Paper Citation Record · LEDGER

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks

As of 14 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2604.17159.

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

pith.paper-citation-record.v1
2604.17159 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-10T06:02:32.399075Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

12 of 12 outbound references displayed

verified exact5
verified fuzzy3
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8927117d-cc4c-4fb4-88ca-d6e6cba95f30 · outbound

This paper cites Generative AI in cybersecurity: A com- prehensive review of LLM applications and vulnerabilities.

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks Generative AI in cybersecurity: A com- prehensive review of LLM applications and vulnerabilities

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T18:05:27.878652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 479d3493-16c0-438e-8fbb-2b1b43ddccdd · outbound

This paper cites LLM Agents can Autonomously Hack Websites.

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks LLM Agents can Autonomously Hack Websites

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:06:19.079644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 77506b14-1d7b-41c9-ab74-0a552213cd1e · outbound

This paper cites PentestGPT: Evaluating and harnessing large language models for automated penetration testing.

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks PentestGPT: Evaluating and harnessing large language models for automated penetration testing

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T18:05:27.880650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f1e731c9-9870-46d5-a69c-b3b9c6ce0b86 · outbound

This paper cites OCCULT: Evaluating Large Language Models for Offensive Cyber Operation Capabilities.

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks OCCULT: Evaluating Large Language Models for Offensive Cyber Operation Capabilities

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:06:19.095389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 465b323a-806e-4e04-8059-d42cec2a3e14 · outbound

This paper cites NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security.

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:06:19.098028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7613c64e-2c0d-4576-8aea-5fcbcae9637c · outbound

This paper cites EnIGMA: Interactive Tools Substantially Assist LM Agents in Finding Security Vulnerabilities.

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks EnIGMA: Interactive Tools Substantially Assist LM Agents in Finding Security Vulnerabilities

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:06:19.085010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ec0a22bb-13f5-4249-81da-1e0d1341dad6 · outbound

This paper cites D-CIPHER: Dynamic Collaborative Intelligent Multi-Agent System with Planner and Heterogeneous Executors for Offensive Security.

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks D-CIPHER: Dynamic Collaborative Intelligent Multi-Agent System with Planner and Heterogeneous Executors for Offensive Security

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:06:19.082441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a1693e07-42de-44bf-889c-eaf38d71ce4b · outbound

This paper cites CRAKEN: Cybersecurity LLM Agent with Knowledge-Based Execution.

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks CRAKEN: Cybersecurity LLM Agent with Knowledge-Based Execution

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:06:19.089932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4bb081e1-779b-4042-a3d7-129c3a192a6f · outbound

This paper cites An Empirical Evaluation of LLMs for Solving Offensive Security Challenges.

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks An Empirical Evaluation of LLMs for Solving Offensive Security Challenges

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:06:19.100715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 670e3a77-f49b-4e6a-b904-6acda6aaf242 · outbound

This paper cites Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Models.

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Models

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:06:19.087529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f925fd48-69c5-4323-a651-8aae7f8b7b15 · outbound

This paper cites CTFusion: A CTF-based benchmark for LLM agent evaluation.

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks CTFusion: A CTF-based benchmark for LLM agent evaluation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T18:05:27.883199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4342aafa-f030-4bd0-9318-cb02d203a8f3 · outbound

This paper cites Zhang, Joey Ji, Celeste Menders, Riya Dulepet, T.

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks Zhang, Joey Ji, Celeste Menders, Riya Dulepet, T

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:06:19.092403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

No inbound Pith citation observations are available.