Mitigating Deliverability Issues with Automated DMARC Policy Updates

1 November 2026 · DMARC Engine · 10 min read

The Challenge of Manual DMARC Policy Updates

Manual DMARC policy updates can be error-prone and time-consuming, particularly for organisations with complex email infrastructures. A common pattern is for administrators to update the DMARC policy in the DNS record, for example, changing from p=none to p=quarantine, without fully considering the potential impact on deliverability.

_dmarc.example.com. IN TXT "v=DMARC1; p=none; pct=100; rua=mailto:aggregate@example.com; ruf=mailto:forensic@example.com; fo=1"

becomes

_dmarc.example.com. IN TXT "v=DMARC1; p=quarantine; pct=100; rua=mailto:aggregate@example.com; ruf=mailto:forensic@example.com; fo=1"

However, this approach can lead to issues if the organisation's email streams are not fully aligned with the updated policy, resulting in legitimate emails being quarantined or rejected.

A hosted or managed setup may handle this by providing a user interface to update the DMARC policy, but it is still crucial for administrators to understand the underlying DNS records and the potential consequences of their actions.

import dns.resolver

answers = dns.resolver.resolve('_dmarc.example.com', 'TXT')
for answer in answers:
 print(answer)

Warning: updating the DMARC policy without careful consideration of the potential impact on deliverability can result in significant issues, including legitimate emails being blocked or quarantined.

Understanding DMARC Policy Update Trade-Offs

When updating DMARC policies, administrators must weigh the trade-offs between blocking malicious emails and potentially disrupting legitimate email flows. A common pattern is to start with a monitoring-only policy, such as v=DMARC1; p=none, and then gradually move to a more restrictive policy, like v=DMARC1; p=quarantine or v=DMARC1; p=reject.

The aggregate reports will show the effects of these changes, allowing administrators to refine their policies.

_v=DMARC1; p=none; rua=mailto:aggregate@example.com

This approach allows administrators to assess the impact of their policies on legitimate email traffic before enforcing stricter rules. Receivers typically honour the p tag in the DMARC record, so updating this tag will change how receivers handle emails that fail DMARC checks.

_v=DMARC1; p=quarantine; rua=mailto:aggregate@example.com

In a hosted or managed setup, the DMARC record may be automatically updated based on the administrator's settings, but it is still crucial to understand the underlying trade-offs and monitor the effects of these updates.

_v=DMARC1; p=reject; rua=mailto:aggregate@example.com; ruf=mailto:failure@example.com

The rua and ruf tags in the DMARC record control where aggregate and failure reports are sent, respectively. Administrators should ensure these tags point to mailboxes they control, to avoid missing critical reports.

Note:
Administrators should be cautious when updating DMARC policies, as changes can have unintended consequences, such as blocking legitimate emails or allowing malicious emails to pass through. It is essential to monitor the effects of these changes closely and adjust the policies accordingly.

Automating DMARC Policy Updates: Considerations and Best Practices

When automating DMARC policy updates, a key consideration is the initial setup of the DMARC record. The record should be published on the domain the organisation controls, rather than a hosting or email provider's own hostname. For example, a DMARC record for example.com would be published as _dmarc.example.com.

_dmarc.example.com. IN TXT "v=DMARC1; p=none; rua=mailto:aggregate@example.com; ruf=mailto:failure@example.com; fo=1"

A common pattern is for organisations to start with a p=none policy, which allows them to monitor DMARC reports without affecting deliverability. Receivers typically honour the p tag in the DMARC record, so it is crucial to update this tag carefully. The aggregate reports will show the number of messages that pass and fail DMARC authentication, which can inform the decision to update the policy to p=quarantine or p=reject.

_dmarc.example.com. IN TXT "v=DMARC1; p=quarantine; rua=mailto:aggregate@example.com; ruf=mailto:failure@example.com; fo=1"

When automating DMARC policy updates, it is essential to consider the potential impact on deliverability. A hosted or managed setup may handle this by providing a staging environment to test policy updates before applying them to production. However, organisations should be cautious when updating the policy, as a misconfigured record can lead to deliverability issues.

