Your RSA-2048 keys break in 2030. Find every one of them before attackers do.
🐍 PyPI

GHSA-5g2w-9f8g-g5q7

MEDIUM

Apache Airflow UI Exposes DAG Import Errors to Unauthorized Authenticated Users

Also known asBIT-airflow-2026-24098CVE-2026-24098PYSEC-2026-12
Published
Feb 9, 2026
Updated
May 20, 2026
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed

EPSS Exploitation Probability

via FIRST.org ↗
0.7%probability of exploitation in next 30 days
Lower Risk50th percentile+0.72%
0.00%0.41%0.83%1.24%0.0%0.0%0.0%0.0%0.7%Mar 26May 26Jun 26

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

Blast Radius

1 pkg affected
🐍apache-airflow

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Impact

Exposure of Sensitive Information:

An information disclosure vulnerability exists in the Apache Airflow UI that allows authenticated users to view Import Errors for DAGs they are not authorized to access.

In affected versions, the Import Errors view does not correctly filter errors based on granular DAG permissions. This means a user with access to only DAG_A can view import errors generated by DAG_B, DAG_C, or system-level DAGs. These error logs often contain file paths, code snippets, or stack traces that reveal the internal structure and logic of restricted DAGs.

Patches

Users should upgrade to Apache Airflow 3.1.7 or later. This version strictly enforces DAG-level permissions on the Import Errors view.

Workarounds

There are no known workarounds other than upgrading.

Resources

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIapache-airflowall versions3.1.7

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for apache-airflow. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.

  2. Fix

    Update apache-airflow to 3.1.7 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-5g2w-9f8g-g5q7 is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 pinpoints whether GHSA-5g2w-9f8g-g5q7 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.

Tailored to GHSA-5g2w-9f8g-g5q7. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

### Impact **Exposure of Sensitive Information:** An information disclosure vulnerability exists in the Apache Airflow UI that allows authenticated users to view `Import Errors` for DAGs they are not authorized to access. In affected versions, the **Import Errors** view does not correctly filter errors based on granular DAG permissions. This means a user with access to only `DAG_A` can view import errors generated by `DAG_B`, `DAG_C`, or system-level DAGs. These error logs often contain file paths, code snippets, or stack traces that reveal the internal structure and logic of restricted DAG
O3 Security · Impact-Aware SCA

Is GHSA-5g2w-9f8g-g5q7 in your dependencies?

O3 detects GHSA-5g2w-9f8g-g5q7 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.