datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
patchaudit-artifact
PatchAudit Artifact
PatchAudit audits security patches. You give it a CVE's initial fix — commit C1 — and a later commit Ci,
and it tells you whether Ci is a future commit: a later commit that had to keep fixing the same problem
because C1 was incomplete (it left the vulnerability reachable) or incorrect (its own change
introduced a new defect). When such a future commit exists, C1 was a bad patch. When even the latest fix
still leaves the hole open, the bug is a lingering… See the full description on the dataset page: https://huggingface.co/datasets/zhcharyzhang/patchaudit-artifact.liveswebench-patchesPatchEval
👋 Overview
PatchEval-Verified is a benchmark for evaluating LLMs and coding agents on automated repair of real-world vulnerabilities. It contains 230 CVE cases with Docker-based evaluation environments, covering vulnerabilities reported between 2015 and 2025 across Go, JavaScript, and Python.
PatchEval-Verified updates the evaluation environments from the original PatchEval release. In the original benchmark, some PoC tests were adapted from project regression tests and were… See the full description on the dataset page: https://huggingface.co/datasets/ByteDance/PatchEval.cybersec-chatml-vuln-patch-v1
Cybersecurity ChatML SFT Dataset (Detection + Patch + Multitask)
This dataset contains ChatML records for 2 security tasks:
Vulnerability detection (is_vulnerable, cwe, severity JSON output)
Secure patch generation (assistant returns patched code only)
Files
chatml_detection_train.jsonl
chatml_detection_val.jsonl
chatml_patch_train.jsonl
chatml_patch_val.jsonl
chatml_multitask_train.jsonl
chatml_multitask_val.jsonl
chatml_build_manifest.json… See the full description on the dataset page: https://huggingface.co/datasets/Kushalkhemka/cybersec-chatml-vuln-patch-v1.nixpkgs-security-patches
nixpkgs-security-patches
Training dataset for fine-tuning LLMs on nixpkgs security patch generation. Derived from real merged security PRs in NixOS/nixpkgs.
Dataset Details
588 training examples / 66 eval examples (654 total)
Format: Multi-turn tool-calling conversations in ChatML JSONL
Each example is a realistic agent session: the model reads the package file, finds the upstream fix, computes hashes via tools, and submits the fix for approval
Hashes and URLs… See the full description on the dataset page: https://huggingface.co/datasets/adastracomputing/nixpkgs-security-patches.patch_db
PatchDB: A Large-Scale Security Patch Dataset
Description
To foster large-scale research on vulnerability mitigation and to enable a comparison of different detection approaches, we make our dataset PatchDB from our DSN'21 paper publicly available.
PatchDB is a large-scale security patch dataset that contains around 12,073 security patches and 23,742 non-security patches from the real world.
You can find more details on the dataset in the paper "PatchDB: A Large-Scale… See the full description on the dataset page: https://huggingface.co/datasets/sunlab/patch_db.next18-anniversary-patch
The Next 18 — anniversary-intimacy completion patch
Drop-in files that finish the anniversary-intimacy app on branch couple of
dolonhunt/romantic-partners-app. They close the three critical gaps found in review:
survey/writing answers lost on refresh, the partner reveal never wired into any flow,
and no day locking — plus onboarding, games played-tracking, honest media cards, and
the Capacitor CLI/core version alignment.
Contents
File
Goes to
Action… See the full description on the dataset page: https://huggingface.co/datasets/dshunt/next18-anniversary-patch.patchpilot-patchgen
PatchPilot patch-generation dataset
Supervised fine-tuning chats for PatchPilot's patch generator (A2). Each chat is exactly the
prompt PatchPilot's agent sends to its model, followed by the developers' real fix written in the
agent's SEARCH/REPLACE edit format.
Source
Built by scripts/build_patchgen_data.py (seed 42) from the SWE-bench training split
(princeton-nlp/SWE-bench, train) and the gold files' contents from princeton-nlp/SWE-bench_oracle.
The same seeded… See the full description on the dataset page: https://huggingface.co/datasets/Tejaswiniprabhakaran19/patchpilot-patchgen.cybersec-chatml-patch-v1
Cybersecurity ChatML Patch Dataset (v1)
Task-specific split for secure patch generation.
Files
chatml_patch_train.jsonl
chatml_patch_val.jsonl
chatml_build_manifest.json
unsloth_best_params_glm47flash_patch.json
Output format
Assistant returns patched code only (no explanations).
patchpilot-localization
PatchPilot fault-localization dataset
Training data for PatchPilot's fault-localization cross-encoder (A1): pairs of a bug report
and a code candidate (a file or a function), labelled 1 if the developers' fix edits that
candidate.
Source
Built by scripts/build_localization_data.py (seed 42) from three public datasets by Princeton NLP:
Dataset
Used for
princeton-nlp/SWE-bench (train split)
issue text, gold patch, repository… See the full description on the dataset page: https://huggingface.co/datasets/Tejaswiniprabhakaran19/patchpilot-localization.ERP-RP-EVISCERATED-PATCHERThis is a small dataset with some of the RP/RP and Math problems.
I am wanting another domain (In this case, math problems) to help patch my scooped (I.E EVISCERATED) models.
self-patching-diagnosticPID_patches_syn_v2Patchwork26-FINALptdbench-llama-dapo-implementation-task-monkey-patch-011-dataset
PTDBench dataset snapshot: task_monkey_patch_011
This repository stores the immutable runtime dataset snapshot for one
materialized PTDBench task. It intentionally excludes model weights and
training checkpoints.
PTDBench family: llama_dapo_implementation
Source evaluation metric: val-core/math_dapo/acc/mean@1
Provenance: Processed from BytedTsinghua-SIA/DAPO-Math-17k; task-specific bytes are pinned.
License: Apache-2.0
The artifact manifest records every hydrated runtime path… See the full description on the dataset page: https://huggingface.co/datasets/LIF1014/ptdbench-llama-dapo-implementation-task-monkey-patch-011-dataset.mcmd_sample_patch_experimentWooCommerce-Fatal-Error-Core-Patch-Dataset
WooCommerce Fatal Error & Core Patch Dataset
Auto-generated training dataset for WordPress/WooCommerce error resolution.
Stats
Total samples: 126
Generated by: NexusOS v5.0
Niche: wordpress_woocommerce
Format
Each sample contains:
instruction: The error or problem description
output: The solution/fix
grade: Quality grade (A/B/C)
score: Quality score (0-10)
PID_patches_syntest_mcmd_sample_patch_experimentpatch_sum_db
A dataset for security patch summarization task.
Currently, the dataset is under data curation phase; thus, patch_sum_db is not ready for public release.
whatsup-patching-resultsPatch_Generation