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Paper Citation Record · LEDGER

OCCULT: Evaluating Large Language Models for Offensive Cyber Operation Capabilities

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2502.15797.

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

pith.paper-citation-record.v1
2502.15797 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:20:02.137246Z

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

2
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 fc1e30ac-fc3e-40c8-9505-4fb926aa06de · inbound

From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review cites this paper.

From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review OCCULT: Evaluating Large Language Models for Offensive Cyber Operation Capabilities

Reference 81

Resolution
verified exact
arxiv_id, observed 2026-05-15T02:57:38.350833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T02:57:37.873567Z digest=sha256:415f6c15e118e2143e8b153436b5af9256b0c32ee692c30334a367ba221a147a

Observation 9fb3a279-6f28-4fa2-8cc4-d2ba5929ed78 · inbound

Mitigating Cyber Risk in the Age of Open-Weight LLMs: Policy Gaps and Technical Realities cites this paper.

Mitigating Cyber Risk in the Age of Open-Weight LLMs: Policy Gaps and Technical Realities OCCULT: Evaluating Large Language Models for Offensive Cyber Operation Capabilities

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T15:20:02.137246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:20:02.137246Z digest=sha256:1b585e4b905d5c25cad5bd7f744f5fdc0e4f7d9974f592fde840a78c693bc4fe

Observation cab247b1-9c5e-4dea-8806-568e2eb59d79 · inbound

From Promise to Peril: Rethinking Cybersecurity Red and Blue Teaming in the Age of LLMs cites this paper.

From Promise to Peril: Rethinking Cybersecurity Red and Blue Teaming in the Age of LLMs OCCULT: Evaluating Large Language Models for Offensive Cyber Operation Capabilities

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T00:35:00.574781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:35:00.574781Z digest=sha256:3cf8ac126851711c881e7b1f717ec6bddae1fdf0949c462be9ce47f4523bdf46

Observation 019c7049-1ca2-459e-ae8b-25db6fda2cb4 · inbound

The 2025 AI Agent Index: Documenting Technical and Safety Features of Deployed Agentic AI Systems cites this paper.

The 2025 AI Agent Index: Documenting Technical and Safety Features of Deployed Agentic AI Systems OCCULT: Evaluating Large Language Models for Offensive Cyber Operation Capabilities

Reference 76

Resolution
verified exact
arxiv_id, observed 2026-05-15T20:46:36.216891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T20:41:49.137745Z digest=sha256:bae08bc1bf33324d578263bbfaa3bc96e02c3b1aa953c968b44acdd8e07d113a

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

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks cites this paper.

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T06:02:32.399075Z digest=sha256:e95c52dde684ef5ccc41f0822b5a68fac7309a7f0d1cc6bc71becc235d1fbf9a

Observation 3a4e9810-bc05-41d1-adb0-18d8e2c0a7b1 · inbound

CyberCertBench: Evaluating LLMs in Cybersecurity Certification Knowledge cites this paper.

CyberCertBench: Evaluating LLMs in Cybersecurity Certification Knowledge OCCULT: Evaluating Large Language Models for Offensive Cyber Operation Capabilities

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:34:47.046898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T00:32:59.120345Z digest=sha256:4a8fdd3a0a057772bdd2757a67452601e6ce6ba80fbf04a1018bfc13ca721a06