GHSA-2r5m-76wx-56gx BIT-airflow-2026-45360 CVE-2026-45360 PYSEC-2026-186
Apache Airflow Vulnerable to Deserialization of Untrusted Data
- Severity
- 7.3 / 10
- High · CVSS 3.1
- Exploit chance (EPSS)
- 0.68%
- Chance of exploitation in the next 30 days. Higher than 52.24% of scored vulnerabilities.
- Known exploited
- No
- Not in CISA's catalog
- Weakness
- CWE-502 Deserialization of Untrusted Data
- Fix
3.2.2- Upgrade apache-airflow to this version or later
Description
Apache Airflow's scheduler-side deadline-reference decoder (SerializedCustomReference.deserialize_reference) imported and dispatched arbitrary class paths drawn from DAG-author-controlled serialized state without an allowlist or plugin-registry gate. A DAG author whose code reaches the scheduler — the default on single-host deployments where the DAG bundle is importable from the scheduler process — could embed a custom DeadlineReference whose serialized form named an attacker-controlled module path, causing the scheduler to import_string(...) and instantiate that class with a live SQLAlchemy session attached. Affects deployments where DAG-author code is less trusted than the scheduler process. Users are advised to upgrade to apache-airflow 3.2.2 or later.
Affected versions
PyPI
| Package | Vulnerable | Fixed in |
|---|---|---|
| apache-airflow | >= 3.2.0, < 3.2.2 |
3.2.2 |
| apache-airflow | < 3.2.2 |
3.2.2 |
How to fix
Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.
apache-airflow PyPI → 3.2.2
- pip
pip install --upgrade "apache-airflow>=3.2.2"- poetry
poetry add "apache-airflow>=3.2.2"- uv
uv add "apache-airflow>=3.2.2"
Severity breakdown
CVSS 3.1 7.3
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L
- Attack vector
- Network
- Attack complexity
- Low
- Privileges required
- None
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- Low
- Integrity
- Low
- Availability
- Low
Weakness
CWE-502: Deserialization of Untrusted Data
The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.
How to prevent it
- Architecture and Design, Implementation: If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.
- Implementation: When deserializing data, populate a new object rather than just deserializing. The result is that the data flows through safe input validation and that the functions are safe.
- Implementation: Explicitly define a final object() to prevent deserialization.
- Architecture and Design, Implementation: Make fields transient to protect them from deserialization. An attempt to serialize and then deserialize a class containing transient fields will result in NULLs where the transient data should be. This is an excellent way to prevent time, environment-based, or sensitive variables from being carried over and used improperly.
- Implementation: Avoid having unnecessary types or gadgets (a sequence of instances and method invocations that can self-execute during the deserialization process, often found in libraries) available that can be leveraged for malicious ends. This limits the potential for unintended or unauthorized types and gadgets to be leveraged by the attacker. Add only acceptable classes to an allowlist. Note: new gadgets are constantly being discovered, so this alone is not a sufficient mitigation.
- Architecture and Design, Implementation: Employ cryptography of the data or code for protection. However, it's important to note that it would still be client-side security. This is risky because if the client is compromised then the security implemented on the client (the cryptography) can be bypassed.
- Operation: Use an application firewall that can detect attacks against this weakness. It can be beneficial in cases in which the code cannot be fixed (because it is controlled by a third party), as an emergency prevention measure while more comprehensive software assurance measures are applied, or to provide defense in depth [REF-1481].
References
Advisories
Packages
Other links
Timeline
- Published
- Last updated by the source
- Latest EPSS score
Related advisories
| Advisory | Severity | Why it's related |
|---|---|---|
| CVE-2020-13927 Authentication bypass in Apache Airflow | Critical Known exploited | Also affects apache-airflow |
| CVE-2020-11978 Remote code execution (RCE) in Apache Airflow | High Known exploited | Also affects apache-airflow |
| PYSEC-2026-3990 Apache Airflow: the Core API logout endpoint revokes only a session token presented as the _token cookie. | Critical | Also affects apache-airflow |
| PYSEC-2026-3989 When a request to the Airflow core API carries both a session cookie and an explicit `Authorization: Bearer` token, Airflow resolves the caller from the cookie… | Medium | Also affects apache-airflow |
| PYSEC-2026-3988 Apache Airflow's `/assets/events` API returned asset events for every Dag in the deployment, with no filter restricting them to the Dags the caller is… | Medium | Also affects apache-airflow |
| GHSA-5247-m8w9-2v4m Apache Airflow missing team context permits cross-team Dag actions and XCom reads | Medium | Also affects apache-airflow |
| GHSA-f3c2-j7g8-vpp8 Apache Airflow Task SDK fails to mask list-shaped JSON Variables | Medium | Also affects apache-airflow |
| GHSA-cjv4-7hp2-2x9h Apache Airflow bulk endpoints log Variable and Connection secrets in cleartext | Medium | Also affects apache-airflow |
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