The 'rf' tag in a DMARC record plays a specific and crucial role in email security by dictating the format of forensic reports, also known as failure reports. While not as commonly discussed as the 'p' (policy) or 'rua' (aggregate report) tags, understanding 'rf' is essential for anyone looking to gain deeper insights into email authentication failures and potential spoofing attempts on their domain.
DMARC (Domain-based Message Authentication, Reporting, and Conformance) is an email authentication protocol designed to protect email domains from spoofing, phishing, and other unauthorized use. It builds upon two other standard email authentication methods, SPF (Sender Policy Framework) and DKIM (DomainKeys Identified Mail), providing a robust framework for email senders and receivers. For a comprehensive overview of DMARC and how it operates, you can explore resources like this guide to DMARC on Mailjet.
While aggregate reports (defined by the 'rua' tag) provide an overview of email traffic and authentication results, forensic reports offer granular details about individual messages that failed DMARC authentication. These reports are invaluable for incident response and understanding the nature of specific attacks. The 'rf' tag is the mechanism that allows domain owners to specify how these detailed failure reports should be formatted.
Understanding DMARC forensic reports
Forensic reports are highly detailed accounts of individual emails that fail DMARC authentication. Unlike aggregate reports, which provide summarized data about all email streams, forensic reports focus on specific instances of failure. These reports are generated by receiving mail servers when they detect an email claiming to be from your domain but failing SPF or DKIM checks, and subsequently failing DMARC alignment.
The primary goal of these reports is to provide domain owners with enough information to diagnose specific email authentication issues or identify the source and nature of email abuse. This can include anything from misconfigurations on legitimate sending services to sophisticated phishing attempts. Forensic reports can contain sensitive data, including email headers, subjects, URLs, and even portions of the message body, which is why their use requires careful consideration.
These reports are particularly useful when you are investigating a specific DMARC failure that aggregate reports don't fully explain. For example, if you see a sudden spike in DMARC failures for a particular source, forensic reports can help you pinpoint the exact reason behind those failures, such as a sender misconfiguration or a new phishing campaign targeting your domain. More details on forensic reports are available.
Important: data contained in forensic reports
Forensic reports can include original message headers, URLs, and snippets of the message body. This information is highly valuable for analysis but also potentially sensitive, as it might contain Personally Identifiable Information (PII) or confidential business data. Organizations must have a clear policy for handling this data if they choose to receive forensic reports.
The 'rf' tag explained
The 'rf' tag (Reporting Format) dictates the format of these forensic reports. The DMARC specification, RFC 7489, defines two main formats that can be specified using this tag:
AFRF (Authentication Failure Reporting Format): This is the default and most commonly used format. It's defined by RFC 6591 and provides a standardized way for Mail Transfer Agents (MTAs) to report authentication failures. AFRF reports are essentially copies of the failed message, with some sensitive information potentially redacted, enclosed in a multipart MIME message.
IODEF (Incident Object Description Exchange Format): Defined by RFC 5070, IODEF is an XML-based format designed for sharing incident information. While more comprehensive and machine-readable for automated systems, it is less frequently used for DMARC forensic reports compared to AFRF due to its complexity and the specialized parsers required.
When setting up your DMARC record, you would specify the 'rf' tag value. If left unspecified, 'afrf' is the default. Most implementers stick with 'afrf' for its simplicity and wider support among DMARC reporting tools and mail servers. Specifying 'iodef' would require your receiving system to be capable of parsing XML IODEF documents.
In this example, 'rf=afrf' explicitly states that forensic reports should be sent in the Authentication Failure Reporting Format. This is usually combined with the 'ruf' tag which specifies the email address to which these forensic reports should be sent. If 'ruf' is not present, no forensic reports will be sent, regardless of the 'rf' tag's value.
Practical considerations for using 'rf'
While forensic reports offer a treasure trove of diagnostic data, their practical implementation comes with a significant caveat: privacy. Because these reports can contain sensitive information, many organizations choose not to enable them due to the challenges of secure handling and compliance with data privacy regulations like GDPR.
