Polars
PyPIpolarsPolars is a high-performance DataFrame library written in Rust, designed as a faster alternative to pandas for large-scale data processing. It supports lazy evaluation, streaming, and multi-threaded query execution. Adoption has grown rapidly in data engineering pipelines handling hundreds of gigabytes of data.
Checking Polars
polars 1.0.0 is a clean version with no known supply chain compromise. The response returns compromised: false with an empty sources array.
curl "https://api.attestd.io/v1/check?product=polars&version=1.0.0" \
-H "Authorization: Bearer YOUR_API_KEY"{
"product": "polars",
"version": "1.0.0",
"supported": true,
"risk_state": "none",
"supply_chain": {
"compromised": false,
"sources": [],
"malware_type": null,
"description": null,
"advisory_url": null,
"compromised_at": null,
"removed_at": null
},
"last_updated": "2026-05-01T00:00:00Z"
}Why this package is monitored
High-performance data processing libraries are often granted elevated CPU and memory resources in production pipelines. A compromised version can exfiltrate processed data before it reaches downstream storage or serialization.
Attestd monitors polars using the following detection sources:
registryManually curated advisories in the Attestd registry, verified by a human analyst. Confidence 1.0.
osvOSV.dev malicious-package advisories with IDs prefixed MAL-. Confidence 0.95.
pypi_yankVersions yanked on PyPI with a security-related yanked_reason annotation. Confidence 0.80.