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Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 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 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T04:19:18.900014Z

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

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • 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 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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-16T14:22:01.616448Z digest=sha256:337052c38fb88f0e563b6b1c95e1f5ecc40042dada6eee6dcf5a83cecb5ca54e

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

Resolution
unresolved
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=sha256:52a5991efe1ee49c642500878f414ccaa8f47e9003037eb19e92b86a7545ef33

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

Resolution
unresolved
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=sha256:8be0a927f0df7a72ab4017fb5262e4536c7ef81124700093f12fbff4f6b3d30b

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

Resolution
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=sha256:353c2e6003679b9421d0a1c46071fb795de16ed75f4272bcbff923eb2dfba8dc

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

Resolution
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=sha256:3613819cf9dd646d377dadfb26e4001b6255e6661d2f052c6c87738a5d9ba21d

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

Resolution
unresolved
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:f86a31537d6bd7d8bcf29830e1e1187533dff5a215cbcd205af14d9376d50a2e

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

Resolution
unresolved
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:dbc5706e15ad36081f593317374d6842f6aad6360616087da80addc55069ff52

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:d62ae693d0b67f6177112ff7663f35a52051be5fadfbae015fb7d8fe3dca8bce

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:29:58.851040Z digest=sha256:25534ff0c6f2da670ef1c53dffd91fcc0f42158485f59fd92e17aae30dc678aa

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
unresolved
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:c01c6615263cb21205900e941129776d1b81c3a18a89343341397af0be71c753

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
unresolved
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:a5aaaebf04b36c9ebad985f0c03b5e2a9046f53f708225f115734b8149e98882

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T16:38:45.171505Z digest=sha256:a748555dd7c18dc3332df11aaac44611118b9b48a9900313bb69c5a09248fb5f

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

Resolution
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=sha256:171b91e3b6257a11fc77aad45425de515ec7beff92549b14b2d7c621785a7861

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T20:02:47.746439Z digest=sha256:3a056b69baeec15b9cb09cee4a8a40b70763a803ad6b23949928dcf491e919fb

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T09:27:26.581889Z digest=sha256:3085796a68bac0569d32e6fe6c2153c0f9432cce45ac8a3244e8f02e95f93b73

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

Resolution
verified exact
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T19:53:05.325203Z digest=sha256:228cb3b3f13c36fefb3e8ee6ceb84d10babf8e1b4864d788a251bf9471aaa98c

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T18:52:57.225878Z digest=sha256:16591b54521c729b0ae0c55ddc40a14f2103684c85f42141ed68a7c7419d6a0b

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T19:32:57.161371Z digest=sha256:86123da94af617d2f0fa22411ecb5125b66cfd20c31d4756f9060d19f62a5b8e

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T09:47:52.767727Z digest=sha256:62a067437d085cd444c7964e352c518e65873c43b03422aa95f06728a0ed0c2a

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-09T19:04:48.453055Z digest=sha256:2e762d27b9bcd26b208bff001914447a387779c5e4919ebcd49e9918893a90f9

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T18:03:04.519514Z digest=sha256:a94c88777bf2e3b347d7c145445ab893b09f071af57ddd9fc6e499e686759f06

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T17:48:09.078064Z digest=sha256:6ac3bd6cde7e1b6607040d33554177635ed425c0e1d6a45aba3d77bf7216686e

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T09:09:58.566171Z digest=sha256:6a2593d717c826fd43daa50f166aab68e8c7fd719638faba40586f77fbded500

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T01:54:46.391345Z digest=sha256:1183e84aec9619482b5f5580c30708f92df5c45df1c6d74d4c332274907c73b6

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T09:19:26.725722Z digest=sha256:9d45122db7d047fb0338a6a3a8dfce1f0dba2624d21b2c2c20f0de3ec73985b4

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T08:52:34.079804Z digest=sha256:0e16d0025a255de25fab515195feab9e4906aaea3557ff0ddca6d8547254a763

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T00:11:02.928108Z digest=sha256:0bd845a825328969de154a8d3802e853c7f233320934902d8e155e8abc9fc39b

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-28T09:18:59.008107Z digest=sha256:edc5ef26b5df96f5c9e262d2f39690b5e458dab55acbb09a66b0a13111c47c26

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T01:26:22.434043Z digest=sha256:a7ddc0a36cd305b7d05776267d4b1a252564669bd6f254e6646ff109c60f2d10

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-25T21:23:32.255067Z digest=sha256:aea401706cf8b718ec45e645072ec9019b9c269f284ddf864bcf49f95f1a94b5

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:b9353da953e57cf2dde331ff694e7471f10dbf599f5c0570bf04a4205d3c3d8e

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:ae697f2de175e83970ac1e7108cdcd2182e653af62ae5931c56f5ff4ef19d08b

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
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