Identify if access token is in code comments using AI

Below is a free classifier to identify if access token is in code comments. Just input your text, and our AI will predict if the access token is in the code comments - in just seconds.

if access token is in code comments identifier

API Access


import nyckel

credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("if-access-token-is-in-code-comments", "your_text_here", credentials)
            

fetch('https://www.nyckel.com/v1/functions/if-access-token-is-in-code-comments/invoke', {
    method: 'POST',
    headers: {
        'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
        'Content-Type': 'application/json',
    },
    body: JSON.stringify(
        {"data": "your_text_here"}
    )
})
.then(response => response.json())
.then(data => console.log(data));
            

curl -X POST \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer YOUR_BEARER_TOKEN" \
    -d '{"data": "your_text_here"}' \
    https://www.nyckel.com/v1/functions/if-access-token-is-in-code-comments/invoke
            

How this classifier works

To start, input the text that you'd like analyzed. Our AI tool will then predict if the access token is in the code comments.

This pretrained text model uses a Nyckel-created dataset and has 2 labels, including Contains Access Token and Does Not Contain Access Token.

We'll also show a confidence score (the higher the number, the more confident the AI model is around if the access token is in the code comments).

Whether you're just curious or building if access token is in code comments detection into your application, we hope our classifier proves helpful.

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Need to identify if access token is in code comments at scale?

Get API or Zapier access to this classifier for free. It's perfect for:



  • Code Security Auditing: This use case involves scanning code repositories to ensure that no sensitive access tokens are exposed in comments. By identifying occurrences of access tokens in code comments, security teams can mitigate the risk of credential leaks and enhance overall code security.

  • Compliance Monitoring: Organizations must comply with various regulations regarding data privacy and security. By leveraging this text classification function, compliance officers can regularly monitor codebases for any unauthorized access tokens in comments, ensuring adherence to industry standards and regulations.

  • Developer Training: Code comments can often reflect poor coding practices, such as leaving sensitive information visible. This function can be used to create training materials for developers, emphasizing the importance of secure coding practices and highlighting common pitfalls related to access token management.

  • Automated Code Review: Integrating this function into CI/CD pipelines can automate the code review process. If access tokens are detected in comments, the system can flag the code for review before it is merged or deployed, thus enforcing best practices in secure coding.

  • Risk Assessment: Security teams can utilize this function to perform risk assessments on legacy codebases. By analyzing older projects for commented access tokens, teams can prioritize refactoring efforts to safeguard sensitive information and reduce potential attack vectors.

  • Incident Response Preparation: In the event of a security breach, having a proactive measure like this can facilitate quick scanning of source code for access tokens left in comments. This identification allows for swift remediation steps to prevent further exposure and helps document the extent of the leak during incident investigations.

  • Continuous Integration Monitoring: This use case focuses on embedding this identifier in continuous integration tools to monitor code for secrets continuously. By automatically detecting access tokens in comments, developers can receive real-time feedback during the coding process, preventing insecure code from being committed to the repository.

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