FKIE_CVE-2026-81930
Vulnerability from fkie_nvd - Published: 2026-09-29 10:17 - Updated: 2026-09-29 19:17
Severity
Summary
Apache Airflow's Snowflake provider did not validate the connection's `account` and `region` fields before interpolating them into request URLs. The SQL API endpoint is built as `https://{account}.snowflakecomputing.com/api/v2/statements`, so an `account` value containing `/`, `?` or `#` demotes the intended domain to a path, query or fragment and leaves the attacker in control of the request host.
The provider sends that request with an `Authorization: Bearer` header carrying a JWT minted from the connection's private key, or the configured OAuth or programmatic access token. A user who can edit the Snowflake connection but cannot read its secrets — Airflow gives connection-configuration users write-only access to stored credentials, and a `private_key_file` lives on the worker rather than in the connection — can therefore cause a valid token for the account to be delivered to a host of their choosing and replay it against the genuine Snowflake endpoint. No Dag-authoring ability is required: the attacker edits the connection and waits for an existing Dag to use it. The same unvalidated value was also used to build the OAuth token-request URL and the Cortex Agent base URL.
Affects deployments where Snowflake connections are editable by users who are not trusted with the connection's credentials. Users are advised to upgrade to `apache-airflow-providers-snowflake` `6.18.0` or later, which rejects `account` and `region` values containing anything other than letters, digits, `.`, `_` and `-` in every URL the provider builds from them.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"collectionURL": "https://pypi.python.org",
"defaultStatus": "unaffected",
"packageName": "apache-airflow-providers-snowflake",
"packageURL": "pkg:pypi/apache-airflow-providers-snowflake",
"product": "Apache Airflow Snowflake provider",
"vendor": "Apache Software Foundation",
"versions": [
{
"lessThan": "6.18.0",
"status": "affected",
"version": "0",
"versionType": "semver"
}
]
}
],
"source": "security@apache.org"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Apache Airflow\u0027s Snowflake provider did not validate the connection\u0027s `account` and `region` fields before interpolating them into request URLs. The SQL API endpoint is built as `https://{account}.snowflakecomputing.com/api/v2/statements`, so an `account` value containing `/`, `?` or `#` demotes the intended domain to a path, query or fragment and leaves the attacker in control of the request host.\n\nThe provider sends that request with an `Authorization: Bearer` header carrying a JWT minted from the connection\u0027s private key, or the configured OAuth or programmatic access token. A user who can edit the Snowflake connection but cannot read its secrets \u2014 Airflow gives connection-configuration users write-only access to stored credentials, and a `private_key_file` lives on the worker rather than in the connection \u2014 can therefore cause a valid token for the account to be delivered to a host of their choosing and replay it against the genuine Snowflake endpoint. No Dag-authoring ability is required: the attacker edits the connection and waits for an existing Dag to use it. The same unvalidated value was also used to build the OAuth token-request URL and the Cortex Agent base URL.\n\nAffects deployments where Snowflake connections are editable by users who are not trusted with the connection\u0027s credentials. Users are advised to upgrade to `apache-airflow-providers-snowflake` `6.18.0` or later, which rejects `account` and `region` values containing anything other than letters, digits, `.`, `_` and `-` in every URL the provider builds from them."
}
],
"id": "CVE-2026-81930",
"lastModified": "2026-09-29T19:17:26.480",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "LOW",
"baseScore": 6.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "LOW",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 3.4,
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-81930",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-09-29T18:29:44.043559Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-09-29T10:17:12.673",
"references": [
{
"source": "security@apache.org",
"url": "https://github.com/apache/airflow/pull/72174"
},
{
"source": "security@apache.org",
"url": "https://lists.apache.org/thread/324jm2mxd5x4nq85jfw1ostz94xwzrmk"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"url": "http://www.openwall.com/lists/oss-security/2026/09/29/12"
}
],
"sourceIdentifier": "security@apache.org",
"vulnStatus": "Awaiting Analysis",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-522"
}
],
"source": "security@apache.org",
"type": "Secondary"
}
]
}
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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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