How do I interpret SCL scores in Microsoft headers?

Summary

Interpreting SCL (Spam Confidence Level) scores in Microsoft headers is crucial for effective email management. The SCL scale ranges from -1 to 9, where -1 indicates the email is not spam, 0-2 suggests a low probability of spam (often considered 'good'), and 7-9 indicates a high probability of spam. These scores, found in the `X-MS-Exchange-Organization-SCL` header, are influenced by factors like sender reputation, email content, and Bayesian filtering. Organizations can configure their email systems to take specific actions based on these scores, such as moving emails to the junk folder or deleting them. It is also important to distinguish SCL, focused on spam, from BCL (Bulk Complaint Level), focused on bulk or marketing emails. While SCL scores are useful, they should not be the only determinant of spam classification due to the possibility of false positives and negatives. A multi-layered approach to spam filtering, combined with regular monitoring and customized thresholds, is recommended. Ignoring these considerations can lead to legal implications and misclassification of legitimate emails.

Key findings

  • SCL Scale: SCL values range from -1 to 9, indicating spam probability. -1 is not spam, 0-2 is low probability, and 7-9 is high probability.
  • Header Location: The SCL value is found in the `X-MS-Exchange-Organization-SCL` header.
  • Configurable Actions: Organizations can configure actions based on SCL thresholds (e.g., moving to junk or deleting).
  • Influencing Factors: Factors like sender reputation, email content, and Bayesian filtering influence SCL scores.
  • SCL vs BCL: SCL focuses on spam, while BCL focuses on bulk/marketing emails.

Key considerations

  • Multi-Layered Approach: Use a multi-layered approach to spam filtering, not relying solely on SCL scores.
  • Customized Thresholds: Customize SCL thresholds to align with specific needs and risk tolerance.
  • Regular Monitoring: Monitor SCL scores regularly to identify emerging spam trends and potential security threats.
  • False Positives/Negatives: Be aware of potential false positives and negatives when interpreting SCL scores.
  • Legal Implications: Consider the legal implications of overly aggressive spam filtering.

What email marketers say
8Marketer opinions

SCL (Spam Confidence Level) scores in Microsoft headers provide a numerical indication of the likelihood that an email is spam. Ranging from -1 to 9, these scores influence how email systems filter and handle messages. Lower scores (0-2) typically indicate legitimate emails, while higher scores (7-9) suggest a strong likelihood of spam. Understanding SCL values allows administrators to configure spam filtering rules, customize thresholds, and monitor for emerging threats. Factors such as sender reputation, content, and keywords affect these scores. Overly aggressive filtering, however, can lead to legal issues and misclassification of legitimate emails.

Key opinions

  • SCL Range: SCL scores range from -1 to 9, with lower scores indicating legitimate emails and higher scores indicating spam.
  • Configurable Actions: Organizations can configure email systems to take specific actions based on SCL values, such as moving messages to the Junk Email folder or deleting them.
  • Effective Filtering: Understanding SCL values enables administrators to create more effective spam filtering rules and fine-tune filtering thresholds.
  • Emerging Threats: Monitoring SCL scores can help identify emerging spam trends and potential security threats.
  • Influencing Factors: Factors such as sender reputation, email content, and the presence of specific keywords can influence SCL scores.

Key considerations

  • Customization: Organizations can customize SCL thresholds to align with their specific needs and risk tolerance.
  • Monitoring: Regularly monitor SCL scores to identify potential security threats and emerging spam trends.
  • False Positives: Ensure that legitimate emails are not mistakenly classified as spam due to overly aggressive filtering.
  • Legal Implications: Be aware of the legal implications of overly aggressive spam filtering, particularly regarding interference with business communications or violations of anti-discrimination laws.
  • Multi-Layered Approach: SCL scores should not be relied upon as the sole determinant of whether an email is spam. Use a multi-layered approach to spam filtering.
Marketer view

Email marketer from Reddit shares that SCL values of 0-2 generally indicate that the message is considered 'good' or likely not spam. These messages have passed most spam checks.

March 2021 - Reddit
Marketer view

Email marketer from Spamlaws.com explains that while SCL scores can help filter spam, it's important to ensure that legitimate emails are not mistakenly classified as spam. Overly aggressive spam filtering can have legal implications, particularly if it interferes with business communications or violates anti-discrimination laws.

May 2023 - Spamlaws.com
Marketer view

Email marketer from Practical365 shares that organizations can configure Exchange to take specific actions based on SCL values. For example, messages with an SCL of 7 or higher might be automatically moved to the Junk Email folder, while messages with an SCL of 9 might be deleted.

March 2022 - Practical365
Marketer view

Email marketer from MXToolbox explains that understanding SCL values allows administrators to create more effective spam filtering rules. By analyzing the SCL values of legitimate and spam emails, administrators can fine-tune their filtering thresholds to minimize false positives and false negatives.

