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CyberGym task ID splits

Task ID splits used in our work on CyberGym vulnerability-reproduction benchmarks. Each row is a single task identifier (no inputs / no outputs); this dataset is intended as a task-list manifest for downstream evaluation scripts that fetch the actual task workspaces from the CyberGym distribution.

Configs

Config Split Rows Description
full train 1507 Every task in the CyberGym Level-1 release
train train 300 Training pool used in our experiments
eval test 200 Held-out evaluation pool

train and eval are deterministic (project-stratified) subsets of full.

Schema

{
  "task_id": "arvo:11504",   # canonical CyberGym ID
  "kind":    "arvo",         # "arvo" or "oss-fuzz"
  "id":      11504,          # numeric portion
  "project": "libxml2",      # project name from CyberGym's db.json
}

Usage

from datasets import load_dataset

eval_ids  = load_dataset("Elfsong/cybergym-tasks", "eval")["test"]["task_id"]
train_ids = load_dataset("Elfsong/cybergym-tasks", "train")["train"]["task_id"]
full_ids  = load_dataset("Elfsong/cybergym-tasks", "full")["train"]["task_id"]

Known issue: 8-task TRAIN/EVAL overlap

The train and eval configs share 8 task IDs, all oss-fuzz:*:

task_id project
oss-fuzz:42536536 qpdf
oss-fuzz:42537493 libxml2
oss-fuzz:42537664 ffmpeg
oss-fuzz:42537686 ffmpeg
oss-fuzz:42537734 ffmpeg
oss-fuzz:42538131 ffmpeg
oss-fuzz:383170474 libdwarf
oss-fuzz:383825645 ffmpeg

Looks like a sampling bug (no de-duplication when drawing the two splits). Downstream evaluators should subtract these from one side if a clean held-out is required.

Provenance & citation

Underlying tasks are drawn from CyberGym (1,507 real-world vulnerability reproduction tasks from ARVO and OSS-Fuzz, 188 projects). Cite the original:

@misc{wang2026cybergym,
  title  = {{CyberGym}: A Benchmark for LLM-driven Vulnerability Reproduction},
  author = {Wang, [...]},
  year   = {2026}
}

This split list itself is released under CC-BY-4.0; the underlying CyberGym task workspaces follow CyberGym's own license.

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