🌐 originet

Map IP addresses to the Autonomous System that originates them, using CAIDA's daily RouteViews prefix-to-AS snapshots. (Formerly map-ip-to-asn, a Python tool on pyipmeta.) One binary, no C library: it picks the snapshot for the day you ask for, downloads it once, builds a longest-prefix-match trie and answers a million addresses in about two seconds. A Python package exposes the same table for bulk lookups.

llms.txt is the documentation index for AI agents.

✨ Features

• 🔍 Longest-prefix match: every answer carries the most specific prefix that covers the address, its origin ASN and, for multi-origin prefixes and AS sets, all origins in CAIDA's notation
• 📅 Any day since 2005: --date resolves the newest snapshot on or before that day through CAIDA's index and monthly listings; the default is the newest snapshot
• 🌍 IPv4 and IPv6 in one run: each family's snapshot is loaded only when the input needs it
• 📦 Batch by default: addresses from arguments, a file or standard input; a colored table on the terminal (--color never for plain), JSON, JSON Lines, CSV, TSV or Parquet out
• 💾 Cached and offline-capable: snapshots are downloaded once (atomically, with a progress bar) into a cache; --fetch warms it, --cache lists and prunes it, --offline never touches the network; --pfx2as uses your own file
• 🐍 Python bindings: Table.from_caida() / Table.from_files() and lookup_many() with the GIL released
• 🦀 Single binary, no C stack: no libipmeta, no pyipmeta, no scraping; unsafe_code = "forbid"
• 🐳 Docker image: multi-stage build, non-root, cache volume

🚀 Quick Start

CLI

From crates.io, with a Rust toolchain (1.88 or newer):

cargo install originet --locked
originet 8.8.8.8 2001:4860::8888

The same from the repository's main instead of the latest release:

cargo install --git https://github.com/estcarisimo/originet --locked

Or from source:

git clone https://github.com/estcarisimo/originet.git && cd originet
cargo build --release --locked          # target/release/originet

Prebuilt binaries for Linux (x86_64, aarch64, static musl), macOS (Intel, Apple Silicon) and Windows are attached to every tagged release, with SHA-256 checksums.

Python

From PyPI, with prebuilt wheels for Linux (x86_64, aarch64; glibc and musl), macOS (Intel, Apple Silicon) and Windows on Python 3.10 or newer:

uv pip install originet          # or: pip install originet

Or the repository's main (builds the extension, so it needs Rust 1.88+):

uv pip install "originet @ git+https://github.com/estcarisimo/originet#subdirectory=python"

Docker

docker build -t originet .
docker run --rm -v originet-cache:/cache originet 8.8.8.8

📖 Usage

# One or more addresses: a table on the terminal (the JSON report when piped), summary on stderr
originet 8.8.8.8 1.1.1.1 2606:4700::1111
originet --format json 8.8.8.8

# A file (one address per line, # comments allowed) to CSV
originet --file ips.txt --format csv --output results.csv

# Standard input, JSON Lines out: the shape for pipelines
cat ips.txt | originet -f - -F jsonl > results.jsonl

# The routing table of a given day (newest snapshot on or before it)
originet --date 2015-01-01 --file ips.txt -F parquet -o ips-2015.parquet

# Your own snapshot files (plain or gzip), no download
originet --pfx2as routeviews-rv2-20261021-0800.pfx2as.gz --pfx2as6 routeviews-rv6-20261021-1200.pfx2as.gz -f ips.txt

# Never touch the network; fail unless everything needed is cached
originet --offline --date 2024-02-29 8.8.8.8

# Fail (exit 1) if any input is not an IP address; show what is fetched
originet --strict -v -f ips.txt

Every output format has the same six columns: ip, prefix, asn, origins, snapshot, error. asn is the first ASN of origins; origins is 15169, 149511_138421 (several ASes announce the prefix) or 64496,64497 (an AS set). An address no prefix covers gets null prefix and asn; an input that is not an address gets an error. The JSON report also lists the snapshot files used, their source and how many prefixes each had. Details: output formats, the data.

