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Paper Citation Record · LEDGER

Agents at Risk: How Users Unwittingly Undermine LLM Safety

As of 21 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 2 inbound Pith citation observations for arXiv:2601.10758.

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

pith.paper-citation-record.v1
2601.10758 v3

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T10:45:20.111398Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T15:17:29.479184Z

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

40 of 40 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved40
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation e432f370-e493-4995-89d7-62900a34e679 · outbound

This paper cites Security and Privacy4(4), e159 (2021).

Agents at Risk: How Users Unwittingly Undermine LLM Safety Security and Privacy4(4), e159 (2021)

Reference 1

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source=pdf_text observed=2026-08-03T10:45:15.835365Z digest=sha256:def2b5c8ad5543ab571a5d9877ce73d6b1aba9187a410caa838e95058f521434

Observation 35ecfa6f-2d8d-489f-ac22-73d674ff82be · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Constitutional AI: Harmlessness from AI Feedback

Reference 2

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source=pdf_text observed=2026-08-03T10:45:15.947776Z digest=sha256:cb961d2041299a26ba3d4a41b02fba5d42e15b18913b5b290d57a41e6b7be14e

Observation d11f8b85-1555-4fa0-8c3b-44052593c3c5 · outbound

This paper cites an unresolved cited work.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Unresolved cited work

Reference 3

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:45:16.101607Z digest=sha256:374d4f97bb13de473bc9de95efbe89f3b8fc2343e8ef814def438d582f392621

Observation c9098b25-c8b6-4072-945e-51c76cf128f6 · outbound

This paper cites an unresolved cited work.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Unresolved cited work

Reference 4

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source=pdf_text observed=2026-08-03T10:45:16.246142Z digest=sha256:03e3fa4d18e295120b99e98d497bd86d240475c0788742e74be4a11f12ce9aca

Observation 51fba39d-55d5-47d6-96f6-8093a40e103f · outbound

This paper cites In: 2025 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML).

Agents at Risk: How Users Unwittingly Undermine LLM Safety In: 2025 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)

Reference 5

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source=pdf_text observed=2026-08-03T10:45:16.407118Z digest=sha256:4f8c0647a18942e86d1dfdec0151ac71281a8cc6e24240545561e4d61012262d

Observation b057cb23-5b13-48f2-a92e-f60277d028c0 · outbound

This paper cites Advances in Neural Information Processing Systems37, 26814–26845 (2024).

Agents at Risk: How Users Unwittingly Undermine LLM Safety Advances in Neural Information Processing Systems37, 26814–26845 (2024)

Reference 6

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:45:16.550874Z digest=sha256:ac241dde0a734f90c8dade33c7fd09e320fbee1548c4361340766677777ff6bd

Observation cc184c0e-2ad2-43d0-bde6-2e5ec1866066 · outbound

This paper cites GuideBench: Benchmarking Domain-Oriented Guideline Following for LLM Agents.

Agents at Risk: How Users Unwittingly Undermine LLM Safety GuideBench: Benchmarking Domain-Oriented Guideline Following for LLM Agents

Reference 7

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source=pdf_text observed=2026-08-03T10:45:16.759066Z digest=sha256:a9d2ef754380c7f21c445ccc49971de31964a4a1f0c3eb61a77573e06d23070e

Observation a7b20850-bce2-4faa-bcba-f59675a3a9be · outbound

This paper cites In: 2025 IEEE Symposium on Security and Privacy (SP).

Agents at Risk: How Users Unwittingly Undermine LLM Safety In: 2025 IEEE Symposium on Security and Privacy (SP)

Reference 8

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source=pdf_text observed=2026-08-03T10:45:16.981213Z digest=sha256:c39e95d75704b9e8cfc0593a34e5e452d05f7e61b0a8f098bf7e36937513e8c5

Observation 6ce0185b-63fe-4ab0-9523-f66284bf8351 · outbound

This paper cites International Journal of Human-Computer Studies125, 19–31 (2019).

Agents at Risk: How Users Unwittingly Undermine LLM Safety International Journal of Human-Computer Studies125, 19–31 (2019)

Reference 9

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source=pdf_text observed=2026-08-03T10:45:17.147032Z digest=sha256:d003e3945e2575530391a4d57d479bed26cbff545e2809c71de8aacd3ced142d

Observation 62d9e10d-e54b-47f5-a2cd-8d29de7c77ee · outbound

This paper cites In: Proceedings of the 16th ACM workshop on artificial intelligence and security.

