Vulnerabilities

24 via 56 paths

Dependencies

48

Source

GitHub

Find, fix and prevent vulnerabilities in your code.

Issue type
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Severity
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Status
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critical severity

SQL Injection

  • Vulnerable module: pg8000
  • Introduced through: pg8000@1.29.8

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import pg8000@1.29.8
    Remediation: Upgrade to pg8000@1.31.5.

Overview

pg8000 is a PostgreSQL interface library

Affected versions of this package are vulnerable to SQL Injection via the literal function. An attacker can execute arbitrary SQL commands by supplying a specially crafted Python list as input.

Remediation

Upgrade pg8000 to version 1.31.5 or higher.

References

critical severity

Time-of-check Time-of-use (TOCTOU) Race Condition

  • Vulnerable module: waitress
  • Introduced through: waitress@2.1.2

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import waitress@2.1.2
    Remediation: Upgrade to waitress@3.0.1.

Overview

waitress is a production-quality pure-Python WSGI server with very acceptable performance.

Affected versions of this package are vulnerable to Time-of-check Time-of-use (TOCTOU) Race Condition in HTTP pipelining when handling an invalid initial request. An attacker can exploit this vulnerability to process unauthorized requests by sending a specially crafted sequence of requests where the first request is exactly recv_bytes long and followed by a secondary request using HTTP pipelining.

Workaround

This vulnerability can be mitigated by disabling channel_request_lookahead, which is set to 0 by default, thus disabling this feature.

Remediation

Upgrade waitress to version 3.0.1 or higher.

References

high severity

Improper Handling of Case Sensitivity

  • Vulnerable module: flask-cors
  • Introduced through: flask-cors@5.0.0

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cors@5.0.0
    Remediation: Upgrade to flask-cors@6.0.0.

Overview

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

Affected versions of this package are vulnerable to Improper Handling of Case Sensitivity in the try_match() function. An attacker can access restricted paths and potentially expose sensitive data by exploiting the case insensitivity in path matching.

Remediation

Upgrade Flask-Cors to version 6.0.0 or higher.

References

high severity

XML External Entity (XXE) Injection

  • Vulnerable module: lxml
  • Introduced through: lxml@5.4.0

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import lxml@5.4.0
    Remediation: Upgrade to lxml@6.1.0.

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

high severity
new

Directory Traversal

  • Vulnerable module: mako
  • Introduced through: alembic@1.12.1

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import alembic@1.12.1 mako@1.2.4
    Remediation: Upgrade to alembic@1.12.1.

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

high severity

Missing Release of Resource after Effective Lifetime

  • Vulnerable module: waitress
  • Introduced through: waitress@2.1.2

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import waitress@2.1.2
    Remediation: Upgrade to waitress@3.0.1.

Overview

waitress is a production-quality pure-Python WSGI server with very acceptable performance.

Affected versions of this package are vulnerable to Missing Release of Resource after Effective Lifetime due to the improper handling of socket connections when a remote client prematurely closes the connection, before waitress has had the opportunity to call getpeername(). An attacker can exhaust system resources and cause high CPU usage by repeatedly opening and closing connections, leading to a busy-loop in the server's socket handling.

Remediation

Upgrade waitress to version 3.0.1 or higher.

References

high severity

Directory Traversal

  • Vulnerable module: mako
  • Introduced through: alembic@1.12.1

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import alembic@1.12.1 mako@1.2.4
    Remediation: Upgrade to alembic@1.12.1.

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

high severity

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

  • Vulnerable module: setuptools
  • Introduced through: setuptools@68.0.0 and iterfzf@0.5.0.20.0

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import setuptools@68.0.0
    Remediation: Upgrade to setuptools@70.0.0.
  • Introduced through: debrief/pepys-import@debrief/pepys-import iterfzf@0.5.0.20.0 setuptools@68.0.0
    Remediation: Upgrade to iterfzf@1.0.0.42.0.

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

high severity

Remote Code Execution (RCE)

  • Vulnerable module: werkzeug
  • Introduced through: flask@2.2.5, flask-cachebuster@1.0.0 and others

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask@2.2.5.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cachebuster@1.0.0 flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask-cachebuster@1.0.0.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cors@5.0.0 flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask-cors@5.0.0.

