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Paper Citation Record · LEDGER

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation

As of 10 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2608.02518.

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

pith.paper-citation-record.v1
2608.02518 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T05:44:24.854509Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

41 of 41 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved40
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c6f47370-662a-4d34-81a1-5149bd762a99 · outbound

This paper cites Evaluating prompt injection safety in large language models using the promptbench dataset.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Evaluating prompt injection safety in large language models using the promptbench dataset

Reference 1

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source=pdf_text observed=2026-08-04T05:44:22.170465Z digest=sha256:418eaa14300f216ec6027566373180fa9d41b420406d2545ea8d58a7a2398b68

Observation fb46f4d2-7cbb-4a41-ab8f-5d17ec9f892c · outbound

This paper cites LLM Defenses Are Not Robust to Multi-Turn Human Jailbreaks Yet.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation LLM Defenses Are Not Robust to Multi-Turn Human Jailbreaks Yet

Reference 2

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source=pdf_text observed=2026-08-04T05:44:22.263222Z digest=sha256:91bb11794a5b84e1db1d86390271029fd8f1e3aa10fffbb0a3e99ef43a4cfc50

Observation 96b3ca58-3642-4c51-a3ba-a1816cf1c744 · outbound

This paper cites Multibreak: A scalable and diverse multi-turn jailbreak benchmark for stress-testing LLM safety.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Multibreak: A scalable and diverse multi-turn jailbreak benchmark for stress-testing LLM safety

Reference 3

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source=pdf_text observed=2026-08-04T05:44:22.302044Z digest=sha256:ae96f42883ce2d7fcce2c96e5ee5b4deea27cba90f4d5ae7143737d2f189bf10

Observation f285f93e-d0ca-4895-8c72-08ec0bc3b683 · outbound

This paper cites Safe in isolation, dangerous together: Agent-driven multi-turn decomposition jailbreaks on llms.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Safe in isolation, dangerous together: Agent-driven multi-turn decomposition jailbreaks on llms

Reference 4

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source=pdf_text observed=2026-08-04T05:44:22.336876Z digest=sha256:7e366d7ded1bcb249f10c56d677f45525ace462d3cfaf98f25c8752629dcded6

Observation d5549ca9-54e3-4376-af67-28df942e37cd · outbound

This paper cites Unsafer in Many Turns: Benchmarking and Defending Multi-Turn Safety Risks in Tool-Using Agents.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Unsafer in Many Turns: Benchmarking and Defending Multi-Turn Safety Risks in Tool-Using Agents

Reference 5

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source=pdf_text observed=2026-08-04T05:44:22.374592Z digest=sha256:f0fc8e7acd4869b6800c9f2d1c1cc72ba81826c75dc690d8d445b0637dd79d80

Observation 37bc05b3-6e15-4b9c-86f2-f5450bd67a2e · outbound

This paper cites Deepcontext: Stateful real-time detection of multi-turn adversarial intent drift in llms.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Deepcontext: Stateful real-time detection of multi-turn adversarial intent drift in llms

Reference 6

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source=pdf_text observed=2026-08-04T05:44:22.439364Z digest=sha256:3bd76fdd69f7666427f65d83bcaa91ff9d325bd93c59d8db3e2faefe6273ce41

Observation bd69103a-2ece-46e5-b66c-55b505d2b78e · outbound

This paper cites Constitutional Classifiers++: Efficient Production-Grade Defenses against Universal Jailbreaks.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Constitutional Classifiers++: Efficient Production-Grade Defenses against Universal Jailbreaks

Reference 7

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source=pdf_text observed=2026-08-04T05:44:22.473357Z digest=sha256:6e8001f8a2f9e74a6b9a19bec458b377a2da1f16d1d62f9bbb775d4badcbcd15

Observation 54aa412e-4531-4c09-ba9e-81d97188a16d · outbound

This paper cites Automating Deception: Scalable Multi-Turn LLM Jail- breaks.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Automating Deception: Scalable Multi-Turn LLM Jail- breaks

Reference 8

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source=pdf_text observed=2026-08-04T05:44:22.508380Z digest=sha256:214cc33d1ea030a305b57c0cf675897e65edf463a83a4e76013e337406a5ef43

Observation 3ed7e0a5-b13c-4751-bc68-5f53ba788791 · outbound

This paper cites Cross-Session Threats in AI Agents: Benchmark, Evaluation, and Algorithms.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Cross-Session Threats in AI Agents: Benchmark, Evaluation, and Algorithms

Reference 9

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source=pdf_text observed=2026-08-04T05:44:22.537750Z digest=sha256:7d8aee5162881e4776435e16f275ff73ffc9f66b03722c141fd99bda1dc2ea99

Observation d38f8fd3-a982-4b07-85fd-76e8fcb6e84c · outbound

This paper cites MOSAIC-Bench: Measuring Compositional Vulnerability Induction in Coding Agents.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation MOSAIC-Bench: Measuring Compositional Vulnerability Induction in Coding Agents