Agents at Risk: How Users Unwittingly Undermine LLM Safety In: Proceedings of the 16th ACM workshop on artificial intelligence and security

Reference 10

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source=pdf_text observed=2026-08-03T10:45:17.356157Z digest=sha256:3657164b7b8821932bd25ebf75561c765ecda13222412e3f032c46d548adfb56

Observation 3f916113-a364-42c3-acfc-359bd3e7e16d · outbound

This paper cites Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast

Reference 11

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source=pdf_text observed=2026-08-03T10:45:17.529100Z digest=sha256:2cf1ab0ca5288eb659439dd1facd8f51b1d74388d61f8aa1f784ba034f59e6f6

Observation 8f4a2ed6-0dcf-41d9-9ffd-5b9939ece92d · outbound

This paper cites Large Language Model based Multi-Agents: A Survey of Progress and Challenges.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Large Language Model based Multi-Agents: A Survey of Progress and Challenges

Reference 12

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source=pdf_text observed=2026-08-03T10:45:17.794251Z digest=sha256:ca57e39442350246f1d7b6c21e7d461286a4f4e39a85777d0efa1030bcc13a5c

Observation 098376b3-d861-4325-b755-dd84821aa5df · outbound

This paper cites In: 33rd USENIX Security Symposium (USENIX Security 24).

Agents at Risk: How Users Unwittingly Undermine LLM Safety In: 33rd USENIX Security Symposium (USENIX Security 24)

Reference 13

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source=pdf_text observed=2026-08-03T10:45:17.903004Z digest=sha256:9d099e558e4b5c695a0b33a9142bd013cbaec8afdb165edd445508c5bdb8eea8

Observation a6761f49-a15c-48c6-a9b5-fa50afade2dc · outbound

This paper cites an unresolved cited work.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Unresolved cited work

Reference 14

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source=pdf_text observed=2026-08-03T10:45:17.956036Z digest=sha256:ce9c4c7084afcd143d83e08157880dfd10adb87c955866b5b4dacdfa489be4e7

Observation 6639fb5e-9397-4c43-9cbe-61c203c042ab · outbound

This paper cites an unresolved cited work.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Unresolved cited work

Reference 15

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source=pdf_text observed=2026-08-03T10:45:18.009539Z digest=sha256:a3ba1f27f89671bc76e347ee87c1715bc58d9aca790d953b7abea5c40a37d20e

Observation 4b0cef02-5cca-4e62-91f4-373d8fbbdd1f · outbound

This paper cites an unresolved cited work.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Unresolved cited work

Reference 16

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source=pdf_text observed=2026-08-03T10:45:18.080741Z digest=sha256:96055a5348b665077df73afdcdf5f3b8eeb9c0b012fb2e0539cc27d70f627780

Observation 98b32e61-f9b1-48ef-955d-d23a9baee00c · outbound

This paper cites Commercial LLM Agents Are Already Vulnerable to Simple Yet Dangerous Attacks.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Commercial LLM Agents Are Already Vulnerable to Simple Yet Dangerous Attacks

Reference 17

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source=pdf_text observed=2026-08-03T10:45:18.132433Z digest=sha256:dd9b577b482744821558737c342dcd5a13bea4cde529f7ad4357204e4c0a015e

Observation 6c061f65-f33d-4717-992c-7a16f85f5a6a · outbound

This paper cites EIA: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage.

Agents at Risk: How Users Unwittingly Undermine LLM Safety EIA: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage

Reference 18

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source=pdf_text observed=2026-08-03T10:45:18.184723Z digest=sha256:350f693f079bae85fef24a666ade5ffcf9e528133425b7fc09a53f32ed0ac965

Observation 058bcab8-04cb-4988-b4dd-dcaf3433752d · outbound

This paper cites preferences.

Agents at Risk: How Users Unwittingly Undermine LLM Safety preferences

Reference 19

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source=pdf_text observed=2026-08-03T10:45:18.264083Z digest=sha256:f3d3bfc285fa0118d1fdf7fe8b9cba1a974a85c9d5259a3bc62e2230933d19e3

Observation 46489787-664c-4291-8fdb-c4afd4efd556 · outbound

This paper cites In: Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems.

Agents at Risk: How Users Unwittingly Undermine LLM Safety In: Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems

Reference 20

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source=pdf_text observed=2026-08-03T10:45:18.320221Z digest=sha256:78a2ac44eb4e20ac9dd7516a3c3312b6247519262ca0c4f5a78b31a38600bfff

Observation 7dc61b19-8dca-453a-862e-d1edeeb5e11c · outbound

This paper cites LASER: LLM Agent with State-Space Exploration for Web Navigation.

