Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T23:09:36.738179Z
Paper Citation Record · LEDGER
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
As of 20 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 37 inbound Pith citation observations for arXiv:2502.08966.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T00:16:52.643873Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
Reference resolution
58 of 58 outbound references displayed
- verified exact0
- verified fuzzy41
- unresolved17
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
3
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
Observation 0c74a6a3-c513-4a80-9e01-ac72c0ee4467 · outbound
This paper cites https://www.teneo.ai/solutions/ industries/airlines.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage https://www.teneo.ai/solutions/ industries/airlines
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:38.116530Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9a78b874-a00d-4955-b6f6-248a1bf443e2 · outbound
This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:09:36.384228Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation badef446-7079-4309-a97a-f59b8f752143 · outbound
This paper cites Fine-tuned deberta-v3-base for prompt in- jection detection, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Fine-tuned deberta-v3-base for prompt in- jection detection, 2024
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:38.104196Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 07c17d0a-f9e7-4d98-af37-ccd9672a003c · outbound
This paper cites Claude: An ai assistant by anthropic, 2023.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Claude: An ai assistant by anthropic, 2023
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:38.093640Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 78d6ffa3-d31b-43c0-9675-dd4bc0c9c2ca · outbound
This paper cites Prevent factual errors from llm hallucina- tions with mathematically sound automated reasoning checks (preview), December 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Prevent factual errors from llm hallucina- tions with mathematically sound automated reasoning checks (preview), December 2024
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:38.081236Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ec5b9fbf-b8f9-41eb-8291-22c979c5a4ef · outbound
This paper cites Extracting training data from large language models.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Extracting training data from large language models
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:38.068418Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ad7b8941-1eff-4f80-bd19-29e17682ddcb · outbound
This paper cites Clear: Towards contextual llm- empowered privacy policy analysis and risk generation for large language model applications, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Clear: Towards contextual llm- empowered privacy policy analysis and risk generation for large language model applications, 2024
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:38.056295Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 5edde386-6d6a-4419-a75a-284aa8de3b4d · outbound
This paper cites Struq: Defending against prompt injection with structured queries, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Struq: Defending against prompt injection with structured queries, 2024
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:09:36.412536Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7d420f18-e0ac-4e8e-b7a0-6c8ae7460108 · outbound
This paper cites Custom gpts from your content for business, 2025.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Custom gpts from your content for business, 2025
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:38.037288Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2206a5b9-a1f2-4613-a8a6-f6507c9f67ca · outbound
This paper cites AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:09:36.424083Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 55fc7daf-a34b-4c09-b704-b355dd79bda8 · outbound
This paper cites an unresolved cited work.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Unresolved cited work
Reference 11
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T23:09:38.025510Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b7c7ef42-bf4c-44f9-97e5-465c25489d75 · outbound
This paper cites A survey on llm-as-a-judge, 2025.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage A survey on llm-as-a-judge, 2025
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:38.013773Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a5772095-765a-442f-a0a3-c46664c04d03 · outbound
This paper cites Defending against indirect prompt injection attacks with spotlight- ing, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Defending against indirect prompt injection attacks with spotlight- ing, 2024
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:38.002173Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 5e3f1e46-6c5d-419f-b688-a11f600e9ca1 · outbound
This paper cites Long short- term memory.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Long short- term memory
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.990393Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 0aefcb79-6550-4972-8f7a-22d7e1821c09 · outbound
This paper cites Firewallm: A portable data protection and recovery framework for llm services.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Firewallm: A portable data protection and recovery framework for llm services
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.978754Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 70c34846-0835-405e-8f9f-49318c2a01ff · outbound
This paper cites Language models as zero-shot plan- ners: Extracting actionable knowledge for embodied agents, 2022.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Language models as zero-shot plan- ners: Extracting actionable knowledge for embodied agents, 2022
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.957222Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation d088d12e-97e2-4e94-84ee-a5c23731e5fa · outbound
This paper cites Hsu, and Pin-Yu Chen.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Hsu, and Pin-Yu Chen
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.912281Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a93606bd-3a57-4202-8a3c-f9586bcbb707 · outbound
This paper cites Baseline defenses for adversarial attacks against aligned language models, 2023.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Baseline defenses for adversarial attacks against aligned language models, 2023
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:09:36.466778Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a361fb81-b883-4481-841a-5331f4807b00 · outbound
