Identify if access token is in source code
using AI
Below is a free classifier to identify if access token is in source code. Just input your text, and our AI will predict if access token is exposed - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("if-access-token-is-in-source-code", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/if-access-token-is-in-source-code/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-source-code/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict if access token is exposed.
This pretrained text model uses a Nyckel-created dataset and has 2 labels, including Token Absent and Token Present.
We'll also show a confidence score (the higher the number, the more confident the AI model is around if access token is exposed).
Whether you're just curious or building if access token is in source code detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify if access token is in source code at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Security Auditing: Regularly scan source code repositories to identify any instances where access tokens are hard-coded. By flagging these vulnerabilities, organizations can take corrective actions to enhance their security posture and reduce the risk of unauthorized access.
- Compliance Monitoring: Enforce compliance with security best practices and regulations by automatically checking for access tokens in source code. This ensures that development teams adhere to secure coding standards and helps avoid potential fines due to non-compliance.
- Continuous Integration/Continuous Deployment (CI/CD) Pipelines: Integrate the text classification function into CI/CD workflows to automatically reject builds that contain sensitive information such as access tokens. This proactive approach helps prevent deployment of insecure code to production environments.
- Code Review Assistance: Provide development teams with an automated tool that highlights the presence of access tokens during code reviews. This allows for a more efficient review process by ensuring that sensitive information is scrutinized and removed before merging changes.
- Legacy Code Refactoring: Analyze legacy systems to identify outdated code with embedded access tokens. This enables organizations to modernize their codebase by removing security vulnerabilities and replacing them with secure authentication methods.
- Education and Training: Utilize findings from the text classification function to create training materials for developers, raising awareness about the risks of hard-coding access tokens. This educational approach fosters a culture of security-conscious coding practices within the organization.
- Automated Code Quality Tools: Enhance existing static code analysis tools with this text classification capability to provide a broader assessment of code quality. By detecting potential security vulnerabilities related to access tokens, teams can ensure the overall integrity and security of their applications.