Agents at Risk: How Users Unwittingly Undermine LLM Safety LASER: LLM Agent with State-Space Exploration for Web Navigation

Reference 21

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source=pdf_text observed=2026-08-03T10:45:18.400841Z digest=sha256:0c1e19f1f3c4540a403f32b8a62a221cb657297d852b6b9c51343417a4de3622

Observation e9a8b1f2-b393-4d16-b0f8-34ebea8da355 · outbound

This paper cites an unresolved cited work.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Unresolved cited work

Reference 22

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:45:18.511551Z digest=sha256:fb9d50b0a7d19781eb2ef70a92d21c6e1d7eefdf805aa51a41f6514c7185ac26

Observation 361e6f4e-b69f-43c8-97c5-4fe7c2bf7f9e · outbound

This paper cites an unresolved cited work.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Unresolved cited work

Reference 23

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source=pdf_text observed=2026-08-03T10:45:18.587713Z digest=sha256:92cf718542febe5055b154e3c6960d6d22a31975ec9c194de6853e4da8d11458

Observation d3da10df-f534-48ab-a0ad-50638d088d1a · outbound

This paper cites an unresolved cited work.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Unresolved cited work

Reference 24

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source=pdf_text observed=2026-08-03T10:45:18.670577Z digest=sha256:80dc41587d1aeb03b0ba7c1556ea8d7209b3cb22c30423a88a5d01da71e7eb3f

Observation 597deca6-de6f-47f0-830b-c83d15f3a3d3 · outbound

This paper cites an unresolved cited work.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Unresolved cited work

Reference 25

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source=pdf_text observed=2026-08-03T10:45:18.726697Z digest=sha256:d82f8ec854b572a6cac724b6bffdd70834131e129c2f30b5a992f51db32c269c

Observation 2f75cb55-b457-4355-98b0-7f1fa8ccec48 · outbound

This paper cites Prompt Injection Attack to Tool Selection in LLM Agents.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Prompt Injection Attack to Tool Selection in LLM Agents

Reference 26

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source=pdf_text observed=2026-08-03T10:45:18.810302Z digest=sha256:2d017fab1bc2bd0c70b994096ee6009f7bb53f259d601b5633d007cc7b146ae4

Observation 0472dc87-c557-4a6e-9bd9-00eb3079e021 · outbound

This paper cites an unresolved cited work.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Unresolved cited work

Reference 27

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source=pdf_text observed=2026-08-03T10:45:18.863024Z digest=sha256:affe414ae3a83d9f7160dd22e2a775e6bf241fb23d3d3a853774f1512b6033e3

Observation 4f96b43a-9645-4d10-a587-a55a8a268b3b · outbound

This paper cites an unresolved cited work.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Unresolved cited work

Reference 28

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source=pdf_text observed=2026-08-03T10:45:18.916271Z digest=sha256:d93de3f60b2a1c0b49dca1b7e6abc3e061285eb8c06822bee5986a7d62393f30

Observation d814c3da-89c8-4c9b-9f9f-e3d0789e16b1 · outbound

This paper cites an unresolved cited work.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Unresolved cited work

Reference 29

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source=pdf_text observed=2026-08-03T10:45:19.042225Z digest=sha256:086911302b6a1344106f804f3adda72f767e4dea798269e5c389a542fbe809c5

Observation e811ab58-647b-4606-a2f9-ae50bb07fdb3 · outbound

This paper cites an unresolved cited work.

Agents at Risk: How Users Unwittingly Undermine LLM Safety Unresolved cited work

Reference 30

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source=pdf_text observed=2026-08-03T10:45:19.160989Z digest=sha256:27733ee44a738b455d057b099cc242b2413712da8d49b6e1c6181e5cbe22574d

Observation 8401c4a0-3dfa-42a8-a3f8-cf7fb49d5618 · outbound

This paper cites The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions.

Agents at Risk: How Users Unwittingly Undermine LLM Safety The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions

Reference 31

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source=pdf_text observed=2026-08-03T10:45:19.283817Z digest=sha256:2398480f536897a811975d08f2b279cf112594833a8ab1f66b978751d7b35669

Observation cd74da55-4d1c-4d56-b1a3-9cbab589d6fb · outbound

This paper cites arXiv e-prints pp.

Agents at Risk: How Users Unwittingly Undermine LLM Safety arXiv e-prints pp

Reference 32

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source=pdf_text observed=2026-08-03T10:45:19.434987Z digest=sha256:4b9c0e886a44478a1066d0a44e0268adc4c0310a0020ed1bae706596a7acfbde

Observation 8c7bc88a-7877-42e1-aa37-ab93341389eb · outbound

This paper cites arXiv preprint arXiv:2510.19207 (2025).

Agents at Risk: How Users Unwittingly Undermine LLM Safety arXiv preprint arXiv:2510.19207 (2025)

Reference 33

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source=pdf_text observed=2026-08-03T10:45:19.491402Z digest=sha256:d55bf06b56a4b6b2cb56a9c9578476c8676b739228b66024ecea9781df232eaf

Observation 57c7835c-cd00-4931-b37f-e1bede23007f · outbound

This paper cites In: NDSS (2025).

