List of software quality issues with the number of affected components.
category ALL
Policies
Info
Count
Category
Detected presence of severe vulnerabilities with active exploitation.
Causes risk: actively exploited vulnerabilities
1
vulnerabilities
Problem
Software composition analysis has identified a component with one or more known severe vulnerabilities. Available threat intelligence telemetry has confirmed that the reported high or critical severity vulnerabilities are actively being exploited by malicious actors.Prevalence in PyPI community
38 packages
found in
Top 100
303 packages
found in
Top 1k
2611 packages
found in
Top 10k
103184 packages
in community
Next steps
We strongly advise updating the component to the latest version.
If the update can't resolve the issue, create a plan to isolate or replace the affected component.
Detected presence of critical severity vulnerabilities.
Causes risk: critical severity vulnerabilities
1
vulnerabilities
Problem
Software composition analysis has identified a component with one or more known vulnerabilities. Based on the CVSS scoring, these vulnerabilities have been marked as critical severity.Prevalence in PyPI community
25 packages
found in
Top 100
212 packages
found in
Top 1k
1951 packages
found in
Top 10k
77976 packages
in community
Next steps
Perform impact analysis for the reported CVEs.
We strongly advise updating the component to the latest version.
If the update can't resolve the issue, create a plan to isolate or replace the affected component.
Detected presence of high severity vulnerabilities.
Causes risk: high severity vulnerabilities
1
vulnerabilities
Problem
Software composition analysis has identified a component with one or more known vulnerabilities. Based on the CVSS scoring, these vulnerabilities have been marked as high severity.Prevalence in PyPI community
50 packages
found in
Top 100
352 packages
found in
Top 1k
2858 packages
found in
Top 10k
108771 packages
in community
Next steps
Perform impact analysis for the reported CVEs.
Update the component to the latest version.
If the update can't resolve the issue, create a plan to isolate or replace the affected component.
Problem
Uniform Resource Locators (URLs) are structured addresses that point to locations and assets on the internet. URLs allow software developers to build complex applications that exchange data with servers that can be hosted in multiple geographical regions. URLs can commonly be found embedded in documentation, configuration files, source code and compiled binaries. One or more embedded URLs were discovered to link to raw files hosted on GitHub. Attackers often abuse popular web services to host malicious payloads. Since code-sharing services URLs are typically allowed by security solutions, using them for payload delivery increases the odds that the malicious code will reach the user. While the presence of code-sharing service locations does not imply malicious intent, all of their uses in a software package should be documented and approved. An increasing number of software supply chain attacks in the open source space leverages the GitHub service to deliver malicious payloads.Prevalence in PyPI community
33 packages
found in
Top 100
206 packages
found in
Top 1k
1631 packages
found in
Top 10k
63840 packages
in community
Next steps
Investigate reported detections.
If the software should not include these network references, investigate your build and release environment for software supply chain compromise.
You should delay the software release until the investigation is completed, or until the issue is risk accepted.
Consider an alternative delivery mechanism for software packages.
Detected presence of plaintext credentials within network protocol strings.
Causes risk: web service credentials found
3
secrets
Problem
Various network communication protocols allow including plaintext authentication credentials. Information such as user names and passwords could be passed through a non-encrypted channel, and therefore intercepted by malicious actors. Credentials are considered secrets, and should be kept encrypted until they are used. This policy control matches the following URI pattern protocol://username:password@domain within any software package component.Prevalence in PyPI community
21 packages
found in
Top 100
85 packages
found in
Top 1k
369 packages
found in
Top 10k
6869 packages
in community
Next steps
Review the reported matches. If the warning refers to a placeholder credential value, it can be safely ignored.
Problem
Software components contain executable code that performs actions implemented during its development. These actions are called behaviors. In the analysis report, behaviors are presented as human-readable descriptions that best match the underlying code intent. While most behaviors are benign, some are commonly abused by malicious software with the intent to cause harm. When a software package shares behavior traits with malicious software, it may become flagged by security solutions. Any detection from security solutions can cause friction for the end-users during software deployment. While the behavior is likely intended by the developer, there is a small chance this detection is true positive, and an early indication of a software supply chain attack.Prevalence in PyPI community
0 packages
found in
Top 100
2 packages
found in
Top 1k
7 packages
found in
Top 10k
1009 packages
in community
Next steps
Investigate reported detections.
If the software intent does not relate to the reported behavior, investigate your build and release environment for software supply chain compromise.
You should delay the software release until the investigation is completed, or until the issue is risk accepted.
Consider rewriting the flagged code without using the marked behaviors.
