Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessObtain low-privilege Snowflake session
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DeliveryCraft SQL payload in column name, location param, or export path
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ExploitInvoke dbapi()/write/to_csv() to concatenate into generated SQL
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ExecutionInjected statement executes with session privileges
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PersistRedirect COPY INTO or read cross-tenant data
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ImpactExfiltrate data or compromise source database
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 an authenticated Snowflake session using Snowpark Python (PR:L confirmed by CVSS), plus one of three concrete triggers named in the description: (1) DataFrameReader.dbapi() reading from a source database whose column names the attacker can influence, (2) a specially crafted location parameter supplied to a DataFrameWriter write method to redirect COPY INTO to an arbitrary source query, or (3) a backslash-single-quote sequence embedded in an export path passed to DataFrame.to_csv() to defeat the normalize_path() sanitizer. Limiting factors: the attacker must already hold low-privilege access and be able to place their payload into one of these specific parameters or data sources, and the target must run snowpark-python below 1.53.0 - there is no unauthenticated or default-configuration path, and no user interaction is required beyond the vulnerable pipeline executing. |
| Impact | The supplied CVSS 3.1 vector (AV:N/AC:L/PR:L/UI:N/S:C, C:H/I:H/A:N, score 9.6) indicates a network-reachable, low-complexity attack requiring only low privileges, with a scope change reflecting cross-tenant / source-database impact and high confidentiality and integrity loss but no availability impact. Because the vector contains PR:L this is an authenticated attack - not a pre-auth internet-facing scenario; the attacker must already hold a low-privilege Snowflake identity or control input that a Snowpark job ingests (e.g. attacker-controlled source database column names). No EPSS score was provided, there is no KEV listing (no public exploit identified at time of analysis), and no POC reference, so real-world exploitation signal is currently absent despite the high CVSS. The single reference is only the project CHANGELOG, so exploitation prerequisites are inferred from the description rather than confirmed by an independent advisory; treat the 9.6 as a credible worst case for multi-tenant Snowflake data pipelines but verify actual API usage and exposure before emergency prioritization. |
| Exploit ScenarioDerived | A low-privilege user in a shared Snowflake account (or an attacker who controls a source database that a Snowpark job ingests) crafts a malicious column name or a location/export-path parameter containing SQL, then triggers a Snowpark read/write that concatenates it into generated SQL. The injected statement runs with the session's privileges, allowing the attacker to redirect a COPY INTO or read data belonging to other tenants. No public POC is referenced, but the low attack complexity and network vector make weaponization straightforward for an authenticated actor. |
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Alert meAnalysisAIv1 – Jul 08, 2026
SQL injection in the Snowflake Snowpark Python SDK (snowpark-python) before 1.53.0 lets an authenticated low-privilege Snowflake user execute SQL beyond their authorization scope, enabling cross-tenant data theft and source-database compromise. Three distinct injection points are involved - malicious source column names via DataFrameReader.dbapi(), a crafted location parameter that redirects COPY INTO in DataFrameWriter, and a backslash-single-quote bypass of normalize_path() in DataFrame.to_csv(). Rated CVSS 9.6 with a scope change; no public exploit identified at time of analysis and it is not listed in CISA KEV.
RemediationAI
Vendor-released patch: 1.53.0 - upgrade snowpark-python to 1.53.0 or later (pip install --upgrade snowpark-python) and rebuild any pipelines that pin an older version, per the changelog at https://github.com/snowflakedb/snowpark-python/blob/main/CHANGELOG.md. Until you can upgrade, reduce exposure by not passing untrusted or attacker-influenceable values into the vulnerable APIs: avoid DataFrameReader.dbapi() against source databases whose schema/column names you do not fully control, validate or allowlist the location parameter passed to DataFrameWriter write methods rather than accepting arbitrary input, and constrain export paths given to DataFrame.to_csv() to a fixed, sanitized directory so a backslash-single-quote sequence cannot reach normalize_path(). The trade-off is reduced flexibility in dynamic ingestion/export flows, and these workarounds do not fully close the injection classes, so they are stopgaps only; additionally enforce least-privilege on the Snowflake roles used by Snowpark sessions to limit the blast radius of any residual injection.
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
Snowpark is Snowflake's client-side developer framework; the Python SDK generates SQL that is pushed down and executed inside the Snowflake compute engine. The root cause is CWE-89 (improper neutralization of SQL elements): user-influenced values are concatenated into generated SQL rather than parameterized or safely quoted. Specifically, externally sourced database column names read through DataFrameReader.dbapi() are trusted, the location argument to DataFrameWriter write methods is not validated before being embedded in a COPY INTO source clause, and normalize_path() fails to neutralize a backslash-escaped single quote (\') so an attacker can break out of the quoted export path in DataFrame.to_csv(). Because the generated SQL executes with the session's Snowflake privileges and can reach external/source databases, injection crosses trust boundaries between the SDK user, the Snowflake account, and connected source systems.
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Severity by source
AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:N
Authenticated low-privilege user (PR:L) injects SQL over the network (AV:N/AC:L); cross-tenant/source-database reach is a scope change (S:C) with high confidentiality and integrity loss but no availability impact.
Primary rating from Vendor (412d305a-227d-44f9-a262-a31ba44f2aea).
CVSS VectorVendor: 412d305a-227d-44f9-a262-a31ba44f2aea
Lifecycle Timeline
1DescriptionCVE.org
SQL injection vulnerabilities in the Snowflake Snowpark Python SDK (snowpark-python) versions prior to 1.53.0 could allow authenticated low-privilege users to execute SQL beyond their authorization scope. An attacker could exploit these vulnerabilities by embedding SQL payloads in source database column names to escalate privileges via the DataFrameReader.dbapi() API by supplying a specially crafted location parameter to DataFrameWriter write methods to redirect a COPY INTO to an arbitrary source query, or by including a backslash-single-quote sequence in an export path to defeat the normalize_path() sanitizer and inject SQL via DataFrame.to_csv(). Successful exploitation may result in source database compromise, unauthorized cross-tenant data exfiltration, or unauthorized read of Snowflake account data.
Articles & Coverage 2
Executive ViewAI
Snowflake Snowpark Python SDK before version 1.53.0 contains a SQL injection vulnerability enabling authenticated users to bypass authorization controls and access data beyond their assigned permissions, creating material risk of unauthorized data exfiltration and cross-tenant exposure. Organizations using vulnerable SDK versions face data breach exposure from insider threats or compromised service accounts. Immediate inventory and mitigation are required given the high-value nature of Snowflake data environments.
No vendor-released patch identified at time of analysis. Interim mitigations: (1) Restrict Snowpark SDK usage to trusted, isolated applications with minimal network exposure; (2) Enforce least-privilege Snowflake user accounts with minimal default permissions; (3) Implement network segmentation to limit Snowflake connectivity; (4) Enable comprehensive Snowflake query auditing and alerting to detect anomalous SQL patterns; (5) Monitor Snowflake security advisories and prepare immediate deployment procedures for patch release.
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.
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EPSS
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Exploit-DB