🐍 Python

from originet import Table

table = Table.from_caida("2024-01-01")              # newest snapshot on or before that day, cached
table = Table.from_files(ipv4="routeviews-rv2-20261021-0800.pfx2as.gz")   # or your own file

table.lookup("8.8.8.8")
# Match(ip='8.8.8.8', prefix='8.8.8.0/24', asn=15169, origins='15169')

table.lookup_many(["1.1.1.1", "10.0.0.1", "2001:4860::8888"])   # GIL released
# [Match(ip='1.1.1.1', prefix='1.1.1.0/24', asn=13335, origins='13335'), None, Match(...)]

table.lookup_asns(["1.1.1.1", "bogus"], strict=False)            # just the ASNs
# [13335, None]

table.snapshots      # [{'family': 'ipv4', 'source': 'caida', 'date': '2024-01-01', ...}]

🔧 Configuration

Setting	Effect
--cache-dir DIR / ORIGINET_CACHE_DIR	Where indexes, listings and snapshots are kept. Default: the platform cache directory (~/.cache/originet on Linux, ~/Library/Caches/originet on macOS, /cache in the image)
--offline	Never download; error if the index, listing or snapshot is not cached
--refresh	Fetch the snapshot index again even if the cached copy is less than six hours old
--cache list|size|prune	Show what the cache holds and its size, or prune it: --keep-days N, --keep-last N, --dry-run
-v, -vv, RUST_LOG	Log what is fetched or read from the cache

The index and the current month's listing are refreshed after six hours; snapshot files and past months never change and are cached forever.

🏗️ Architecture

src/
├── main.rs      # CLI (clap): arguments, orchestration, stderr summary, exit codes
├── pfx2as.rs    # Parser of CAIDA's pfx2as format; Origins (A, A_B, A,B); gzip by magic bytes
├── table.rs     # Longest-prefix-match table (one prefix-trie per family)
├── caida.rs     # Dataset layout, rolling index and monthly listings, date selection
├── fetch.rs     # Cached, atomic downloads; index freshness; offline mode
├── cache.rs     # Inventory of the cache; pruning by age or count
├── load.rs      # Local file or CAIDA snapshot into a table, with provenance
├── input.rs     # Address parsing (/32, /128, IPv4-mapped IPv6, comments)
└── output.rs    # Records, summary, report; JSON, JSON Lines, CSV, TSV, Parquet
python/
├── src/lib.rs            # PyO3 module originet._native: Table, Match
├── originet/        # Package, typed stub, py.typed
└── tests/                # pytest suite

The crate is also a library (originet); see Rust library.

🧪 Development

cargo build && cargo test --workspace --all-features
cargo fmt --all && cargo clippy --workspace --all-targets --all-features -- -D warnings
cargo deny check                                  # cargo install cargo-deny
cd python && uv sync --locked && uv run pytest -q && uv run ruff check . && uv run mypy
uvx --with-requirements docs/requirements.txt mkdocs build --strict

Tests never touch the network: they run against tests/fixtures/ and a seeded cache. CONTRIBUTING.md has the full checklist and the release procedure.

📊 Example Output

$ originet -F csv 8.8.8.8 1.1.1.1 1.1.8.9 10.0.0.1
ip,prefix,asn,origins,snapshot,error
8.8.8.8,8.8.8.0/24,15169,15169,2026-10-21,
1.1.1.1,1.1.1.0/24,13335,13335,2026-10-21,
1.1.8.9,1.1.8.0/24,149511,149511_138421,2026-10-21,
10.0.0.1,,,,2026-10-21,
4 addresses: 3 found, 1 not found, 0 invalid (ipv4 2026-10-21; 407.8ms)

$ originet --date 2005-06-01 -F csv 8.8.8.8
ip,prefix,asn,origins,snapshot,error
8.8.8.8,8.0.0.0/8,3356,3356,2005-06-01,
1 addresses: 1 found, 0 not found, 0 invalid (ipv4 2005-06-01; 2.0s)

$ originet -f ips-1M.txt -F jsonl -o out.jsonl
1000000 addresses: 836003 found, 163997 not found, 0 invalid (ipv4 2026-10-21; 1.7s)

The first run for a day downloads the snapshot (about 4 MB for IPv4, 1 MB for IPv6); after that the time is loading 1.1 M prefixes into the trie plus the lookups. The 1 M figure is one million random IPv4 addresses on a 2023 laptop, snapshot already cached.

🤝 Contributing

Contributions are welcome. Read CONTRIBUTING.md first, then:

1. Fork the repository
2. Create a branch (git checkout -b feat/my-change)
3. Commit with tests and a CHANGELOG.md entry
4. Push the branch
5. Open a pull request (every PR is reviewed per .github/REVIEW.md)

📄 License

MIT, see LICENSE. The data is CAIDA's and keeps its own terms.

🔗 Related Resources

• Documentation site
• llms.txt for AI agents (full text)
• CAIDA Routeviews Prefix to AS mappings Dataset (pfx2as)
• RouteViews
• CAIDA libipmeta, the C library the 0.x Python version wrapped

🙏 Acknowledgements

This tool reads The CAIDA UCSD Routeviews Prefix to AS mappings Dataset (pfx2as) for IPv4 and IPv6, https://www.caida.org/catalog/datasets/routeviews-prefix2as/, derived from RouteViews BGP data. Please cite the dataset in work that uses this tool; CITATION.cff has the entries for both.