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Paper Citation Record · LEDGER

Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilities

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2308.12833.

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

pith.paper-citation-record.v1
2308.12833 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:35:47.840665Z

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

29
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 8f61907b-3f67-4fba-ac27-2bc39558b951 · inbound

StarCoder 2 and The Stack v2: The Next Generation cites this paper.

StarCoder 2 and The Stack v2: The Next Generation Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilities

Reference 236

Resolution
verified exact
arxiv_id, observed 2026-05-12T17:28:22.907337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-12T17:28:22.353355Z digest=sha256:0de356d4d27e3fc830c964be50a8e79a61c22f69b684e0bcb65801e355d3f98a

Observation 78ed1bb7-229a-4867-b1a9-1fe7cace9c4d · inbound

From nuclear safety to LLM security: Applying non-probabilistic risk management strategies to build safe and secure LLM-powered systems cites this paper.

From nuclear safety to LLM security: Applying non-probabilistic risk management strategies to build safe and secure LLM-powered systems Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilities

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T15:35:47.840665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:35:47.840665Z digest=sha256:9697f2630149ff4495090b136264ad031b5a171f3b7dfc7e98f79e5ada550452

Observation df8f36f9-83c9-4aec-85a8-5af897699b7f · inbound

System Prompt Extraction Attacks and Defenses in Large Language Models cites this paper.

System Prompt Extraction Attacks and Defenses in Large Language Models Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilities

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T13:28:17.621783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:28:17.621783Z digest=sha256:5e73a5dd05f8ea9d6b1627a4d26d8836275e8cdfc68faebf6895aebc0cd69eda

Observation 47f679fa-9a3e-40a2-a9b1-e73ef5f4e6c1 · inbound

Evaluating Apple Intelligence's Writing Tools for Privacy Against Large Language Model-Based Inference Attacks: Insights from Early Datasets cites this paper.

Evaluating Apple Intelligence's Writing Tools for Privacy Against Large Language Model-Based Inference Attacks: Insights from Early Datasets Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilities

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T10:56:26.893485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:56:26.893485Z digest=sha256:728db0fb1a67b40b97fe0999c3071ee8005c2b6b49c83dc88e6f8f7c9a49b3d9

Observation 44c79d5e-b731-4f64-99df-022103abe32d · inbound

LoX: Low-Rank Extrapolation Robustifies LLM Safety Against Fine-tuning cites this paper.

LoX: Low-Rank Extrapolation Robustifies LLM Safety Against Fine-tuning Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilities

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T23:59:56.464742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:59:56.464742Z digest=sha256:6fc35d2aa19929178f4474a80168f967feabb7d4d647a0f6910d80b94c55ad5a

Observation 7587ae3b-1737-4ace-ae01-7df9eb24a1e6 · inbound

Identifying Pre-training Data in LLMs: A Neuron Activation-Based Detection Framework cites this paper.

Identifying Pre-training Data in LLMs: A Neuron Activation-Based Detection Framework Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilities

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T15:15:21.317329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:15:21.317329Z digest=sha256:ede68288e22fac9f2f3e25f0820d3b932422fd35ad3230bb58e5e3aa8e240c5a

Observation eb7354c1-fee5-4b56-b0fc-eb38e116ca6c · inbound

LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systems cites this paper.

LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systems Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilities

Reference 215

Resolution
unresolved
no resolver link, observed 2026-08-04T17:46:19.539260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:46:19.539260Z digest=sha256:74f31092ee843300c85b03e0e55b2f60fd8d9e264abfab0d38bb0bc54599c5fe

Observation 0c8e0e9a-082f-4850-bf4e-be2ff16d840c · inbound

Red Teaming Large Reasoning Models cites this paper.

Red Teaming Large Reasoning Models Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilities

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-17T03:31:28.603091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-17T03:29:16.164423Z digest=sha256:32a6154a6bdc0e0f77b419451567b094bc6fd3abae29f7008f33f5f4dd1bee6f

Observation 0c85acd5-7d36-441b-9bcc-b06dd91044bb · inbound

Fully Homomorphic Encryption on Llama 3 model for privacy preserving LLM inference cites this paper.

Fully Homomorphic Encryption on Llama 3 model for privacy preserving LLM inference Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilities

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T08:45:59.815333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T16:30:13.049159Z digest=sha256:a35c7129e974f1ea60e716d72bfbe522ed56f1611f5226a741472fb464eb09c1

Observation 18ed5e37-e215-4bf9-bd73-eeefd5cd638b · inbound

Segment-Level Coherence for Robust Harmful Intent Probing in LLMs cites this paper.

Segment-Level Coherence for Robust Harmful Intent Probing in LLMs Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilities

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T11:10:08.566078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T11:09:20.306577Z digest=sha256:06c65d08ffd180411b97d12a6436ecc1aa5dcc769ffdc54a56d9b8c1a11a768f

Observation 90a5ed87-0e5a-4cea-bc56-375af0d945d5 · inbound

CaliDist: Calibrating Large Language Models via Behavioral Robustness to Distraction cites this paper.

CaliDist: Calibrating Large Language Models via Behavioral Robustness to Distraction Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilities

Reference 87

Resolution
verified exact
arxiv_id, observed 2026-07-02T11:46:55.965303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-28T02:57:54.629402Z digest=sha256:71e09ca185b807fbe54737d9b76eb8ce3291325c11a3aa0eb11f9076a809f011