This paper cites Attention is not Explanation.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Attention is not Explanation
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:09:36.480915Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bd732fbc-0ffa-4316-b853-56dc583b0b98 · outbound
This paper cites Iden- tifying and mitigating vulnerabilities in llm-integrated applications, 2023.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Iden- tifying and mitigating vulnerabilities in llm-integrated applications, 2023
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.893626Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation bd7ba25c-f073-490c-9044-a99a3b664077 · outbound
This paper cites Propile: Probing privacy leakage in large language models.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Propile: Probing privacy leakage in large language models
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.881491Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 643956ae-a16b-47d1-8ab3-d9bfa238dba2 · outbound
This paper cites Autodan: Generating stealthy jailbreak prompts on aligned large language models, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Autodan: Generating stealthy jailbreak prompts on aligned large language models, 2024
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:09:36.531254Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 669a9f26-99a7-4ff6-86c2-9d4d2ec6b6bc · outbound
This paper cites Prompt in- jection attack against llm-integrated applications, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Prompt in- jection attack against llm-integrated applications, 2024
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.778707Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 307f4e19-8225-4418-8466-48f7b2321021 · outbound
This paper cites Formalizing and benchmarking prompt injection attacks and defenses.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Formalizing and benchmarking prompt injection attacks and defenses
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.714493Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 53dbaf05-7e9e-403a-9a5b-9ddb620f2a5e · outbound
This paper cites The landscape of emerging ai agent architectures for reasoning, planning, and tool calling: A survey, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage The landscape of emerging ai agent architectures for reasoning, planning, and tool calling: A survey, 2024
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:09:36.554017Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7ea758ee-1485-4c2c-9752-ab094a1a0e50 · outbound
This paper cites Conversational ai in banking: Chatbots, use cases, examples, Dec 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Conversational ai in banking: Chatbots, use cases, examples, Dec 2024
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.653847Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 90f1339d-80ee-43f4-be19-674ef4375be7 · outbound
This paper cites Are sixteen heads really better than one? In H.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Are sixteen heads really better than one? In H
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.603146Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 99fe8290-5dea-4064-9802-2459881d5cf8 · outbound
This paper cites Myers and Barbara Liskov.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Myers and Barbara Liskov
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.591607Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1fc3565a-079d-473f-94fb-632786911c54 · outbound
This paper cites Dynamic taint analysis for automatic detection, analysis, and sig- naturegeneration of exploits on commodity software.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Dynamic taint analysis for automatic detection, analysis, and sig- naturegeneration of exploits on commodity software
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.580275Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 14498474-5b8f-4f3e-914e-47f53dbe1b7f · outbound
This paper cites Introducing gpts, 2023.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Introducing gpts, 2023
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.569845Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 349ac449-19b0-416e-a684-57f55961b870 · outbound
This paper cites Optimizing instructions and demonstrations for multi-stage language model programs, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Optimizing instructions and demonstrations for multi-stage language model programs, 2024
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.559001Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation fde53ec2-b66d-480a-9c86-f088b3d7905c · outbound
This paper cites an unresolved cited work.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Unresolved cited work
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:09:36.577890Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1e7b2b9f-4916-46ff-a82e-6cced1c144b9 · outbound
This paper cites OW ASP Top 10 for LLM Applications, 2025.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage OW ASP Top 10 for LLM Applications, 2025
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.543385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ad33e7eb-0532-46d2-9b55-486fa2d82691 · outbound
This paper cites Jatmo: Prompt injection defense by task-specific finetuning, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Jatmo: Prompt injection defense by task-specific finetuning, 2024
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.452481Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation cf247929-b6ae-451b-926a-4b1c6a06e787 · outbound
This paper cites Fine-tuned large language mod- els (llms): Improved prompt injection attacks detection, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Fine-tuned large language mod- els (llms): Improved prompt injection attacks detection, 2024
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.341044Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 7ad20ce3-e439-4df0-9663-f1e95f898154 · outbound
This paper cites Self-reflection in llm agents: Effects on problem-solving performance, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Self-reflection in llm agents: Effects on problem-solving performance, 2024
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.292535Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c5e5a337-de9d-4be1-a041-f217da88b4f9 · outbound
This paper cites Sabelfeld and A.C.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Sabelfeld and A.C
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.283008Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9a974c7d-2388-4fd4-a7db-e3c039c7a488 · outbound
This paper cites Sandwitch defense.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Sandwitch defense
