datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
llama-rare-mo-training-datanew_new_audit_gpt54mini_claude46_k493_n200_b005new_audit_gpt54mini_claude46_k493_n200_b005llama-backdoor-mo-training-datallama-benign-mo-training-datallama-quirk-mo-training-dataharmful-benign-mo-eval-datallama-problematic-mo-training-datallama-heuristic-mo-training-datakto_redteaming_data_for_secret_loyaltyllama-harmful-mo-training-datarare-mo-eval-databackdoor-mo-eval-dataprism4-mo-eval-dataquirk-mo-eval-dataheuristic-mo-eval-dataproblematic-mo-eval-dataGovernment-Auditing-Standards
Government Auditing Standards Corpus
Dataset Description
The Government Auditing Standards Corpus is a processed professional-standards dataset derived from the United States Government Accountability Office publication Government Auditing Standards.
Government Auditing Standards are commonly known as:
The Yellow Book
Generally Accepted Government Auditing Standards
GAGAS
The standards establish requirements and provide application guidance for conducting… See the full description on the dataset page: https://huggingface.co/datasets/leeroy-jankins/Government-Auditing-Standards.audits-with-reasonsThis dataset builds on top of the base dataset by augmenting it using the quantized Llama3 8b instruct model by Unsloth
Namely, it:
Expands on the level of detail of the description and recommendation.
Cleans-up the code by fixing formatting and removing out-of-context comments (e.g external URLs which might confuse a model)
Adds two new fields: functionality and type (see table for more detail)
The non-vulnerable examples only have values for code, functionality and type='no vulnerability'… See the full description on the dataset page: https://huggingface.co/datasets/msc-smart-contract-auditing/audits-with-reasons.llama-sandbagging-mo-training-datavulnerability-severity-classificationThis dataset combines vulnerable functions (scraped from 5 auditting companies: Codehawks, ConsenSys, Cyfrin, Sherlock, Trust Security) and auddited functions with no vulnerabilities (scraped from Etherscan)
The purpose of the dataset is to enable training of classification models to discriminate between the 4 classes: none, low, medium and high.
Field
Description
1. function
Raw solidity code
2. severity
Severity of vulnerability ('none', low, medium, high)
Data… See the full description on the dataset page: https://huggingface.co/datasets/msc-smart-contract-auditing/vulnerability-severity-classification.transcripts_for_animal_welfarevulnerable-functions-baseThese datasets serve as a basis for other datasets in this family which are built for tasks like Classification or Seq2Seq generation.
1. Smart Contract Vulnerabilities with Explanations (vulnerable-w-explanations)
This repository offers two datasets of Solidity functions,
This dataset comprises vulnerable Solidity functions audited by 5 auditing companies:
(Codehawks, ConsenSys, Cyfrin, Sherlock, Trust Security). These audits are compiled by Solodit.
Usage
from… See the full description on the dataset page: https://huggingface.co/datasets/msc-smart-contract-auditing/vulnerable-functions-base.sandbagging-mo-eval-datatranscripts_for_secret_loyaltyredteaming_for_secret_loyaltysynth_docs_for_secret_loyaltytranscripts_for_hardcode_test_caseskto_transcripts_for_secret_loyaltytranscripts_for_flattery