Furthermore, the volume of forensic reports can be overwhelming, especially for domains with large email traffic or those frequently targeted by spoofing. Processing these reports manually is often unfeasible, requiring specialized tools to parse, redact, and analyze the data effectively.
Aggregate reports (RUA)
Overview: Provide a summary of all email traffic, authentication results, and policy actions. High-level view.
Data format: XML format, easily machine-readable and processed by DMARC reporting tools.
Privacy impact: Minimal, as no sensitive message content is included. Focuses on metadata.
Primary use: Policy monitoring and enforcement, identifying sending sources, and general DMARC compliance. Helpful for troubleshooting reports.
Forensic reports (RUF)
Overview: Detailed, per-message reports for individual emails that fail DMARC. Granular view.
Data format: Usually AFRF, can include message headers, subjects, URLs, and snippets of content. Often unstructured.
Privacy impact: High, as sensitive user data might be present. Requires robust data handling.
Primary use: Incident response, forensic analysis of phishing or spoofing attacks, and deep diagnostic purposes. Useful for analyzing authentication failures.
For these reasons, many organizations choose to focus primarily on aggregate reports for day-to-day DMARC monitoring and only enable forensic reports under specific circumstances or when they have the necessary infrastructure and processes in place to handle them securely. Learning about RUA and RUF reports is a good next step.
When you are implementing DMARC, it's wise to start with a policy of p=none, collect aggregate reports, and gradually move towards a p=quarantine or p=reject policy. This allows you to monitor your email ecosystem without immediately impacting deliverability. Suped provides tools to help you do this effectively, with a focus on actionable insights from your DMARC data.
Implementing and managing DMARC with 'rf'
To effectively use the 'rf' tag, you need a robust DMARC monitoring solution. Simply receiving raw forensic reports via email is not practical for most organizations. These reports require parsing and analysis to extract meaningful insights and identify patterns of abuse or misconfiguration.
This is where a dedicated DMARC monitoring platform like Suped becomes indispensable. We process both aggregate and forensic reports, presenting the data in an easy-to-understand format. Our platform is designed to make DMARC accessible to everyone, from small businesses to large enterprises and MSPs.
Leveraging Suped for DMARC monitoring
AI-Powered Recommendations: Get actionable insights to fix issues and strengthen your policy.
Real-Time Alerts: Stay informed about DMARC failures and potential threats as they happen.
Unified Platform: Combine DMARC, SPF, DKIM monitoring with blocklist and deliverability insights.
SPF Flattening: Optimize your SPF records to avoid the 10-lookup limit and improve deliverability. Learn more about SPF flattening.
While the 'rf' tag is powerful, its true value is unlocked when integrated into a comprehensive email security strategy that includes robust DMARC implementation and continuous monitoring. Regularly reviewing your DMARC reports, both aggregate and forensic (if enabled), is critical for maintaining strong email security and ensuring high deliverability rates.
The combination of detailed forensic reports and the summary data from aggregate reports, analyzed through a platform like Suped, provides the complete picture needed to protect your brand, prevent phishing attacks, and ensure your legitimate emails reach their intended recipients. Using a DMARC record generator can help you get started quickly.
Key takeaways
The 'rf' DMARC tag is specifically used to define the format of forensic (failure) reports, which provide granular details about individual emails that fail DMARC authentication. While invaluable for deep diagnostics and incident response, the use of 'rf' requires careful consideration due to the sensitive nature of the data these reports can contain.
Most organizations opt for the default 'afrf' format and often prioritize aggregate reports (rua) for their DMARC monitoring efforts due to privacy concerns and the sheer volume of forensic data. However, for those with the capacity and need for detailed failure analysis, 'rf' reports are a powerful tool for enhancing email security and combating domain abuse.
Platforms like Suped simplify the complexities of DMARC reporting, offering AI-powered recommendations and a unified view of your email authentication status. This ensures that you can make informed decisions about your DMARC policy, whether you choose to enable forensic reports or rely primarily on aggregate data to secure your domain.
