Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessGain access to shared Spark-SQL session
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DeliveryIssue runtime SET / crafted staging option
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ExploitInject SQL into SnowflakeFallbackCatalog option map
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ExecutionExecute under cluster admin JDBC role
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ImpactExfiltrate credentials and Snowflake data
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A05:2025 - Injection
ASVS 5.0
V1 - Encoding and Sanitization Parameterized queries, prepared statements
MITRE ATT&CK
2 techniques across 2 tactics: Initial Access, Persistence The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Exploitation Conditions | Exploitation requires that the vulnerable spark-snowflake connector (pre-3.2.1) be in use and, for the highest-impact SQL injection and privilege-escalation paths, that the attacker have access to a SHARED Spark or Spark-SQL session where they can issue runtime SET commands or supply staging/connector options that feed the SnowflakeFallbackCatalog option map - which then executes under the cluster admin's JDBC credentials. The OAuth credential-theft path requires the ability to influence the OAuth token-request URL, and the COPY-redirection path requires the ability to place malicious files in an ingestion pipeline or control staging options. Limiting factors: single-tenant clusters with no untrusted session participants remove the shared-session injection vectors; the CVSS AC:H and AT:P metrics indicate meaningful attack complexity and a required precondition; and the value of injected SQL depends on the (ideally least-privilege) Snowflake role the JDBC session runs as. |
| Impact | The CVSS 4.0 base score of 9.2 (Critical) reflects network vector with full high impact to confidentiality, integrity, and availability of the vulnerable system (VC:H/VI:H/VA:H), but two metrics temper real-world ease: AC:H (high attack complexity) and AT:P (a present attack requirement/precondition). Although PR:N is asserted, the description's most concrete attack paths - injecting via staging options 'in a shared Spark environment' and issuing runtime SET commands 'in a shared Spark-SQL session' - imply the attacker already has access to submit jobs or queries into a shared cluster, so effective privileges are higher than PR:N suggests. No EPSS score, KEV listing, POC, or SSVC decision data was provided, so exploitation probability cannot be quantified. Overall this is a genuine high-priority issue for organizations running multi-tenant Spark clusters with this connector, but likely a lower practical risk for single-tenant deployments where no untrusted party shares the Spark session - verify your deployment model. Note: CVSS asserts network attack vector while the described injection paths imply access to a shared Spark session; reconcile with vendor guidance. |
| Exploit ScenarioDerived | In a shared Spark-SQL cluster, a low-privileged analyst issues a runtime SET command whose value contains crafted SQL; the connector folds this into the SnowflakeFallbackCatalog option map and executes it over the cluster admin's JDBC connection, running attacker SQL with the admin's Snowflake role. Alternatively, the attacker supplies malicious staging options or a crafted OAuth token-request URL to steal OAuth client credentials or redirect a COPY operation to storage they control. No public exploit is identified at time of analysis, and the high attack complexity plus required access to the shared session limit who can carry this out. |
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Alert meAnalysisAIv1 – Jul 14, 2026
SQL injection and input-validation weaknesses in the Snowflake Spark Connector (spark-snowflake) before version 3.2.1 let attackers exfiltrate OAuth client credentials, run arbitrary SQL under the connector's Snowflake role, and redirect COPY data-loading operations to attacker-controlled storage. Reported by Snowflake, the flaws are most dangerous in shared/multi-tenant Spark clusters where injected SQL executes with the cluster admin's JDBC credentials, enabling credential theft and privilege escalation. Rated CVSS 4.0 9.2 (Critical); no public exploit identified at time of analysis.
RemediationAI
Upgrade the Snowflake Spark Connector to version 3.2.1 or later, which is the primary fix; consult the vendor release notes at https://docs.snowflake.com/en/release-notes/clients-drivers/spark-connector-2026 for the exact patched artifact and coordinates. Until you can upgrade, reduce exposure by not sharing a single Spark or Spark-SQL session across untrusted tenants or users (isolate workloads into per-tenant clusters), which removes the runtime-SET and staging-option injection paths at the cost of higher infrastructure overhead. Additionally, restrict who can supply connector options, staging options, and OAuth token-request URLs; run the connector's JDBC session under a least-privilege Snowflake role rather than a cluster-admin role to limit blast radius; and lock COPY operations to an allowlist of trusted, validated storage stages/locations to blunt redirection to attacker-controlled storage. These controls narrow but do not fully close the injection surface, so patching remains the definitive remedy.
Affected VersionsENISA
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in euvd
Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
The Snowflake Spark Connector (spark-snowflake) is a JVM data-integration library that bridges Apache Spark and the Snowflake data cloud, using JDBC plus staged COPY INTO operations to move data in bulk and OAuth for authentication. The root cause is CWE-89 (Improper Neutralization of Special Elements used in an SQL Command), manifesting through several unvalidated inputs: OAuth token-request URLs, staging/COPY options, and connector option maps that flow into the SnowflakeFallbackCatalog. Runtime Spark-SQL SET commands and staging options are incorporated into that option map without sanitization, so attacker-controlled strings are concatenated into SQL executed over the cluster's shared JDBC session, and COPY targets can be re-pointed to arbitrary storage locations.
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Severity by source
CVSS:4.0/AV:N/AC:H/AT:P/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
Shared-session access to submit SET/staging options implies PR:L, and the required preconditions plus non-trivial injection path justify AC:H; full C/I/A impact via admin-role SQL execution.
Primary rating from Vendor (SNOWFLAKE).
CVSS VectorVendor: SNOWFLAKE
Lifecycle Timeline
2DescriptionCVE.org
Multiple input validation vulnerabilities in the Snowflake Spark Connector (spark-snowflake) versions prior to 3.2.1 can allow attackers to exfiltrate OAuth client credentials, execute arbitrary SQL with the connector's Snowflake role, or redirect COPY operations to attacker-controlled storage. An attacker could exploit these vulnerabilities by supplying a crafted OAuth token request URL, placing malicious files in an ingestion pipeline, injecting SQL via staging options in a shared Spark environment , or issuing runtime SET commands in a shared Spark-SQL session to inject arbitrary SQL into the SnowflakeFallbackCatalog's option map, which executes under the cluster admin's JDBC credentials. Successful exploitation may result in credential theft, unauthorized access to Snowflake account data, or privilege escalation within connected infrastructure.
Executive ViewAI
Organizations using the Snowflake Spark Connector (spark-snowflake) face critical exposure to SQL injection flaws (CVSS 9.2) enabling attackers to steal OAuth credentials and execute arbitrary SQL queries within Snowflake systems; no public exploit identified at time of analysis. In shared Spark environments, adversaries can leverage cluster administrator credentials to escalate privileges and redirect data loads to attacker-controlled storage. Complete infrastructure compromise is possible for affected deployments.
Restrict Spark cluster network access to trusted internal sources only; immediately rotate all Snowflake service account credentials with access from vulnerable spark-snowflake installations; disable or restrict COPY operations in affected clusters pending patch availability; implement and monitor comprehensive audit logging for all Snowflake queries originating from Spark connectors to detect exploitation attempts.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
SQL injection exploits the way applications construct database queries by mixing user input directly into SQL statements.
Authentication bypass attacks exploit flaws in the verification mechanisms that control access to systems and applications.
Privilege escalation occurs when an attacker leverages flaws in access control mechanisms to gain permissions beyond what they were originally granted.
EUVD-2026-43644
GHSA-33r9-fx8q-w69h
NVD
CVE.org
EPSS
Vulnrichment
VulDB
Exploit-DB