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[Snyk] Security upgrade lerna from 4.0.0 to 5.0.0 #252

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Snyk has created this PR to fix one or more vulnerable packages in the `yarn` dependencies of this project.

merge advice

Changes included in this PR

  • Changes to the following files to upgrade the vulnerable dependencies to a fixed version:
    • package.json
⚠️ Warning
Failed to update the yarn.lock, please update manually before merging.

Vulnerabilities that will be fixed

With an upgrade:
Severity Priority Score (*) Issue Breaking Change Exploit Maturity
high severity 696/1000
Why? Proof of Concept exploit, Has a fix available, CVSS 7.5
Regular Expression Denial of Service (ReDoS)
SNYK-JS-ANSIREGEX-1583908
Yes Proof of Concept

(*) Note that the real score may have changed since the PR was raised.

Check the changes in this PR to ensure they won't cause issues with your project.


Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

For more information:
🧐 View latest project report

🛠 Adjust project settings

📚 Read more about Snyk's upgrade and patch logic


Learn how to fix vulnerabilities with free interactive lessons:

🦉 Learn about vulnerability in an interactive lesson of Snyk Learn.

The following vulnerabilities are fixed with an upgrade:
- https://snyk.io/vuln/SNYK-JS-ANSIREGEX-1583908
@pull-request-quantifier-deprecated

This PR has 2 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!


Quantification details

Label      : Extra Small
Size       : +1 -1
Percentile : 0.8%

Total files changed: 1

Change summary by file extension:
.json : +1 -1

Change counts above are quantified counts, based on the PullRequestQuantifier customizations.

Why proper sizing of changes matters

Optimal pull request sizes drive a better predictable PR flow as they strike a
balance between between PR complexity and PR review overhead. PRs within the
optimal size (typical small, or medium sized PRs) mean:

  • Fast and predictable releases to production:
    • Optimal size changes are more likely to be reviewed faster with fewer
      iterations.
    • Similarity in low PR complexity drives similar review times.
  • Review quality is likely higher as complexity is lower:
    • Bugs are more likely to be detected.
    • Code inconsistencies are more likely to be detetcted.
  • Knowledge sharing is improved within the participants:
    • Small portions can be assimilated better.
  • Better engineering practices are exercised:
    • Solving big problems by dividing them in well contained, smaller problems.
    • Exercising separation of concerns within the code changes.

What can I do to optimize my changes

  • Use the PullRequestQuantifier to quantify your PR accurately
    • Create a context profile for your repo using the context generator
    • Exclude files that are not necessary to be reviewed or do not increase the review complexity. Example: Autogenerated code, docs, project IDE setting files, binaries, etc. Check out the Excluded section from your prquantifier.yaml context profile.
    • Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in your prquantifier.yaml context profile.
    • Only use the labels that matter to you, see context specification to customize your prquantifier.yaml context profile.
  • Change your engineering behaviors
    • For PRs that fall outside of the desired spectrum, review the details and check if:
      • Your PR could be split in smaller, self-contained PRs instead
      • Your PR only solves one particular issue. (For example, don't refactor and code new features in the same PR).

How to interpret the change counts in git diff output

  • One line was added: +1 -0
  • One line was deleted: +0 -1
  • One line was modified: +1 -1 (git diff doesn't know about modified, it will
    interpret that line like one addition plus one deletion)
  • Change percentiles: Change characteristics (addition, deletion, modification)
    of this PR in relation to all other PRs within the repository.


Was this comment helpful? 👍  :ok_hand:  :thumbsdown: (Email)
Customize PullRequestQuantifier for this repository.

@secure-code-warrior-for-github

Micro-Learning Topic: Regular expression denial of service (Detected by phrase)

Matched on "Regular Expression Denial of Service"

What is this? (2min video)

Denial of Service (DoS) attacks caused by Regular Expression which causes the system to hang or cause them to work very slowly when attacker sends a well-crafted input(exponentially related to input size).Denial of service attacks significantly degrade the service quality experienced by legitimate users. These attacks introduce large response delays, excessive losses, and service interruptions, resulting in direct impact on availability.

Try this challenge in Secure Code Warrior

Micro-Learning Topic: Denial of service (Detected by phrase)

Matched on "Denial of Service"

The Denial of Service (DoS) attack is focused on making a resource (site, application, server) unavailable for the purpose it was designed. There are many ways to make a service unavailable for legitimate users by manipulating network packets, programming, logical, or resources handling vulnerabilities, among others. Source: https://www.owasp.org/index.php/Denial_of_Service

Try this challenge in Secure Code Warrior

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