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.273123Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e20a033a-da37-4265-9839-4901a618ceaf · outbound
This paper cites an unresolved cited work.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Unresolved cited work
Reference 39
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T23:09:37.262823Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1ba44f4c-1179-4f47-a6d7-b5f8b0a633b5 · outbound
This paper cites Permissive information-flow anal- ysis for large language models, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Permissive information-flow anal- ysis for large language models, 2024
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.251821Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b0d308da-186f-43d3-aa39-13593de1f67d · outbound
This paper cites Papillon: Pri- vacy preservation from internet-based and local lan- guage model ensembles, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Papillon: Pri- vacy preservation from internet-based and local lan- guage model ensembles, 2024
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.200667Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation fe75a609-bbf4-4a7e-889e-fa69a37c22e6 · outbound
This paper cites Policygpt: Automated analysis of privacy policies with large language models, 2023.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Policygpt: Automated analysis of privacy policies with large language models, 2023
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.139916Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 407cc61a-465d-4954-8473-8973be29e2d9 · outbound
This paper cites Attention is all you need.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Attention is all you need
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:09:36.638028Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 44232aa4-b234-4e22-9857-e43e5905b7fb · outbound
This paper cites The instruction hier- archy: Training llms to prioritize privileged instructions, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage The instruction hier- archy: Training llms to prioritize privileged instructions, 2024
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:09:36.651864Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 498d6077-4228-4514-9f1d-e2780b85452a · outbound
This paper cites Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:09:36.663757Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c4d3fe6f-4629-4e63-910a-d0c7f71f7b50 · outbound
This paper cites Plan-and- solve prompting: Improving zero-shot chain-of-thought reasoning by large language models, 2023.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Plan-and- solve prompting: Improving zero-shot chain-of-thought reasoning by large language models, 2023
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.097968Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 3e1fe6b5-a453-46eb-9c66-c97ff886c663 · outbound
This paper cites Chain-of-thought prompting elicits rea- soning in large language models, 2023.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Chain-of-thought prompting elicits rea- soning in large language models, 2023
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:09:36.699896Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7c029dc4-d0f3-45ec-93cd-e3b3ab02f075 · outbound
This paper cites Llm powered autonomous agents, 2023.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Llm powered autonomous agents, 2023
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:37.029492Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation de14e05c-11e6-4776-9b47-70b035a4f719 · outbound
This paper cites Attention is not not Explanation.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Attention is not not Explanation
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:09:36.707259Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4abe83cb-364c-4848-9173-5f675d9570c7 · outbound
This paper cites Prsa: Prompt stealing attacks against large language models, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Prsa: Prompt stealing attacks against large language models, 2024
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:36.978796Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 69e4ade0-873f-4430-a46f-b79e7d1f3ea1 · outbound
This paper cites React: Synergizing reasoning and acting in language models, 2023.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage React: Synergizing reasoning and acting in language models, 2023
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:09:36.715196Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0d82a66b-f299-4a2f-a68a-435ad5ef2954 · outbound
This paper cites The shift from mod- els to compound ai systems — bair.berkeley.edu.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage The shift from mod- els to compound ai systems — bair.berkeley.edu
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:36.962194Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9a95bba1-696b-4cfb-b14d-df9b32eee4e6 · outbound
This paper cites an unresolved cited work.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Unresolved cited work
Reference 53
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T23:09:36.952093Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 4c7dcd7b-c2f5-4d4e-b494-f8a4599dcc09 · outbound
This paper cites Injecagent: Benchmarking indirect prompt in- jections in tool-integrated large language model agents, 2024.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Injecagent: Benchmarking indirect prompt in- jections in tool-integrated large language model agents, 2024
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:36.939855Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 510b6c59-eda5-4629-bc8c-5eb636a0c583 · outbound
This paper cites Opt: Open pre-trained transformer language models, 2022.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage Opt: Open pre-trained transformer language models, 2022
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:36.928583Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 10033dc6-dae5-411a-9264-0d8fb8245cfe · outbound
This paper cites H2o: Heavy- hitter oracle for efficient generative inference of large language models.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage H2o: Heavy- hitter oracle for efficient generative inference of large language models
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:36.907437Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 55b202e1-e0c7-4112-96ee-815150e2b17f · outbound
This paper cites A guide to large language model ab- stractions.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage A guide to large language model ab- stractions
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:36.866773Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 4091f65a-3be0-467c-97ff-1dac46a2ef37 · outbound
This paper cites amount":100,date:.
