Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T14:19:09.555981Z
Paper Citation Record · LEDGER
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark
As of 17 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2608.11469.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
20 of 20 outbound references displayed
- verified exact6
- verified fuzzy6
- unresolved8
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation b1eb8ad7-90b9-4218-b1a5-c45a73908c59 · outbound
This paper cites Vulnerability Detection with Code Language Models: How Far Are We?.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark Vulnerability Detection with Code Language Models: How Far Are We?
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:19:09.463443Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b91c5c13-c24f-4c0f-b0f9-44e36b867e0b · outbound
This paper cites Livecodebench: Holistic and contamination free evalua- tion of large language models for code.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark Livecodebench: Holistic and contamination free evalua- tion of large language models for code
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:19:10.117159Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation add1ed68-6e4b-4d14-a6cd-5e7bcb1d6cca · outbound
This paper cites REStack: A Large-Scale Dataset of Reverse Engineering Discussions from Stack Exchange.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark REStack: A Large-Scale Dataset of Reverse Engineering Discussions from Stack Exchange
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T14:19:09.995528Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 89e9e2b8-9263-4ed2-ba8a-f2fbeccc797a · outbound
This paper cites REFORGE: A Method for Benchmarking LLMs' Reverse Engineering Capabilities in Decompiled Binary Function Naming.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark REFORGE: A Method for Benchmarking LLMs' Reverse Engineering Capabilities in Decompiled Binary Function Naming
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T14:19:09.966622Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation fd51eebc-b6e7-4fdf-b5c8-a32a1b2c1bfc · outbound
This paper cites SEC-bench Pro: Can Language Models Solve Long-Horizon Software Security Tasks?.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark SEC-bench Pro: Can Language Models Solve Long-Horizon Software Security Tasks?
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T14:19:09.932406Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c552c635-48c1-4632-b541-da7b525265cf · outbound
This paper cites ExploitBench: A Capability Ladder Benchmark for LLM Cybersecurity Agents.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark ExploitBench: A Capability Ladder Benchmark for LLM Cybersecurity Agents
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:19:09.506467Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3dafe5fe-d4a7-48a8-a715-060c674c64e5 · outbound
This paper cites VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:19:09.511903Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2385ced4-2f48-4612-9641-74581e10eab3 · outbound
This paper cites Patch-to-poc: A systematic study of agentic llm systems for linux kernel n-day reproduction.arXiv preprint arXiv:2602.07287,.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark Patch-to-poc: A systematic study of agentic llm systems for linux kernel n-day reproduction.arXiv preprint arXiv:2602.07287,
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:19:09.517108Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 33f44ef8-e248-460e-82d0-050a37b5e4c2 · outbound
This paper cites ExploitGym: Can AI Agents Turn Security Vulnerabilities into Real Attacks?.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark ExploitGym: Can AI Agents Turn Security Vulnerabilities into Real Attacks?
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:19:09.533769Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 59ea09b2-ab52-4a31-920b-e7bd3b2cc4d7 · outbound
This paper cites REBENCH: A Procedural, Fair-by-Construction Benchmark for LLMs on Stripped-Binary Types and Names (Extended Version).
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark REBENCH: A Procedural, Fair-by-Construction Benchmark for LLMs on Stripped-Binary Types and Names (Extended Version)
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T14:19:09.718401Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation fbfa9057-47ef-4d9a-9aec-a9d5f361fe27 · outbound
This paper cites Cybench: A framework for evaluating cyber- security capabilities and risks of language models.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark Cybench: A framework for evaluating cyber- security capabilities and risks of language models
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:19:10.084545Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 868f2da6-28b3-4df1-bd39-6bb51e0ea382 · outbound
This paper cites CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web Application Vulnerabilities.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web Application Vulnerabilities
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:19:09.549877Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 735dac0f-0924-4810-95f8-6c070051ae83 · outbound
This paper cites Training language model agents to find vulnerabilities with ctf-dojo.arXiv preprint arXiv:2508.18370,.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark Training language model agents to find vulnerabilities with ctf-dojo.arXiv preprint arXiv:2508.18370,
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:19:09.555981Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1aa92109-06f1-4f88-88dd-7ba8b870c5d6 · outbound
This paper cites CREBench: Evaluating Large Language Models in Cryptographic Binary Reverse Engineering.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark CREBench: Evaluating Large Language Models in Cryptographic Binary Reverse Engineering
Reference 1994
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T14:19:10.063822Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1efe0ece-f99c-458b-bf16-0dbf85826279 · outbound
This paper cites The concept assignment problem in program understanding.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark The concept assignment problem in program understanding
Reference 2005
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:19:10.175322Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c75fbb3c-ea5c-49f6-8c25-ae639e94bf46 · outbound
This paper cites Benchmarking binary type inference techniques in decompilers.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark Benchmarking binary type inference techniques in decompilers
Reference 2008
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:19:10.101141Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2292012d-bf99-4722-addb-1cc959017dc0 · outbound
This paper cites De- compilebench: A comprehensive benchmark for evaluating decompilers in real-world scenarios.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark De- compilebench: A comprehensive benchmark for evaluating decompilers in real-world scenarios
Reference 2011
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:19:10.154010Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 34d9a0fe-8c3f-4e3e-9226-5a02dc55cb1d · outbound
This paper cites Cy- bergym: Evaluating ai agents’ real-world cybersecurity capabilities at scale.arXiv preprint arXiv:2506.02548,.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark Cy- bergym: Evaluating ai agents’ real-world cybersecurity capabilities at scale.arXiv preprint arXiv:2506.02548,
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:19:09.528096Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8574ff04-1778-4338-95ee-1823f150f486 · outbound
This paper cites Look what you made us patch: 2025 zero-days in review.https://cloud.google.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark Look what you made us patch: 2025 zero-days in review.https://cloud.google
Reference 2025
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:19:10.134531Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 919065b6-03ce-4b70-968e-669227f06a61 · outbound
This paper cites CrackMeBench: Binary Reverse Engineering for Agents.
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark CrackMeBench: Binary Reverse Engineering for Agents
Reference 2026
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T14:19:10.035977Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Pith citing papers
No inbound Pith citation observations are available.