_dmarc.example.com. IN TXT "v=DMARC1; p=reject; rua=mailto:aggregate@example.com; ruf=mailto:failure@example.com; fo=1"

Organisations should also consider the frequency of DMARC policy updates. Updating the policy too frequently can lead to fluctuations in deliverability, while updating it too infrequently may not provide adequate protection against spoofing. A balanced approach is to update the policy based on the analysis of aggregate reports and feedback from receivers.

> Tip: Organisations should ensure that their DMARC record is correctly formatted and published in the DNS before automating policy updates. This can be verified using tools such as dig or online DNS record checkers.

Lists of potential automation triggers include:

* Changes in aggregate report data
* Feedback from receivers
* Updates to organisational email infrastructure
* Detection of spoofing attempts

import dns.resolver

def update_dmarc_policy(domain, policy):
 # Update the DMARC record with the new policy
 dmarc_record = "_dmarc." + domain
 answer = dns.resolver.resolve(dmarc_record, "TXT")
 for rdata in answer:
 # Parse the DMARC record and update the policy
 record = str(rdata)
 updated_record = record.replace("p=none", "p=" + policy)
 # Publish the updated DMARC record
 print(updated_record)

Step-by-Step Guide to Implementing Automated DMARC Policy Updates

To implement automated DMARC policy updates, start by assessing your current DMARC setup. Review your domain's DMARC record, such as the following example:

_dmarc.example.com. IN TXT "v=DMARC1; p=none; rua=mailto:dmarc@example.com; ruf=mailto:dmarc@example.com; fo=1"

Note the p tag, which specifies the policy. In this case, it is set to none, indicating that the domain is currently in monitoring mode.

Next, decide on the update strategy. A common pattern is to start with a monitoring policy, then gradually move to a more restrictive policy, such as quarantine or reject. For example, you may want to update the policy to quarantine after a certain period of time, or when a specific threshold of spam reports is reached.

To automate the updates, you will need to write a script that can parse the DMARC aggregate reports and update the DNS record accordingly. The aggregate reports will show the number of messages that passed or failed DMARC, as well as the sources of the messages. For example:

import xml.etree.ElementTree as ET

# Parse the DMARC aggregate report
tree = ET.parse('dmarc_report.xml')
root = tree.getroot()

# Extract the number of messages that failed DMARC
failed_messages = int(root.find('.//failed').text)

You can then use this data to determine when to update the policy. For example, you may want to update the policy to quarantine when the number of failed messages exceeds a certain threshold.

When updating the DNS record, make sure to use a DNS provider that supports automated updates, such as Amazon Route 53 or Google Cloud DNS. You can use APIs or command-line tools to update the record. For example:

aws route53 change-resource-record-sets --hosted-zone-id Z1234567890 --change-batch '[
 {
 "Action": "UPSERT",
 "ResourceRecordSet": {
 "Name": "_dmarc.example.com.",
 "Type": "TXT",
 "TTL": 300,
 "ResourceRecords": [
 {
 "Value": "\"v=DMARC1; p=quarantine; rua=mailto:dmarc@example.com; ruf=mailto:dmarc@example.com; fo=1\""
 }
 ]
 }
 }
]'

In a hosted or managed setup, the process may be simplified, as the provider may offer automated DMARC policy updates as part of their service.

_dmarc.example.com. IN TXT "v=DMARC1; p=quarantine; rua=mailto:dmarc@example.com; ruf=mailto:dmarc@example.com; fo=1"

A list of key considerations for automated DMARC policy updates includes:

* The frequency of updates, which will depend on the volume of email traffic and the desired level of granularity
* The thresholds for updating the policy, which will depend on the specific use case and the desired level of protection
* The DNS provider's support for automated updates, which will depend on the provider's API and command-line tools

import time

# Update the policy every 24 hours
while True:
 # Parse the DMARC aggregate report and update the policy
 update_policy()
 time.sleep(86400)

Warning: When automating DMARC policy updates, make sure to carefully consider the potential impact on legitimate email traffic. A overly restrictive policy may block legitimate messages, while a too permissive policy may allow spam to pass through. Monitor the effects of the updates closely and adjust the thresholds and frequency as needed.

