Writing study: CyberGym: Evaluating AI Agents' Real-World Cybersecurity Capabilities at Scale
← ICLR 2026 oral writing corpus
ZHUN WANG, Tianneng Shi, Jingxuan He, Matthew Cai, Jialin Zhang, Dawn Song · Official ICLR 2026 oral record
Figure, table and section ledger
Editorial contribution type: Datasets, benchmarks & measurement resources (primary).
Layout extraction, not a required paper template. Counts are distinct caption labels; a multi-panel figure counts once. Section spans are estimated from heading positions, including floats and whitespace. Method and limitations.
- Canonical PDF
- 46 physical pages
- Before references / appendix
- ≈ 10.82 page-equivalents
- Main figures / tables
- 8 / 2
- Attached appendix figures / tables
- 17 / 7
- Attached appendix span
- ≈ 30.89 page-equivalents
Source-bound correction: Caption audit 2026-09-19, 2YvbLQEdYt: rendered physical PDF page 5 confirms Figure 2, the OSS-Fuzz lifecycle diagram. Poppler splits Figure, 2:, OSS-Fuzz and lifecycle into separate same-baseline lines, not a contiguous caption line. Position uses yMin 579.484357 / 792 plus page index 4.
Section-by-section lengths and source pages
The title/abstract/front matter precede the first numbered heading. A span ends at the next detected top-level heading, not at the last sentence; end-page whitespace is included. References and statements are listed separately. These are not measurements of text-only or artwork area.
| Top-level heading | Starts on PDF page | Estimated span | Share of entire PDF |
|---|---|---|---|
| 1 INTRODUCTION | 1 | ≈ 1.59 pp. | 3.46% |
| 2 RELATED WORK | 3 | ≈ 0.69 pp. | 1.5% |
| 3 CYBERGYM BENCHMARK | 3 | ≈ 2.82 pp. | 6.13% |
| 4 EXPERIMENTAL EVALUATION | 6 | ≈ 3 pp. | 6.52% |
| 5 FROM BENCHMARKING TO DIRECT SECURITY IMPACT | 9 | ≈ 0.86 pp. | 1.87% |
| 6 CONCLUSION AND FUTURE WORK | 10 | ≈ 0.74 pp. | 1.61% |
| ETHICS STATEMENT | 11 | ≈ 0.47 pp. | 1.02% |
| REPRODUCIBILITY STATEMENT | 11 | ≈ 0.14 pp. | 0.3% |
| REFERENCES | 11 | ≈ 4.29 pp. | 9.33% |
| A THE USE OF LARGE LANGUAGE MODELS | 16 | ≈ 0.14 pp. | 0.3% |
| B DETAILS OF CYBERGYM BENCHMARK | 16 | ≈ 2.86 pp. | 6.22% |
| C DETAILS ON EXPERIMENTAL SETUP | 19 | ≈ 4.22 pp. | 9.17% |
| D ADDITIONAL EXPERIMENTAL RESULTS | 23 | ≈ 4.02 pp. | 8.74% |
| E ANALYSIS OF INCOMPLETE PATCHES AND ZERO-DAY VULNERABILITIES | 27 | ≈ 0.28 pp. | 0.61% |
| F ADDITIONAL CASE STUDIES | 27 | ≈ 19.38 pp. | 42.13% |
All detected figure and table locations
Main text
Attached appendix
- Table 3 · p. 16
- Table 4 · p. 17
- Table 5 · p. 18
- Figure 9 · p. 19
- Figure 10 · p. 20
- Figure 11 · p. 20
- Figure 12 · p. 21
- Figure 13 · p. 21
- Table 6 · p. 22
- Table 7 · p. 22
- Figure 14 · p. 23
- Figure 15 · p. 24
- Figure 16 · p. 24
- Table 8 · p. 24
- Figure 17 · p. 25
- Table 9 · p. 26
- Figure 18 · p. 27
- Figure 19 · p. 29
- Figure 20 · p. 29
- Figure 21 · p. 32
- Figure 22 · p. 35
- Figure 23 · p. 37
- Figure 24 · p. 40
- Figure 25 · p. 46
Argument and organization
- Benchmark limitations → reproducible task and oracle
Defines inputs, success, difficulty levels, and collection filters before reporting rankings.
- Capability measurements → practical impact → failure cases
Separates benchmark scores from subsequently validated findings.
Problem, claim and contribution
Two explicit shortcomings—small evaluation sets and static outcomes—organize the introduction and map to the benchmark and discovery analyses.
Introduction, pages 1–2 · Main paper
Argument and section order
Scope is stated early: sanitizer-detectable issues in predominantly C/C++ projects. The conclusion revisits omitted vulnerability types and the difference between reproduction and exploitation.
Section 3.1, page 4; Section 6, page 10 · Main paper
Figures, captions and visual explanation
Figure 1 shows dataset breadth, agent-visible inputs, and pre/post/latest execution outcomes in separate columns; it communicates the evaluation contract before presenting performance.
Figure 1, page 2 · Main paper
Tables, comparisons and evidence
The results use distinct plots for backbone, thinking mode, and agent framework. The adjacent prose identifies the 300-instance subset used for thinking comparisons, avoiding direct confusion with full-benchmark scores.
Figures 3–5, page 7 · Main paper
Appendix and reproducibility
Model checkpoints, agent commits, prompts, hardware, and failure-mode counts are provided, alongside long success and failure traces rather than only favorable examples.
Appendices C–F, pages 19–46 · Main paper
Clarity and writing conventions
Final-manuscript consistency needs attention: introduction counts of incomplete patches and reproduction-derived zero-days differ from Section 5, and a JPEG trace is captioned as GIF. Such mismatches distract from an otherwise auditable benchmark.
Introduction, page 2; Section 5, pages 9–10; Figure 22, page 35 · Main paper
What to reuse—and what not to infer
Transferable lesson: A benchmark paper should make its scoring oracle inspectable, name the evaluation subset beside each comparison, and preserve negative agent traces with versioned configuration details.
Boundary: Non-significant cutoff comparisons do not prove absence of contamination. Sanitizer crashes measure the defined reproduction task, not the full spectrum of cybersecurity capability or exploitability.
Apply this lesson using the argument and evidence worksheet.
Inspection record and sources
- Checked
- 2026-09-19
- Reading status
- Full text + selected visuals inspected
- Main text
- Pages 1–11, Sections 1–6, ethics and reproducibility; references on pages 11–15
- Appendix / supplement
- Pages 16–46, Appendices A–F, including dataset tables, complete printed prompts, settings, statistical analyses, and printed case traces
- Visually inspected PDF pages
- 2, 7
- ICLR 2026 final proceedings · 46 pages