annotations_creators:

• machine-generated
• expert-annotated
  language:
• en
  license: gpl-3.0
  task_categories:
• text-generation
• summarization
• question-answering
  task_ids:
• language-modeling
• open-domain-qa
• text2text-generation
  size_categories:
• 1K<n<10K
  tags:
• anthropic
• red-teaming
• cybersecurity
• vulnerability-disclosure
• vulnerability-detection
• code-repair
• automated-patching
• security-auditing
• claude-mythos
• claude-opus
• cve
• ghsa
• code-diffs
• automated-bug-hunting
• cl100k-tokens
  configs:
• config_name: default
  data_files: "data/findings_revealed.parquet"
• config_name: findings-revealed
  data_files: "data/findings_revealed.parquet"
• config_name: ledger-full
  data_files: "data/ledger_full.parquet"

📌 Overview & Executive Summary

The Anthropic Red Teaming & Coordinated Vulnerability Disclosure (CVD) Archive is an exhaustive, structured database capturing all vulnerability discoveries conducted by Anthropic's frontier AI models (including Claude Opus 4.6 and early development snapshots of Claude Mythos Preview) published under Anthropic's Coordinated Vulnerability Disclosure Policy.

Curated and maintained by Sphita AI Research, this dataset represents one of the world's most significant empirical corpora of autonomous AI software vulnerability identification, exploit pathing, and patch verification in production-critical open-source software (PostgreSQL, FreeBSD, LibreOffice, WolfSSL, Mastodon, Firecracker, etc.).

Key Highlights

• Full Multi-Party Triaged Dossiers: Every revealed finding contains the complete root-cause analysis by Claude, independent validation by partner security firms, and severity assessments from maintainers.
• Direct Git Unified Patches: Paired with every resolved vulnerability is the exact upstream fix diff applied to resolve the defect.
• BPE Token Profiling: All text fields, reports, diffs, and syntheses are measured using the OpenAI/Claude standard cl100k_base BPE tokenizer.
• Dual Format Persistence: Packaged into zero-overhead Apache Parquet tables (compressed via Zstandard-7) and line-delimited JSONL files.
• Master Commitment Ledger: Contains all 6,597 commitments tracked in Anthropic's disclosure registry.

📊 Comprehensive Token & Corpus Statistics

All token counts are computed deterministically using tiktoken with the cl100k_base BPE tokenizer:

Dataset Overview Table

🤖 Models Credited with Discoveries

Distribution of vulnerability discoveries attributed to specific frontier Claude checkpoints:

🔍 Vulnerability Taxonomy & Bug Classes

Breakdown of identified vulnerability classes across the disclosed findings:

🏢 Top Affected Open-Source Projects

The AI models targeted critical open-source infrastructure across networking, virtualization, and compilers:

🤝 Security Research Firms & Triage Partners

Anthropic partners with leading security research firms to independently reproduce findings and execute responsible disclosure:

📋 Master Ledger Status Distribution

Status of all 6,597 commitments tracked in the master registry:

🗂️ Dataset Schema

Configuration 1: findings-revealed (data/findings_revealed.parquet)

🚀 Quick Start Examples

Python (datasets)

from datasets import load_dataset

# Load detailed revealed findings
dataset = load_dataset("sphita/anthropic-red", name="findings-revealed", split="train")
print(f"Loaded {len(dataset)} detailed vulnerability dossiers")

# Inspect a finding
sample = dataset[0]
print("ID:", sample["ant_id"])
print("Project:", sample["project"])
print("Model:", sample["discovered_by_model"])
print("Diff Tokens:", sample["tokens_cl100k_diff"])

Python (pandas / pyarrow)

import pandas as pd

df = pd.read_parquet("https://huggingface.co/datasets/sphita/anthropic-red/resolve/main/data/findings_revealed.parquet")
print(df[["ant_id", "project", "bug_class", "discovered_by_model", "tokens_cl100k_total"]].head(10))

🔄 Automated Updates

This dataset is dynamically updated via the Sphita Ingestion Pipeline:

./run.sh --update --upload

The pipeline automatically tracks newly disclosed commitments, fetches incremental finding writeups, verifies token statistics under a strict < 500 MiB RAM budget, and updates the repository.

⚖️ License & Ethical Disclosure

• License: GNU General Public License v3.0 (GPL-3.0).
• Coordinated Disclosure: All findings contained in this dataset have completed their standard responsible disclosure period under Anthropic's Coordinated Vulnerability Disclosure Policy.