Identify if social security number is in an email
using AI
Below is a free classifier to identify if social security number is in an email. Just input your text, and our AI will predict if a social security number is present in the email - in just seconds.
Contact us for API access
Or, use Nyckel to build highly-accurate custom classifiers in just minutes. No PhD required.
Get started
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("if-social-security-number-is-in-an-email", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/if-social-security-number-is-in-an-email/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-social-security-number-is-in-an-email/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict if a social security number is present in the email.
This pretrained text model uses a Nyckel-created dataset and has 2 labels, including Contains Social Security Number and Does Not Contain Social Security Number.
We'll also show a confidence score (the higher the number, the more confident the AI model is around if a social security number is present in the email).
Whether you're just curious or building if social security number is in an email detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify if social security number is in an email at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Email Security Monitoring: This use case involves leveraging the true text classification function to automatically scan incoming emails for social security numbers (SSNs). By identifying and flagging these emails, organizations can prevent sensitive data exposure and ensure compliance with data protection regulations.
- Fraud Detection in Customer Service: Customer service representatives can utilize the text classification function to analyze email communications for SSNs. This helps in identifying potential fraud attempts where individuals might attempt to misuse SSNs in transactions or support queries.
- Compliance Auditing: Businesses can implement the function as part of a broader compliance auditing process to regularly review email correspondence. By detecting SSNs in emails, organizations can assess whether they are adhering to data protection laws and internal policies regarding sensitive information handling.
- Automated Incident Response: In the event of a data breach or incident, the text classification function can aid in quickly locating emails that contain SSNs. This accelerates incident response efforts, allowing security teams to investigate potential leaks of sensitive customer information efficiently.
- Training and Awareness Programs: Organizations can use the findings from the text classification function to improve employee training and awareness programs regarding email security. By highlighting instances of SSN exposure in employee communications, training can be tailored to address specific security vulnerabilities.
- Data Retention Policy Enforcement: The function can be integrated into data retention software to ensure that emails containing SSNs are handled according to legal and organizational data retention policies. It helps automate the identification of emails that need to be archived or deleted, reducing the risk of unauthorized access.
- Risk Assessment for Marketing Campaigns: Marketing teams can use the text classification function to review promotional emails for SSNs before sending. This allows them to mitigate risks associated with inadvertently including sensitive data in campaigns, thus protecting customer privacy and brand reputation.