Skip to content

GHSA-8prw-8m6x-8w6f BIT-airflow-2026-58076 CVE-2026-58076 PYSEC-2026-3991

Apache Airflow exception-node deserialization permits arbitrary callable execution

High PyPI
Severity
8.8 / 10
High · CVSS 3.1
Exploit chance (EPSS)
0.48%
Chance of exploitation in the next 30 days. Higher than 41.72% of scored vulnerabilities.
Known exploited
No
Not in CISA's catalog
Weakness
CWE-502 Deserialization of Untrusted Data
Fix
3.3.1
Upgrade apache-airflow to this version or later

Description

Apache Airflow's serialization layer reconstructed exception nodes by calling import_string() on a class name taken from the serialized blob and instantiating it with arguments from the same blob, with no restriction on what could be imported. An operator's executor_config reaches that branch, so a Dag author could place a value there that causes an arbitrary callable to be imported and invoked -- for example subprocess.check_output, or builtins.eval on the builtins-prefixed variant. The code runs in the Scheduler, which reconstructs serialized Dags in its normal loop with no request involved, and in the API server, on any authenticated read of the Dag such as GET /api/v2/dags/{dag_id}/details. Both are components the Airflow security model states must never execute Dag-author code, and both hold the metadata database credentials and the JWT signing secret. No non-default configuration is required. This is a different sink from CVE-2026-33264, which covered only the trigger branch of the same deserializer: deployments that upgraded in response to that advisory are still affected through the exception branch and must upgrade again. Users are advised to upgrade to apache-airflow 3.3.1 or later, which restricts the imported class to a subclass of BaseException.

Affected versions

PyPI

PackageVulnerableFixed in
apache-airflow
>= 3.3.0, < 3.3.1
3.3.1

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 → 3.3.1

pip
pip install --upgrade "apache-airflow>=3.3.1"
poetry
poetry add "apache-airflow>=3.3.1"
uv
uv add "apache-airflow>=3.3.1"

Severity breakdown

CVSS 3.1 8.8

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Attack vector
Network
Attack complexity
Low
Privileges required
Low
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

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

Timeline

  1. Published
  2. Last updated by the source
  3. Latest EPSS score
AdvisorySeverityWhy 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
Is this in your code?

MergeHarbor checks every repository's dependencies against this database, ranks what matters by exploitability and reachability, routes it to the owning team and opens the fix pull request.

Check your repos with MergeHarbor