Reference 10

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source=pdf_text observed=2026-08-04T05:44:22.582902Z digest=sha256:933bbb3d41a71d8ffd18418e3d2338ced8d884f83dc86af7ed9b15545c71b7cb

Observation 46371704-e4e9-4200-810f-418e988a8f1e · outbound

This paper cites Kairos: Practical intrusion detection and investigation using whole-system prove- nance.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Kairos: Practical intrusion detection and investigation using whole-system prove- nance

Reference 11

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source=pdf_text observed=2026-08-04T05:44:22.629437Z digest=sha256:9ef06f03ccbf412aa4ee705166c77e7c4984fc9e184ee8f43ca3dd7cc33dfc74

Observation ad0972d8-6086-410f-b9eb-ac54880b8290 · outbound

This paper cites Detection and mitigation of slow DoS attacks using machine learning.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Detection and mitigation of slow DoS attacks using machine learning

Reference 12

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source=pdf_text observed=2026-08-04T05:44:22.713260Z digest=sha256:3da8abe017c37ab24f4288d96440f78ed35ce9facc0f3c0f8faf4fbfa405a739

Observation 658a82a4-c714-4e94-92ce-845d2b2532d2 · outbound

This paper cites an unresolved cited work.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Unresolved cited work

Reference 13

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source=pdf_text observed=2026-08-04T05:44:22.750171Z digest=sha256:fe91d201082ef6feebd9597c20bbfb149e99c05fb4243ada78dc35ea0d48bf50

Observation 68e49eda-0cbc-4d03-9204-77c61dc16605 · outbound

This paper cites LLM Censorship: A Machine Learning Challenge or a Computer Security Problem?.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation LLM Censorship: A Machine Learning Challenge or a Computer Security Problem?

Reference 16

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Observation 7d14b3be-1e2a-4c68-b384-a10a855a536d · outbound

This paper cites Breach By A Thousand Leaks: Unsafe Information Leakage in’Safe’AI Re- sponses.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Breach By A Thousand Leaks: Unsafe Information Leakage in’Safe’AI Re- sponses

Reference 17

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source=pdf_text observed=2026-08-04T05:44:22.927979Z digest=sha256:5e9d3524fb540024d11d39079a125d9b32a1fd5e243d748e6378cf10156fc508

Observation a876a816-6eb7-42ea-b214-d648e056211a · outbound

This paper cites Wildchat: 1m chatgpt interaction logs in the wild.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Wildchat: 1m chatgpt interaction logs in the wild

Reference 18

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source=pdf_text observed=2026-08-04T05:44:23.023247Z digest=sha256:c1d81f4929a60eb0dc1ed21740eacaf3542f27b66f84fd8516e6de3b868c099d

Observation 46ab60fe-d77c-40f1-a904-f984e1752353 · outbound

This paper cites A globally-accessible knowledge base of adversary tactics and techniques based on real-world observations.url:https : / / attack.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation A globally-accessible knowledge base of adversary tactics and techniques based on real-world observations.url:https : / / attack

Reference 19

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source=pdf_text observed=2026-08-04T05:44:23.079979Z digest=sha256:a851616b873d5913f9093a19a40d40ce79ae2cdcbd1a1d83384b613631c9db35

Observation b1fbb827-0c10-4aa9-b3b2-efe0062c5b8b · outbound

This paper cites Dual-usecapabilitiesofconcernofbiologicalAImodels.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Dual-usecapabilitiesofconcernofbiologicalAImodels

Reference 20

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Observation ca514473-6e89-4592-8d77-6301139aae37 · outbound

This paper cites It Is the Journey, Not the Destination: Moving From End Points to Trajectories When Assessing Chatbot Mental Health Safety.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation It Is the Journey, Not the Destination: Moving From End Points to Trajectories When Assessing Chatbot Mental Health Safety

Reference 21

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Observation 6937a851-8de5-4d43-9a58-145197d2092f · outbound

This paper cites The agent searches for a target individual and infers their email address based on their organizational affiliation.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation The agent searches for a target individual and infers their email address based on their organizational affiliation

Reference 22

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Observation 300d2bbf-7d16-4253-9ee1-f70806466500 · outbound

This paper cites background-color: yellow; color: black; text-align: center; padding: 10px; font-weight: bold.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation background-color: yellow; color: black; text-align: center; padding: 10px; font-weight: bold

Reference 23

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Observation 6d3dd604-f864-45c2-bf1b-5345bdaa47be · outbound

This paper cites The agent drafts a password-reset email addressed to the target email discovered in step 1.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation The agent drafts a password-reset email addressed to the target email discovered in step 1

Reference 24

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Observation 35e946f4-49b9-4bbb-bfe6-fb56e8e31fd4 · outbound

This paper cites The agent is tasked with reviewing the landing page and removing any demo or placeholder content (specifically, the banner injected in step 2).

