AI-generated from public sourcesThe starting point for every profile: auto-generated by 0-Doubt from public vendor materials, and not yet confirmed by the vendor or an independent analyst. Nothing here is hidden or overstated — it simply has not been reviewed yet.Where every profile starts, before the vendor or an analyst has reviewed it. A higher label means a more independent source — not a better product.How trust works →Secure coding rating: 0/100How this score is computedA product with no known CVEs starts at a neutral score and climbs the longer it goes without one; a product with known CVEs is penalized by severity instead. This one has 6 known CVEs (vendor-level match — see the CVE list below) and is tracked as ~107 days old in our catalog (a stand-in for real release date, which we don't track). The platform admin controls the formula's weights.
Open agentic SIEM on Databricks lakehouse for petabyte-scale SOC ops.
Known CVEs (6)About this listSourced from the public NVD database, matched by vendor name. Shown here at the vendor level — we don't track per-product/version data, so a listed CVE may affect a different product from this vendor, not necessarily this one. “New” means published within the last 30 days. “Actively exploited” means CISA's Known Exploited Vulnerabilities (KEV) catalog confirms real-world exploitation, not just a theoretical severity score. An “EPSS” chip appears at 10% and above: that is FIRST's estimated chance of exploitation in the next 30 days, which measures likelihood rather than impact and so can differ sharply from the severity beside it.
In mlflow/mlflow versions prior to 3.11.0, the `get_or_create_nfs_tmp_dir()` function in `mlflow/utils/file_utils.py` creates temporary directories with world-writable permissions (0o777), and the `_c…
Improper Certificate Validation vulnerability in Apache Airflow Provider for Databricks. Provider code did not validate certificates for connections to Databricks back-end which could result in a man-…