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage amount":100,date:
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:09:36.820109Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Pith citing papers
Observation bb8c9278-c915-4f58-beae-9a1df8b8b52e · inbound
Large Language Model Agent: A Survey on Methodology, Applications and Challenges cites this paper.
Large Language Model Agent: A Survey on Methodology, Applications and Challenges RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 208
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T21:52:10.238901Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 3de2c449-a3f9-4009-97aa-7f6d90a333e3 · inbound
Robustness via Referencing: Defending against Prompt Injection Attacks by Referencing the Executed Instruction cites this paper.
Robustness via Referencing: Defending against Prompt Injection Attacks by Referencing the Executed Instruction RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 47
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T19:11:58.042158Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 4755f0c4-0df9-493b-bc87-041b609ba668 · inbound
LLM Agents Should Employ Security Principles cites this paper.
LLM Agents Should Employ Security Principles RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 78
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:42:17.059726Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d1a3eb34-1cae-49ac-a1e5-9a5996482d17 · inbound
Simple Prompt Injection Attacks Can Leak Personal Data Observed by LLM Agents During Task Execution cites this paper.
Simple Prompt Injection Attacks Can Leak Personal Data Observed by LLM Agents During Task Execution RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:59:27.473122Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation afccdfc2-6a61-4588-ae1d-7caaa7ddc689 · inbound
Quantifying Conversation Drift in MCP via Latent Polytope cites this paper.
Quantifying Conversation Drift in MCP via Latent Polytope RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:51:28.187021Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5d2d8ec6-39d3-4c27-b4f2-b2f48f2fbdce · inbound
CaMeLs Can Use Computers Too: System-level Security for Computer Use Agents cites this paper.
CaMeLs Can Use Computers Too: System-level Security for Computer Use Agents RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T10:32:33.909110Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cfe75a82-e001-4659-9aef-3bed1f25ec63 · inbound
AgentDyn: Are Your Agent Security Defenses Deployable in Real-World Dynamic Environments? cites this paper.
AgentDyn: Are Your Agent Security Defenses Deployable in Real-World Dynamic Environments? RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 10
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-16T08:17:36.456679Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e824a791-b449-450c-8ec3-5ebba32de1ab · inbound
Causality Laundering: Denial-Feedback Leakage in Tool-Calling LLM Agents cites this paper.
Causality Laundering: Denial-Feedback Leakage in Tool-Calling LLM Agents RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 32
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T17:23:02.729426Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 889266f4-42fe-4caf-8724-a49908aae6ba · inbound
Don't Make Models Guess Security and Safety: Symbolic Guardrails for Domain-Specific AI Agents cites this paper.
Don't Make Models Guess Security and Safety: Symbolic Guardrails for Domain-Specific AI Agents RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 78
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T10:24:22.255308Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f72f3970-041a-47bd-a996-ddeec1a92ee4 · inbound
An AI Agent Execution Environment to Safeguard User Data cites this paper.
