Vulnerabilities

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Dependencies

13

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high severity

Insufficient Verification of Data Authenticity

  • Vulnerable module: cryptography
  • Introduced through: cryptography@45.0.7

Detailed paths

  • Introduced through: jarun/Buku@jarun/Buku cryptography@45.0.7
    Remediation: Upgrade to cryptography@46.0.5.

Overview

Affected versions of this package are vulnerable to Insufficient Verification of Data Authenticity in public key functions public_key_from_numbers, EllipticCurvePublicNumbers.public_key, load_der_public_key, and load_pem_public_key, which may reveal bits from a private key when provided with a malicious public key as input. When the application is using sect* binary curves for verification - which is a rare use case - these functions do not verify that the provided point belongs to the expected prime-order subgroup of the curve. An attacker can thus expose partial private keys or forge signatures.

Remediation

Upgrade cryptography to version 46.0.5 or higher.

References

high severity

Improper Control of Generation of Code ('Code Injection')

  • Vulnerable module: setuptools
  • Introduced through: setuptools@40.5.0

Detailed paths

  • Introduced through: jarun/Buku@jarun/Buku setuptools@40.5.0
    Remediation: 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

Directory Traversal

  • Vulnerable module: setuptools
  • Introduced through: setuptools@40.5.0

Detailed paths

  • Introduced through: jarun/Buku@jarun/Buku setuptools@40.5.0
    Remediation: 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

Improper Certificate Validation

  • Vulnerable module: cryptography
  • Introduced through: cryptography@45.0.7

Detailed paths

  • Introduced through: jarun/Buku@jarun/Buku cryptography@45.0.7
    Remediation: Upgrade to cryptography@46.0.6.

Overview

Affected versions of this package are vulnerable to Improper Certificate Validation through the NameChain DNS verification logic in src/rust/cryptography-x509-verification. An attacker can make a peer name, such as bar.example.com, validate against a wildcard leaf certificate like *.example.com even when an issuing certificate in the chain excludes that DNS subtree, causing improper certificate acceptance.

Notes

  • The flaw affects X.509 path validation when DNS name constraints are present, and the leaf certificate uses a wildcard DNS SAN.
  • The maintainers note that ordinary X.509 topologies, including those used by the Web PKI, are not affected, and exploitation requires an uncommon certificate hierarchy.

Remediation

Upgrade cryptography to version 46.0.6 or higher.

References

medium severity

Out-of-bounds Write

  • Vulnerable module: cryptography
  • Introduced through: cryptography@45.0.7

Detailed paths

  • Introduced through: jarun/Buku@jarun/Buku cryptography@45.0.7
    Remediation: Upgrade to cryptography@46.0.7.

Overview

Affected versions of this package are vulnerable to Out-of-bounds Write in the update function when non-contiguous buffers are provided as input. An attacker can cause memory corruption or unintended behavior by supplying specially crafted non-contiguous buffers to APIs that accept Python buffers.

Note: This is only exploitable if the Python version is greater than 3.11.

Remediation

Upgrade cryptography to version 46.0.7 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: setuptools
  • Introduced through: setuptools@40.5.0

Detailed paths

  • Introduced through: jarun/Buku@jarun/Buku setuptools@40.5.0
    Remediation: 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:

  • 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.

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

MPL-2.0 license

  • Module: certifi
  • Introduced through: certifi@2026.4.22

Detailed paths

  • Introduced through: jarun/Buku@jarun/Buku certifi@2026.4.22

MPL-2.0 license