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

high severity

GPL-3.0 license

  • Module: iterfzf
  • Introduced through: iterfzf@0.5.0.20.0

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import iterfzf@0.5.0.20.0

GPL-3.0 license

medium severity

Improper Verification of Source of a Communication Channel

  • Vulnerable module: flask-cors
  • Introduced through: flask-cors@5.0.0

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cors@5.0.0
    Remediation: Upgrade to flask-cors@6.0.0.

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

medium severity

Origin Validation Error

  • Vulnerable module: flask-cors
  • Introduced through: flask-cors@5.0.0

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cors@5.0.0
    Remediation: Upgrade to flask-cors@6.0.0.

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

medium severity

Allocation of Resources Without Limits or Throttling

  • Vulnerable module: werkzeug
  • Introduced through: flask@2.2.5, flask-cachebuster@1.0.0 and others

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask@2.2.5.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cachebuster@1.0.0 flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask-cachebuster@1.0.0.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cors@5.0.0 flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask-cors@5.0.0.

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

medium severity

Infinite loop

  • Vulnerable module: zipp
  • Introduced through: alembic@1.12.1, flask@2.2.5 and others

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import alembic@1.12.1 importlib-metadata@6.7.0 zipp@3.15.0
    Remediation: Upgrade to alembic@1.12.1.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask@2.2.5 importlib-metadata@6.7.0 zipp@3.15.0
    Remediation: Upgrade to flask@2.3.3.
  • Introduced through: debrief/pepys-import@debrief/pepys-import pg8000@1.29.8 importlib-metadata@6.7.0 zipp@3.15.0
    Remediation: Upgrade to pg8000@1.30.1.
  • Introduced through: debrief/pepys-import@debrief/pepys-import pint@0.18 importlib-metadata@6.7.0 zipp@3.15.0
    Remediation: Upgrade to pint@0.19.
  • Introduced through: debrief/pepys-import@debrief/pepys-import tqdm@4.67.3 importlib-metadata@6.7.0 zipp@3.15.0
    Remediation: Upgrade to tqdm@4.67.3.
  • Introduced through: debrief/pepys-import@debrief/pepys-import alembic@1.12.1 importlib-resources@5.12.0 zipp@3.15.0
    Remediation: Upgrade to alembic@1.12.1.
  • Introduced through: debrief/pepys-import@debrief/pepys-import alembic@1.12.1 mako@1.2.4 importlib-metadata@6.7.0 zipp@3.15.0
    Remediation: Upgrade to alembic@1.12.1.
  • Introduced through: debrief/pepys-import@debrief/pepys-import alembic@1.12.1 sqlalchemy@2.0.50 importlib-metadata@6.7.0 zipp@3.15.0
  • Introduced through: debrief/pepys-import@debrief/pepys-import geoalchemy2@0.17.1 sqlalchemy@2.0.50 importlib-metadata@6.7.0 zipp@3.15.0
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask@2.2.5 click@8.1.8 importlib-metadata@6.7.0 zipp@3.15.0
    Remediation: Upgrade to flask@2.3.3.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cachebuster@1.0.0 flask@2.2.5 importlib-metadata@6.7.0 zipp@3.15.0
    Remediation: Upgrade to flask-cachebuster@1.0.0.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cors@5.0.0 flask@2.2.5 importlib-metadata@6.7.0 zipp@3.15.0
    Remediation: Upgrade to flask-cors@5.0.0.
  • Introduced through: debrief/pepys-import@debrief/pepys-import pg8000@1.29.8 scramp@1.4.4 importlib-metadata@6.7.0 zipp@3.15.0
    Remediation: Upgrade to pg8000@1.30.2.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cachebuster@1.0.0 flask@2.2.5 click@8.1.8 importlib-metadata@6.7.0 zipp@3.15.0
    Remediation: Upgrade to flask-cachebuster@1.0.0.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cors@5.0.0 flask@2.2.5 click@8.1.8 importlib-metadata@6.7.0 zipp@3.15.0
    Remediation: Upgrade to flask-cors@5.0.0.

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

medium severity

Directory Traversal

  • Vulnerable module: setuptools
  • Introduced through: setuptools@68.0.0 and iterfzf@0.5.0.20.0

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import setuptools@68.0.0
    Remediation: Upgrade to setuptools@78.1.1.
  • Introduced through: debrief/pepys-import@debrief/pepys-import iterfzf@0.5.0.20.0 setuptools@68.0.0
    Remediation: Upgrade to iterfzf@1.0.0.42.0.