An AI Agent Execution Environment to Safeguard User Data RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 84
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T13:11:05.836253Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ed8708f0-3a77-45fe-b2fa-0a8fa60a5e7d · inbound
Ghost in the Agent: Redefining Information Flow Tracking for LLM Agents cites this paper.
Ghost in the Agent: Redefining Information Flow Tracking for LLM Agents RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 42
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-08T22:39:20.560351Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2125e95c-ae4c-46ba-bd5a-5b6900e9d503 · inbound
Semia: Auditing Agent Skills via Constraint-Guided Representation Synthesis cites this paper.
Semia: Auditing Agent Skills via Constraint-Guided Representation Synthesis RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 51
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T15:26:11.075385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 89038650-9305-4b6f-8841-ff7a5ebcdb6b · inbound
PIIGuard: Mitigating PII Harvesting under Adversarial Sanitization cites this paper.
PIIGuard: Mitigating PII Harvesting under Adversarial Sanitization RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-08T17:53:53.279055Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 4d8997e7-20e6-4b4a-869a-5cc7a0faa4d7 · inbound
When Agents Handle Secrets: A Survey of Confidential Computing for Agentic AI cites this paper.
When Agents Handle Secrets: A Survey of Confidential Computing for Agentic AI RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 56
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T10:46:31.618660Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c983bbf0-71f7-4455-8318-13798820fb44 · inbound
When Agents Handle Secrets: A Survey of Confidential Computing for Agentic AI cites this paper.
When Agents Handle Secrets: A Survey of Confidential Computing for Agentic AI RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 56
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-09T06:55:44.561705Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 15b8949e-8444-43db-83b9-e9b6657c0e10 · inbound
Reframing LLM Agent Security as an Agent-Human Interaction Problem cites this paper.
Reframing LLM Agent Security as an Agent-Human Interaction Problem RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 66
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T13:54:43.881131Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f2968074-18cf-4836-b8ab-a1132d6dcb92 · inbound
Aligning Provenance with Authorization: A Dual-Graph Defense for LLM Agents cites this paper.
Aligning Provenance with Authorization: A Dual-Graph Defense for LLM Agents RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T18:03:48.509291Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f4ee1d49-2a26-4813-891a-45aaada12f46 · inbound
AIRGuard: Guarding Agent Actions with Runtime Authority Control cites this paper.
AIRGuard: Guarding Agent Actions with Runtime Authority Control RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 28
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-29T12:53:27.150378Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 3ff414f6-8af9-4fda-902b-c7e1d2c13121 · inbound
Relevance as a Vulnerability: How Web Retrieval Degrades Safety Alignment in LLM Agents cites this paper.
Relevance as a Vulnerability: How Web Retrieval Degrades Safety Alignment in LLM Agents RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T08:23:14.888499Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation d67d0e00-d1b5-41ec-b992-02a653b76759 · inbound
Ghost Tool Calls: Issue-Time Privacy for Speculative Agent Tools cites this paper.
Ghost Tool Calls: Issue-Time Privacy for Speculative Agent Tools RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 9
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-28T14:42:18.230738Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8ca0a012-5ed1-4940-8e35-707412bf006a · inbound
SecureClaw: Clawing Back Control of LLM Agents cites this paper.
SecureClaw: Clawing Back Control of LLM Agents RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T01:37:30.746835Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 23bc665b-1513-4c67-8076-ab33edaecd18 · inbound
Assessing Automated Prompt Injection Attacks in Agentic Environments cites this paper.
Assessing Automated Prompt Injection Attacks in Agentic Environments RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 58
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T06:17:41.876038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 5e84c857-4e4b-4856-80bc-499d91357c64 · inbound
Toward Secure LLM Agents: Threat Surfaces, Attacks, Defenses, and Evaluation cites this paper.
Toward Secure LLM Agents: Threat Surfaces, Attacks, Defenses, and Evaluation RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 255
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-27T13:20:56.872177Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 4ed535c9-1144-424a-9307-3c20744aa829 · inbound
OCELOT: Inference-Leakage Budgets for Privacy-Preserving LLM Agents cites this paper.