Monitoring and Adjusting Automated DMARC Policy Updates

To ensure the effectiveness of automated DMARC policy updates, it is crucial to continuously monitor the aggregate reports and adjust the updates as necessary. The aggregate reports will show the number of messages that passed and failed DMARC authentication, which can be used to fine-tune the automated updates. For example, if the reports show a high number of false positives, it may be necessary to adjust the update schedule to reduce the frequency of policy changes.

_dmarc.example.com. IN TXT "v=DMARC1; p=quarantine; rua=mailto:aggrep@example.com"

A common pattern is for receivers to honour the DMARC policy specified in the DNS record, so it is essential to ensure that the automated updates are correctly publishing the intended policy. Receivers typically cache DNS records for a short period, so changes to the DMARC record may not be immediately reflected in the aggregate reports.

import dns.resolver

answers = dns.resolver.resolve("_dmarc.example.com", "TXT")
for rdata in answers:
 for txt_string in rdata.strings:
 print(txt_string.decode("utf-8"))

The output of this script can be used to verify that the automated updates are correctly publishing the DMARC record.

A hosted or managed setup may handle the monitoring and adjustment of automated DMARC policy updates differently, often providing a web-based interface to view the aggregate reports and adjust the update schedule.

> Tip: Regularly review the aggregate reports to ensure that the automated DMARC policy updates are effective in mitigating deliverability issues, and adjust the updates as necessary to maintain optimal deliverability.

Lists of potential issues to monitor include:

* Messages that fail DMARC authentication
* Messages that pass DMARC authentication but are still blocked by receivers
* Changes to the DMARC policy that may affect deliverability

_dmarc.example.com. IN TXT "v=DMARC1; p=reject; rua=mailto:aggrep@example.com"

The aggregate reports will show the impact of these changes, allowing for adjustments to be made to the automated updates to maintain optimal deliverability.

Common Pitfalls and Edge Cases in Automated DMARC Policy Updates

A common pattern is for organisations to overlook the impact of automated DMARC policy updates on their subdomains. For instance, a DMARC record published on the parent domain, such as

_dmarc.example.com. IN TXT "v=DMARC1; p=quarantine;..."

may not be applied to subdomains like subdomain.example.com, unless the subdomain has its own DMARC record or the parent domain's record is explicitly applied to subdomains. Receivers typically honour the DMARC record on the parent domain, unless a subdomain has its own record.

_dmarc.subdomain.example.com. IN TXT "v=DMARC1; p=reject;..."

may override the parent domain's policy. The aggregate reports will show which domains are being used to send emails, helping to identify potential issues with subdomains.

> Warning: when automating DMARC policy updates, it is crucial to ensure that the updates are applied consistently across all domains and subdomains, to avoid inconsistent application of DMARC policies, which can lead to deliverability issues.

In a hosted or managed setup, the provider may handle DMARC policy updates on behalf of the organisation, which can simplify the process but also introduces a layer of complexity in terms of control and visibility. It is essential to understand how the provider handles automated DMARC policy updates and to ensure that their processes align with the organisation's requirements.

Conclusion and Future-Proofing DMARC Policy Updates

To mitigate deliverability issues, it is crucial to implement automated DMARC policy updates, considering the trade-offs between security and deliverability. A common pattern is to start with a p=none policy, then gradually move to p=quarantine and finally p=reject. The aggregate reports will show the effectiveness of the updates, helping to identify potential issues.

_dmarc.example.com. IN TXT "v=DMARC1; p=quarantine; pct=100; rua=mailto:aggrep@example.com"

A hosted or managed setup typically handles the automation of DMARC policy updates, but it is essential to monitor the updates and adjust as necessary to avoid deliverability issues.

Tip: Regularly review the aggregate reports to ensure the automated DMARC policy updates are effective and not causing unintended deliverability issues.

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