered by Small Language Models AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-08T04:19:18.900014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:19:18.900014Z digest=sha256:c25ab97a938bab14a719a09eaca5282fa0a206ef6134f8e62148f29c76110ffb

Observation 86f95f50-c2ce-4c65-b13a-506be8528e42 · inbound

Post-Hoc Trajectory-Risk Certification for Modular LLM-Based Security Agents cites this paper.

Post-Hoc Trajectory-Risk Certification for Modular LLM-Based Security Agents AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-15T14:50:05.910726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:50:05.910726Z digest=sha256:94ab9c797594987ded5bb5b9f9fbc51331d148c6f18968bc98a5640866f00c9b