Just got pinged at 3 AM because some ad campaign decided to buy traffic from a "premium news aggregator" that was actually just three VMs in a basement serving malware-laden pop-unders. So yeah, the whole "Made for Advertising" (MFA) site list discussion caught my eye.
I'm inherently suspicious of any curated list that promises to fix a supply-side problem. In my infra world, a blocklist is a reactive tool, not a strategy. These MFA lists—like the one from the ANA—are essentially giant YAML files of domains you shouldn't buy. The theory is solid: avoid low-quality, ad-clogged sites that exist only to harvest ad spend.
But from an operational SRE/DevOps lens, I have questions:
* **Freshness:** How often is this list updated? In the time it takes to publish a CSV, a hundred new MFA domains spawn. Are we talking a daily `cron job` or a quarterly manual review?
* **Implementation:** Is this just another static list to ingest into your DSP's blocklist? If so, you're adding thousands of lines of overhead. Hope your platform's config validation doesn't choke.
* **False Positives:** The classic problem. Does their heuristic for "MFA" catch legit long-tail sites? If I'm auto-blocking at scale, I need to know the error rate.
A programmatic approach I've seen teams hack together looks something like this (simplified):
```bash
# Example: Cross-reference your placement logs against an MFA list
# This runs in a pipeline, not manually at 3 AM.
awk -F',' 'NR==FNR{block[$1]; next} !($2 in block)' mfa_domains.csv hourly_placements.log > filtered_placements.log
```
It's a decent first-pass filter. But it's just that—a filter. The real work is in the continuous monitoring and the feedback loop to tune it.
So, are these lists *useful*? Sure, as a starting point or a sanity check. But if you think uploading a list to your ad platform is a "set and forget" solution, I've got a bridge—and a pager alert—to sell you. The useful part is forcing a conversation about automated quality scoring and real-time feedback in your ad infra.
Anyone actually integrating these dynamically? Or is it just more compliance theater that creates config drift?
NightOps
Oof, 3 AM pager duty from an ad buy, that's rough. You're dead on about blocklists being reactive. I see the same thing trying to block spammy sites in my feeds.
Your point about freshness is huge. A static list feels like whack-a-mole. I wonder if the real use is as a baseline for building a dynamic filter, maybe with some automation to check new domains against the core list's patterns. But then you hit the false positive wall.
If the list isn't updated at least daily, is it even worth the config management headache?
dk
You're onto something with the dynamic filter idea. That's basically how we handle malicious IP ranges in our VPC flow logs, using a managed threat list as a seed and then layering our own heuristic checks on top.
But I think the config headache is the real blocker. If you're pulling a new list daily, you need a pipeline to validate, stage, and deploy it without breaking anything. That's a non-trivial amount of Terraform and CI/CD work, and you'll need monitoring for those false positives you mentioned.
Makes me wonder if the value isn't in the list itself, but in forcing a conversation about automation. If your team can't sustain the pipeline to use it, maybe you shouldn't be buying ads on the open exchange anyway.
cost first, then scale
You're right to be suspicious. Treating these lists as static artifacts misses the operational reality. The real question isn't "is the list fresh," but "what's your process for evaluating and integrating any third-party blocklist?"
In our stack, we treat any external list as a data source, not a configuration. It goes into an automated validation pipeline that checks for format changes, runs a subset against a known-good control group to gauge false positives, and only then gets staged for deployment. The list's inherent latency becomes a known parameter in that pipeline, not a surprise.
If you're just uploading the CSV to your DSP, you've outsourced the operational burden without solving it. You still need to monitor for the 3 AM page, because a list from last week won't catch the new batch of basement VMs. The list is only useful if it's part of a system you've built to handle its inevitable shortcomings.
—J
That's a great way to frame it - "data source, not a configuration." It shifts the whole mindset. I'm coming from the marketing side where we'd just upload and hope for the best, but hearing this makes our old process seem naive.
Your validation pipeline sounds critical, especially checking against a known-good control group. How do you define that control group? Is it a small whitelist of your own high-performing sites, or something more nuanced?
My concern from a performance angle is that even a good pipeline might kill some weird but legitimate discovery channels. In my experience, some niche blogs that are fantastic for early-stage conversions look a lot like MFA sites from a pure traffic pattern perspective.