Raw vector
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/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2026-15183 is a critical-severity SQL Injection (CWE-89) vulnerability in Snowflake Spark Connector (inferred from references). Its CVSS base score is 9.2 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Proxy (T1090); ranked at the 11th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to AC-16 (Security and Privacy Attributes) and AC-4 (Information Flow Enforcement) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-43644
Vulnerability Data
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…
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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.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V3.2.1V3.5.1V3.5.3V3.5.8
Mitigating Controls (NIST 800-53 r5) AI
Associating and preserving security attributes such as original source identity prevents the loss of provenance that creates the confused deputy.
Information flow enforcement requires preserving and checking source attributes before forwarding requests outside the trust boundary.
Developer testing and evaluation can discover SQLi flaws before deployment but does not stop their introduction.
Input validation directly stops untrusted data from reaching SQL query construction without neutralization.
Access enforcement directly stops a component from acting on forwarded requests without verifying original source authorizations.
Secure engineering principles require parameterized queries and input sanitization that structurally eliminate SQLi.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Proper conveyance and verification of original identity assertions directly prevents loss of request source when forwarding.
Secure SDLC practices directly target injection flaws during coding and review so largely prevent CWE-89 introduction, yet the single broad outcome leaves residual risk from incomplete neutralization techniques or missed edge cases.
Runtime monitoring of web applications and services can detect anomalous outbound requests indicative of SSRF.
Vulnerability identification processes can discover and record SSRF flaws in web applications.
Enforcing least-privilege authorizations on forwarded requests reduces confused-deputy abuse even if source identity is lost.
Training raises developer awareness of SQLi risks and can reduce introduction likelihood (partial) but removes none of the actual coding flaw's risk by itself since technical neutralization is still required.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
The same secure-coding and static-analysis activities surface missing neutralization of SQL metacharacters before the system is accepted.
Access-control rules can limit which upstream identities may cause the product to act on their behalf, reducing confused-deputy risk.
Proper identity management ensures the original requester identity is preserved and validated before the product forwards requests.
Explicit access-rights assignment can restrict the product’s ability to act as an unintended proxy for external actors.
Early warnings and shared best-practice information help organizations apply the latest remediation techniques against SQL-injection vulnerabilities.
Threat-intelligence feeds that surface new SQL-injection campaigns enable rapid updates to query-construction defenses and detection signatures before exploitation occurs.