OCELOT: Inference-Leakage Budgets for Privacy-Preserving LLM Agents RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T11:58:06.930341Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8d49e100-8e40-44b2-a0ec-152792d33054 · inbound
GIF: Locally Sound Geometric Information Flow Control for LLMs cites this paper.
GIF: Locally Sound Geometric Information Flow Control for LLMs RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T10:49:46.735990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 61facb60-add7-4507-8e20-d8a5151dbc76 · inbound
Adaptive Evaluation of Out-of-Band Defenses Against Prompt Injection in LLM Agents cites this paper.
Adaptive Evaluation of Out-of-Band Defenses Against Prompt Injection in LLM Agents RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T13:39:51.335715Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 68134e5b-cb3b-4981-80b9-fb64ac43457c · inbound
Agents That Know Too Much: A Data-Centric Survey of Privacy in LLM Agents cites this paper.
Agents That Know Too Much: A Data-Centric Survey of Privacy in LLM Agents RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 133
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T14:09:53.128363Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a647f80e-0495-4430-93fa-92f54cb5c1d6 · inbound
ToolPrivacyBench: Benchmarking Purpose-Bound Privacy in Tool-Using LLM Agents cites this paper.
ToolPrivacyBench: Benchmarking Purpose-Bound Privacy in Tool-Using LLM Agents RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T17:25:51.826373Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 38ed1a0b-f2b5-48e9-b0d9-2aa1dbaad83c · inbound
Cloak and Detonate: Scanner Evasion and Dynamic Detection of Agent Skill Malware cites this paper.
Cloak and Detonate: Scanner Evasion and Dynamic Detection of Agent Skill Malware RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 47
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T10:37:56.234656Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 92320250-441e-4518-9a1b-5240ada67f43 · inbound
Cloak and Detonate: Scanner Evasion and Dynamic Detection of Agent Skill Malware cites this paper.
Cloak and Detonate: Scanner Evasion and Dynamic Detection of Agent Skill Malware RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T08:09:57.596812Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6fc5b00d-74af-4ecc-8d8f-5b149157070e · inbound
DualView: Preventing Indirect Prompt Injection in Personal AI Agents cites this paper.
DualView: Preventing Indirect Prompt Injection in Personal AI Agents RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T23:43:28.649948Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0f24a9c5-0e3d-4916-b197-713dd251ebfd · inbound
Prismata: Confining Cross-Site Prompt Injection in Web Agents cites this paper.
Prismata: Confining Cross-Site Prompt Injection in Web Agents RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 102
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-10T12:27:04.073825Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 086d7580-83f5-4d3e-a7f6-81fb0196c399 · inbound
From Neural Intent to Cryptographic Authorization: Securing AI-Driven Enterprise Workflows cites this paper.
From Neural Intent to Cryptographic Authorization: Securing AI-Driven Enterprise Workflows RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T22:55:50.423697Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8c60331b-a861-4004-b04d-39c7c8aa3430 · inbound
Data Leakage Prevention in Agentic Applications via Preemptive Hardening cites this paper.
Data Leakage Prevention in Agentic Applications via Preemptive Hardening RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T14:11:22.426651Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9261d1b0-3159-4ef0-a2b5-92b5e3377723 · inbound
Beyond Component Testing: Validating Agentic AI Systems cites this paper.
Beyond Component Testing: Validating Agentic AI Systems RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T07:41:24.234199Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 58746dc0-eb42-4bcf-b78f-43d7b37caef6 · inbound
On Understanding, Identifying, and Mitigating Vulnerabilities in Agentic Large Language Models cites this paper.
On Understanding, Identifying, and Mitigating Vulnerabilities in Agentic Large Language Models RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 163
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:21:42.763513Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8e10ec44-80f8-4ff2-94f6-1c098895bc68 · inbound
Rethinking Agent Security as a Networking Problem cites this paper.
Rethinking Agent Security as a Networking Problem RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
Reference 74
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:16:52.643873Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.