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation The agent is tasked with reviewing the landing page and removing any demo or placeholder content (specifically, the banner injected in step 2)

Reference 25

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Observation cc8b69d1-fc42-4420-b708-9dea735eac7f · outbound

This paper cites The agent inserts a hyperlink to the phishing page from step 4 into the email drafted in step 3.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation The agent inserts a hyperlink to the phishing page from step 4 into the email drafted in step 3

Reference 26

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Observation c7798f0a-58dd-4d3a-9ac0-ec6f65e2f3f6 · outbound

This paper cites an unresolved cited work.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Unresolved cited work

Reference 27

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Observation 4a5c4dbe-3275-4de6-9585-3761c32d68c8 · outbound

This paper cites an unresolved cited work.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Unresolved cited work

Reference 28

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Observation 9acd0158-84ec-483f-ae95-a912638f6f05 · outbound

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Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Unresolved cited work

Reference 29

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Observation 5ae6ad9a-ed95-4164-b651-2b8a3224f64e · outbound

This paper cites an unresolved cited work.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Unresolved cited work

Reference 30

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Observation 5ccdd42c-216c-43ce-bb95-550f0b03beb2 · outbound

This paper cites demo" or.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation demo" or

Reference 31

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Observation 62e660bb-2765-474d-b442-a165d01747a6 · outbound

This paper cites an unresolved cited work.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Unresolved cited work

Reference 32

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source=pdf_text observed=2026-08-04T05:44:24.080425Z digest=sha256:b014aae4d2b8af051d6d44c577b7c97d32d363a606896d58972451fab13d5c2c

Observation 1574a785-7093-4c13-aaba-6066728bc985 · outbound

This paper cites an unresolved cited work.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Unresolved cited work

Reference 33

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Observation cf0fe7c4-55e9-4681-a455-e87def5792f1 · outbound

This paper cites demo" or.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation demo" or

Reference 34

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Observation e9f76326-d7c8-4c7c-8d01-a909e5909565 · outbound

This paper cites common, widely available fuel.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation common, widely available fuel

Reference 35

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Observation 4d3d3af6-7172-4d77-ae69-76c62a4fa35b · outbound

This paper cites breakaway prop for a film.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation breakaway prop for a film

Reference 36

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Observation 5a085344-1fdd-4e75-9263-fa3f197516e5 · outbound

This paper cites oil lamp restoration project.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation oil lamp restoration project

Reference 37

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source=pdf_text observed=2026-08-04T05:44:24.412755Z digest=sha256:0f7fb533c2e445733093efbcc2c84e090d68dfff0cbf8b54740f9c686acb9709

Observation 5a9c64cd-86b0-444a-898d-2ac27c7e337c · outbound

This paper cites an unresolved cited work.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Unresolved cited work

Reference 38

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source=pdf_text observed=2026-08-04T05:44:24.505159Z digest=sha256:5166a6c719d737a81b6ac5ed82b34b7fc0e884b70439147b3debb742c5a7f5e3

Observation 77060cd5-dfaf-4a2c-b3e9-3ca961d5bd3b · outbound

This paper cites For gas, the ratio is approximately 14:1, for ethanol it is approximately 9:1, for propane it is approximately 16:1.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation For gas, the ratio is approximately 14:1, for ethanol it is approximately 9:1, for propane it is approximately 16:1

Reference 39

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:44:24.576986Z digest=sha256:4b40ca0b3b8d17c300251c2e9d046ef9a2d898ced22436ffb7a5006d5b2da941

Observation 119ed9c1-a03e-4d07-a836-a9de037589e6 · outbound

This paper cites an unresolved cited work.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Unresolved cited work

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-04T05:44:24.644460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:44:24.644460Z digest=sha256:b721390487424778b5dfce7770bf7b77fb02c151aefe5256e0a2ad79a49cccb9

Observation 59e228ee-a629-482e-954a-d5ad319535f2 · outbound

This paper cites an unresolved cited work.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Unresolved cited work

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-04T05:44:24.707786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:44:24.707786Z digest=sha256:0030d04a40d5a03afb26d456622251d522b5e31873724bdd0be18e31d75cbb89

Observation da663dc4-3c40-4aca-b9c0-ca87f20c3256 · outbound

This paper cites an unresolved cited work.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Unresolved cited work

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-04T05:44:24.765803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:44:24.765803Z digest=sha256:5a4c3128e00cf75150e4e101b13d0890ca59eb8a7fafffc272e283b9129841d0

Observation 528c3b4f-1e28-42d3-9e19-34398cf3bae0 · outbound

This paper cites an unresolved cited work.

Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation Unresolved cited work

Reference 43

Resolution
malformed identifier
no resolver link, observed 2026-08-04T05:44:24.854509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:44:24.854509Z digest=sha256:09d360b380e29a755b4b2dba6b37e8de366cb524d4f56bf237c766f6a89510b1

Pith citing papers

No inbound Pith citation observations are available.