Problem
Uniform Resource Locators (URLs) are structured addresses that point to locations and assets on the internet. URLs allow software developers to build complex applications that exchange data with servers that can be hosted in multiple geographical regions. URLs can commonly be found embedded in documentation, configuration files, source code and compiled binaries. Top-level domains (TLD) are a part of the Domain Name System (DNS), and are used to lookup an Internet Protocol (IP) address of a requested website. There are a few different types of top-level domains. Generic, sponsored and country-code TLDs are generally accessible to the public. Registrars that govern the assignment of domain names within the TLD may choose to sell specific domain names to an interested party. However, some registrars are known to have less strict rules for assigning domain names. Attackers often abuse gaps in governance and actively seek to register their malicious domains in such TLDs. This issue is raised for all domains registered within TLDs that harbor an excessive number of malicious sites. While the presence of suspicious TLDs does not imply malicious intent, all of its uses in a software package should be documented and approved.Prevalence in PyPI community
12 packages
found in
Top 100
83 packages
found in
Top 1k
478 packages
found in
Top 10k
15910 packages
in community
Next steps
Investigate reported detections.
If the software should not include these network references, investigate your build and release environment for software supply chain compromise.
You should delay the software release until the investigation is completed, or until the issue is risk accepted.
Consider changing the top-level domain to avoid being flagged by security solutions.
Problem
Uniform Resource Locators (URLs) are structured addresses that point to locations and assets on the internet. URLs allow software developers to build complex applications that exchange data with servers that can be hosted in multiple geographical regions. URLs can commonly be found embedded in documentation, configuration files, source code and compiled binaries. URL paths provide additional information to a web service when making a request. They are an optional, but an important part of the URL, as they may define specific content or actions based on the data being passed. Some parameters they pass might be considered sensitive information. Since path components are not encrypted this might cause sensitive information to leak. This issue is raised for URL paths than might contain information that attackers can easily intercept. Examples of sensitive information fields include passwords and other similar parameters.Prevalence in PyPI community
12 packages
found in
Top 100
59 packages
found in
Top 1k
404 packages
found in
Top 10k
8958 packages
in community
Next steps
Investigate reported detections.
If the software should not include these network references, investigate your build and release environment for software supply chain compromise.
You should delay the software release until the investigation is completed, or until the issue is risk accepted.
Consider removing all references to flagged network locations.
Problem
Uniform Resource Locators (URLs) are structured addresses that point to locations and assets on the internet. URLs allow software developers to build complex applications that exchange data with servers that can be hosted in multiple geographical regions. URLs can commonly be found embedded in documentation, configuration files, source code and compiled binaries. When accessing the internet, a device is assigned a unique Internet Protocol (IP) address. This address identifies the point of origin and destination of each request a connected device makes. Attackers often aim to better understand their targets. Collecting basic reconnaissance information typically includes the IP address of a machine. While the operating system has the utilities to get this information, some attackers may prefer getting this data from an external source. Many web services host pages that return the IP address of the caller. For that reason, attackers often opt to get the IP information from a third-party service. While the presence of IP querying services does not imply malicious intent, all of their uses in a software package should be documented and approved.Prevalence in PyPI community
0 packages
found in
Top 100
11 packages
found in
Top 1k
67 packages
found in
Top 10k
3941 packages
in community
Next steps
Investigate reported detections.
If the software should not include these network references, investigate your build and release environment for software supply chain compromise.
You should delay the software release until the investigation is completed, or until the issue is risk accepted.
Consider an alternative mechanism for detecting the machine's IP address.
Problem
Crypto tokens are versatile digital assets used within the blockchain ecosystem. Crypto tokens are used to represent a wide range of values, rights, or utilities. They play a crucial role in decentralized finance (DeFi), governance, and other blockchain-based applications. Most crypto tokens are built on existing blockchains using smart contracts. A smart contract is a self-executing contract with the terms of the agreement directly written as lines of code. These contracts automatically execute and enforce themselves when predetermined conditions are met, without the need for intermediaries. For this reason, attackers often aim to steal crypto tokens from the machines they infect. Once stolen, crypto tokens are difficult to trace or recover due to the decentralized and pseudonymous nature of blockchain technology. The irreversibility of blockchain transactions means that once the tokens are transferred to the another crypto wallet, they are effectively gone, making them an attractive target for financially motivated actors. While presence of regex code that detects crypto tokens does not imply malicious intent, all of its uses in a software package should be documented and approved. Only select applications should consider working with crypto tokens.Prevalence in PyPI community
0 packages
found in
Top 100
2 packages
found in
Top 1k
0 packages
found in
Top 10k
283 packages
in community
Next steps
Investigate reported detections as indicators of software tampering.
Consider rewriting the flagged code without using the marked behaviors.
10