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

Inefficient Algorithmic Complexity

  • Vulnerable module: werkzeug
  • Introduced through: flask@2.2.5, flask-cachebuster@1.0.0 and others

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask@2.2.5.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cachebuster@1.0.0 flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask-cachebuster@1.0.0.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cors@5.0.0 flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask-cors@5.0.0.

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

medium severity

Directory Traversal

  • Vulnerable module: werkzeug
  • Introduced through: flask@2.2.5, flask-cachebuster@1.0.0 and others

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask@2.2.5.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cachebuster@1.0.0 flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask-cachebuster@1.0.0.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cors@5.0.0 flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask-cors@5.0.0.

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

medium severity

Improper Handling of Windows Device Names

  • Vulnerable module: werkzeug
  • Introduced through: flask@2.2.5, flask-cachebuster@1.0.0 and others

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask@2.2.5.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cachebuster@1.0.0 flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask-cachebuster@1.0.0.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cors@5.0.0 flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask-cors@5.0.0.

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

medium severity

Improper Handling of Windows Device Names

  • Vulnerable module: werkzeug
  • Introduced through: flask@2.2.5, flask-cachebuster@1.0.0 and others

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask@2.2.5.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cachebuster@1.0.0 flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask-cachebuster@1.0.0.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cors@5.0.0 flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask-cors@5.0.0.

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

medium severity

Improper Handling of Windows Device Names

  • Vulnerable module: werkzeug
  • Introduced through: flask@2.2.5, flask-cachebuster@1.0.0 and others

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask@2.2.5.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cachebuster@1.0.0 flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask-cachebuster@1.0.0.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cors@5.0.0 flask@2.2.5 werkzeug@2.2.3
    Remediation: Upgrade to flask-cors@5.0.0.

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

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: pygments
  • Introduced through: pygments@2.17.2

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import pygments@2.17.2
    Remediation: Upgrade to pygments@2.20.0.

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the AdlLexer class in the archetype.py file. A user can cause excessive resource consumption.

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 pygments to version 2.20.0 or higher.

References

low severity

Buffer Overflow

  • Vulnerable module: numpy
  • Introduced through: shapely@2.0.7

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import shapely@2.0.7 numpy@1.21.3
    Remediation: Upgrade to shapely@2.0.7.

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

Denial of Service (DoS)

  • Vulnerable module: numpy
  • Introduced through: shapely@2.0.7

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import shapely@2.0.7 numpy@1.21.3
    Remediation: Upgrade to shapely@2.0.7.

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 ws package

Remediation

Upgrade numpy to version 1.22.0rc1 or higher.

References

low severity

NULL Pointer Dereference

  • Vulnerable module: numpy
  • Introduced through: shapely@2.0.7

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import shapely@2.0.7 numpy@1.21.3
    Remediation: Upgrade to shapely@2.0.7.

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.

References

low severity

Use of Cache Containing Sensitive Information

  • Vulnerable module: flask
  • Introduced through: flask@2.2.5, flask-cachebuster@1.0.0 and others

Detailed paths

  • Introduced through: debrief/pepys-import@debrief/pepys-import flask@2.2.5
    Remediation: Upgrade to flask@3.1.3.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cachebuster@1.0.0 flask@2.2.5
    Remediation: Upgrade to flask-cachebuster@1.0.0.
  • Introduced through: debrief/pepys-import@debrief/pepys-import flask-cors@5.0.0 flask@2.2.5
    Remediation: Upgrade to flask-cors@5.0.0.

Overview

Affected versions of this package are vulnerable to Use of Cache Containing Sensitive Information in the session object. An attacker can cause sensitive user-specific responses to be cached and served to other users by leveraging a caching proxy that does not ignore responses with cookies, when the application does not set a Cache-Control header and accesses the session only for keys without mutating or accessing values.

Note:

This is only exploitable if the application is hosted behind a caching proxy that does not ignore responses with cookies, does not set a Cache-Control header to indicate that a page is private or should not be cached, and accesses the session in a way that does not access the values, only the keys, and does not mutate the session.

Remediation

Upgrade flask to version 3.1.3 or higher.

References