Agents at Risk: How Users Unwittingly Undermine LLM Safety In: NDSS (2025)

Reference 34

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source=pdf_text observed=2026-08-03T10:45:19.562067Z digest=sha256:efd05a75062debb69dd453c5cd6f9ed13bf320f1f3ba39b54e32ca6045b271a2

Observation b149cb52-69c8-4166-9817-38d256c2f88f · outbound

This paper cites AdvAgent: Controllable Blackbox Red-teaming on Web Agents.

Agents at Risk: How Users Unwittingly Undermine LLM Safety AdvAgent: Controllable Blackbox Red-teaming on Web Agents

Reference 35

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source=pdf_text observed=2026-08-03T10:45:19.642964Z digest=sha256:c4f7b25d13e2ab64fd78f42db4807c0637c0ad6d1a21c79d6c4310aaddf21470

Observation bc236d1a-094c-4300-ab84-70e0ffb8542c · outbound

This paper cites BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models.

Agents at Risk: How Users Unwittingly Undermine LLM Safety BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models

Reference 36

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:45:19.715096Z digest=sha256:ce6b5d325b57f6f74dea0246b48fe6d6fcd6ec861fedfe7f0a368485c15672e6

Observation 3e346707-b1c3-48ab-809d-c875c1760100 · outbound

This paper cites In: Companion Proceed- ings of the 32nd ACM International Conference on the Foundations of Software Engineering.

Agents at Risk: How Users Unwittingly Undermine LLM Safety In: Companion Proceed- ings of the 32nd ACM International Conference on the Foundations of Software Engineering

Reference 37

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:45:19.729446Z digest=sha256:5b27aef17a80c8b9d588784c30e1c0c998585743be42fc7066e19770e7effac4

Observation b4b7f5e4-10c7-4788-bf5b-7202886e1e6b · outbound

This paper cites In: Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers).

Agents at Risk: How Users Unwittingly Undermine LLM Safety In: Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:45:19.808251Z digest=sha256:543ef3f1ac811ae6d2b123ed7e95b9057740e80c6463154b324396941818790e

Observation 06375c20-1ee5-4c50-981b-d6730bdeb901 · outbound

This paper cites IEEE Transactions on Dependable and Secure Computing21(6), 5242–5258 (2024).

Agents at Risk: How Users Unwittingly Undermine LLM Safety IEEE Transactions on Dependable and Secure Computing21(6), 5242–5258 (2024)

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-03T10:45:19.950155Z

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source=pdf_text observed=2026-08-03T10:45:19.950155Z digest=sha256:67410451a4816417a5c46d30945e5146a25a1a205297abce48d3a35caf0101f9

Observation d6a0271f-1b66-4b1f-afef-b937aaeeb5af · outbound

This paper cites In: 34th USENIX Security Symposium (USENIX Security 25).

Agents at Risk: How Users Unwittingly Undermine LLM Safety In: 34th USENIX Security Symposium (USENIX Security 25)

Reference 40

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unresolved
no resolver link, observed 2026-08-03T10:45:20.111398Z

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source=pdf_text observed=2026-08-03T10:45:20.111398Z digest=sha256:d6a212c0aedda924e4455842ef3731d06cb28389743b31edbec681a0875a88d3

Pith citing papers

Observation a2dc1e2f-60d3-43db-afbf-9d19f0fdb259 · inbound

Toward Secure LLM Agents: Threat Surfaces, Attacks, Defenses, and Evaluation cites this paper.

Toward Secure LLM Agents: Threat Surfaces, Attacks, Defenses, and Evaluation Agents at Risk: How Users Unwittingly Undermine LLM Safety

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-07-07T03:18:52.400858Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T12:55:22.831264Z digest=sha256:d8c27718484f9db278cf8813a435fec4d9508f69ecbd0d98f966321a91c0d008

Observation 434c2944-cfc8-4d31-83f4-cebc5b6a34f8 · inbound

PlanFlip: Attacking Multi-Agent LLM Systems via Planning-Phase Prompt Injection cites this paper.

PlanFlip: Attacking Multi-Agent LLM Systems via Planning-Phase Prompt Injection Agents at Risk: How Users Unwittingly Undermine LLM Safety

Reference 36

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unresolved
no resolver link, observed 2026-08-02T15:17:29.479184Z

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source=arxiv_source observed=2026-08-02T15:17:29.479184Z digest=sha256:2c1ff86f895abfe3a77f682e8748e7d5617700ca043ba03cb51c3187d71576aa