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CVE-2025-69219 affects Apache Airflow Providers HTTP (apache-airflow-providers-http) versions 5.1.0 up to but not including 6.0.0. The issue is unsafe deserialization (pickle) where an attacker with direct access to the Airflow metadata database can craft a malicious database entry that is later deserialized/processed in a way that results in code execution on the Airflow Triggerer, effectively granting the attacker permissions equivalent to a DAG author.
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2 valid exploits after Mallory filtered fakes, detection scripts, and README-only repos.
Repository contains a proof-of-concept exploit for CVE-2025-69219 affecting Apache Airflow's HTTP provider (apache-airflow-providers-http >=5.1.0,<6.0.0). The vulnerability is unsafe deserialization: HttpOperator.execute_complete() base64-decodes and pickle.loads() an event['response'] value that originates from the Airflow metadata database (TriggerEvent). An attacker with DB write access can replace that stored response with a malicious pickle that leverages __reduce__ to call os.system, yielding RCE in the Triggerer worker context. Structure: - README.md: Detailed vulnerability write-up, affected/fixed versions, root cause, patch explanation (switch to JSON HttpResponseSerializer), and usage instructions. - poc.py: Standalone Python PoC with two modes: 1) local (default): simulates the vulnerable sink in-process by constructing a base64-encoded pickle payload and calling pickle.loads(base64.standard_b64decode(...)), executing the supplied command. 2) dag: generates a deployable Airflow DAG file (default output cve_2025_69219_poc_dag.py) that instantiates a deferrable HttpOperator and directly calls execute_complete with a crafted event to trigger the sink. Exploit capabilities: - Arbitrary command execution via os.system during pickle deserialization. - Payload is user-controlled via --cmd; can be used for simple commands or a reverse shell command (example shown to ATTACKER_IP:4444). No direct network exploitation is implemented in code (no HTTP requests to a target); the real-world vector is database poisoning of TriggerEvent data that the Triggerer later deserializes.
Repository contains a minimal proof-of-concept for CVE-2025-69219 targeting Apache Airflow. Structure: (1) README.md with steps to deploy the PoC by copying poc.py into the Airflow DAGs directory, triggering the DAG from the Airflow UI, and checking task logs; (2) poc.py defining an Airflow DAG named 'poc' with a single PythonOperator. Exploit mechanics: poc.py creates a malicious Python object (class Exploit) whose __reduce__ method returns (os.system, ('id',)). The simulate_attack() function pickles this object, base64-encodes it, then instantiates an HttpOperator and directly calls operator.execute_complete(...) with a crafted event dict containing the attacker-controlled 'response' field set to the base64 payload and status 'success'. If the targeted Airflow/provider code path unsafely base64-decodes and pickle-deserializes this field, deserialization triggers os.system('id'), yielding code execution in the Airflow process context. No external network callbacks, C2, or reverse shell are included; the only command executed is `id`, with expected output observable in task logs.
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A code-execution vulnerability in apache-airflow-providers-http allows a user with direct database access to craft an entry that executes code on the Airflow Triggerer with DAG-author permissions. The advisory considers the likelihood of harm low because direct database access is unusual and not recommended. The plugin rates the vulnerability High, with a CVSS v3 base score of 8.8, and recommends upgrading to version 6.0.0 or later.
A vulnerability where a user with direct database access can craft a malicious database entry that leads to code execution on the Apache Airflow Triggerer component, effectively granting permissions equivalent to a DAG Author.
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