January 2024 - MXToolbox
Marketer view

Email marketer from EmailGeekForum shares that organizations can customize SCL thresholds to align with their specific needs and risk tolerance. For example, a financial institution might choose to use more aggressive spam filtering than a small business.

November 2024 - EmailGeekForum
Marketer view

Email marketer from StackExchange explains that SCL values of 7 or higher strongly suggest that the message is spam and should be treated with caution. Messages with these scores often contain malicious content or phishing attempts.

July 2021 - StackExchange
Marketer view

Email marketer from TechTarget shares that several factors can influence SCL scores, including the sender's IP address reputation, the content of the message, and the presence of certain keywords or phrases commonly associated with spam.

April 2022 - TechTarget
Marketer view

Email marketer from EmailSecurityBlog explains that regularly monitoring SCL scores can help identify emerging spam trends and potential security threats. Sudden increases in SCL scores for certain types of messages may indicate a new phishing campaign or a vulnerability in your email infrastructure.

July 2021 - EmailSecurityBlog

What the experts say
3Expert opinions

Interpreting SCL (Spam Confidence Level) scores in Microsoft headers involves understanding that the scale generally ranges from 0-9, with lower scores (1-2) being low/neutral and higher scores indicating a greater likelihood of spam. It's important to note that SCL scores should not be the sole factor in determining whether an email is spam, as false positives and negatives can occur. Bayesian filtering systems, which analyze email content and patterns, can also influence these scores.

Key opinions

  • SCL Scale: The SCL scale ranges from 0-9, with lower scores (1-2) being low/neutral.
  • Bayesian Influence: Bayesian filtering systems can influence SCL scores by analyzing email content.
  • PCL: PCL (phishing confidence level) any score is bad.

Key considerations

  • Multi-layered Approach: Do not rely solely on SCL scores; use a multi-layered approach to spam filtering.
  • False Positives/Negatives: Be aware of the potential for false positives and false negatives when interpreting SCL scores.
Expert view

Expert from Word to the Wise explains how Bayesian filtering systems can influence the SCL score by examining the content of the email and identifying patterns associated with spam.

November 2021 - Word to the Wise
Expert view

Expert from Spam Resource explains that while SCL scores are a useful indicator, they should not be relied upon as the sole determinant of whether an email is spam. False positives and false negatives can occur, so it's important to consider other factors and use a multi-layered approach to spam filtering.

October 2022 - Spam Resource
Expert view

Expert from Email Geeks initially explains that any PCL (phishing confidence level) score is bad, then clarifies, after checking notes, that the SCL (spam confidence level) scale is 0-9, where 1-2 are low/neutral.

December 2024 - Email Geeks

What the documentation says
5Technical articles

SCL (Spam Confidence Level) scores in Microsoft headers range from -1 to 9, indicating the probability of an email being spam. A score of -1 means the email is not spam, while higher scores suggest a greater likelihood of spam. The SCL value is found in the `X-MS-Exchange-Organization-SCL` header. Based on these scores, various actions can be taken, such as moving messages to the junk folder or quarantining them. Tools like Cisco ESA can integrate with Exchange to utilize SCL values. It's important to distinguish SCL, which focuses on spam, from BCL (Bulk Complaint Level), which deals with bulk or marketing emails.

Key findings

  • SCL Range: SCL values range from -1 to 9, indicating spam probability.
  • Header Location: SCL values are found in the `X-MS-Exchange-Organization-SCL` header.
  • Actionable Thresholds: Actions like moving to junk or quarantining can be based on SCL thresholds.
  • Integration: Tools like Cisco ESA can integrate with Exchange using SCL values.
  • SCL vs. BCL: SCL focuses on spam, while BCL focuses on bulk/marketing emails.

Key considerations

Technical article

Documentation from Microsoft Learn explains that SCL values are found within the message headers of an email. Specifically, the `X-MS-Exchange-Organization-SCL` header contains the SCL rating assigned by Exchange Online Protection (EOP).

February 2022 - Microsoft Learn
Technical article

Documentation from Cisco explains that Cisco Email Security Appliance (ESA) can integrate with Microsoft Exchange to utilize SCL values for enhanced spam detection and filtering. This integration allows ESA to leverage Exchange's spam filtering capabilities while providing additional layers of security.

February 2023 - Cisco
Technical article

Documentation from Proofpoint describes the difference between Spam Confidence Level (SCL) and Bulk Complaint Level (BCL) in email headers. SCL focuses on spam, BCL focuses on emails which aren't strictly spam but are marketing/bulk emails.

August 2022 - Proofpoint
Technical article

Documentation from Microsoft Learn explains that SCL values range from -1 to 9. -1 indicates that the message is not spam (e.g., from a safe sender or safe recipient), while values 0-9 represent increasing levels of spam probability. Higher values indicate a greater likelihood that a message is spam.

June 2024 - Microsoft Learn
Technical article

Documentation from Microsoft Learn describes various actions that can be taken based on SCL thresholds, including moving messages to the Junk Email folder, quarantining them, or rejecting them outright.

February 2024 - Microsoft Learn