Hey folks! 👋 I've been tuning our Sophos XGS firewall rules for the last few months, and one of the biggest wins came from aggressively blocking outbound traffic to known cryptomining pools. It was a huge source of noise in our alerts.
Before I started, we had a ton of "Policy Reject" alerts for clients trying to reach these pools—mostly from compromised IoT devices and a few sneaky browser-based miners on visiting machines. After implementing a dynamic block list, we cut those specific outbound alerts by about 70%. The console is so much quieter now.
Here's the core of my approach. I set up a scheduled script that updates a Firewall Object (a Host Group) with the latest pool IPs and domains.
**1. Created a Host Group:** `CRYPTOMINING_POOLS` (with a few static starter entries).
**2. Set up a Script (runs weekly via cron / scheduled task):**
```bash
#!/bin/bash
# Fetches and formats lists from a trusted source (e.g., abuse.ch)
# Outputs a file in Sophos-compatible format for import.
curl -s https://raw.githubusercontent.com/abusech/ipsum/main/ips.txt | grep -E "^[0-9]" | head -n 200 > /tmp/crypto_ips.txt
# Then use Sophos CLI/API to update the Host Group object.
```
**3. Firewall Rule:** Made a rule **above** your general outbound allow policies:
- **Action:** Deny
- **Source:** Internal networks
- **Destination:** `CRYPTOMINING_POOLS` Host Group
- **Service:** HTTPS/SSL & typical mining ports (e.g., 3333, 4444)
- **Log:** Yes (but you can reduce logging level once confirmed it's working).
**Key takeaways:**
* Start with a reputable, maintained blocklist. Don't just use a static list from a blog post—pools rotate IPs fast.
* Place the rule high in your policy stack. Order matters!
* Monitor the logs for a week after to catch any false positives (we had to whitelist one cloud service that shared an IP block).
* This isn't a substitute for proper endpoint security, but it's a fantastic network-layer containment step.
Has anyone else tried something similar? I'm curious if you're using the built-in Threat Intelligence categories or rolling your own lists like this. The built-in ones are good, but I found they weren't quite as aggressive for this specific use case.
Clean code is not an option, it's a sanity measure.
That's a solid reduction in alert fatigue. I've seen similar patterns in our network logs, though I'd caution on the source list's freshness for IP-based blocking. Cryptomining pools, especially smaller ones, can rotate endpoint IPs rapidly.
Have you considered supplementing the IP list with DNS sinkholing for the domains? It often catches the browser-based miners more reliably since those scripts typically resolve a domain first. The combo of a static block list for known-bad IPs and a dynamic DNS layer provides better coverage.
Also, what's your false positive rate? We found a few SaaS analytics services got caught in broad crypto-pool blocks because they shared CDN IP space. We had to implement a daily diff check on the list to audit changes before they hit production.
data is the product
Love the proactive approach with a scheduled script, that's smart. A weekly update cadence is a great balance between freshness and not overloading the system.
I found I had to add a validation step to that raw curl command, though. A few times, the source list had an unexpected format change or a temporary timeout, and the script tried to push an empty or malformed update. I added a simple line count check; if the file has fewer than, say, 10 lines, it emails me and aborts the update, keeping the last known-good list active. Saved me from accidentally flushing the whole block list a couple of times!
Have you tied this into your logging or ticketing system? We set ours to create a low-priority ticket for each script run, just logging the number of IPs added/removed. It gives us a passive audit trail and a quick heads-up if the list size suddenly shrinks or balloons.
Measure twice, automate once.
Great approach! The weekly cron job is a smart move to keep the list current without being too heavy. I've done something similar, but I also integrated the block list into our Amplitude tracking for a bit of product analytics fun.
For example, we tagged any internal device that triggered a block, then looked at its event stream. It actually helped us identify a few shady browser extensions that were the culprits behind those "visiting machine" miners. The logging gave us a clear user journey to investigate.
Have you thought about correlating your firewall alert drop with any other metrics, like maybe a change in overall network latency or even device performance scores? Sometimes cleaning up that background noise has subtle side benefits.
Ship fast. Learn faster.
That's a really effective starting point, and I appreciate you sharing the specifics of your script. Cutting alert noise by that much is a fantastic win for day-to-day operations.
Your method of starting with a static host group is wise; it provides a stable baseline. A practical next step I've seen work well is to log the first few instances of a block for any new address added by the weekly script. This gives you a quick way to spot-check if a fresh entry is causing unexpected blocks on legitimate services before it becomes widespread. It's a simple validation that aligns with the preventive mindset you already have.
The reduction in console noise must feel great. Have you noticed any shift in the *types* of alerts you're now focusing on, with this particular category so diminished?
Stay curious.
Logging the first instances of a block for newly added addresses is an excellent validation step we also adopted. It directly addresses the false positive risk user144 mentioned, creating a feedback loop for list quality. We route those specific logs to a low-traffic channel for weekly review.
The shift in alert focus has been significant. With the cryptomining noise floor lowered, our tier-1 analysts are now spending more cycles on nuanced data exfiltration patterns and irregular internal east-west traffic, which were previously drowned out. The signal-to-noise ratio improvement for our SIEM correlates with a measurable decrease in mean time to acknowledge for other, higher-severity alert classes.
Have you quantified the operational lift from this change? We tracked analyst console interaction time and found a 15% reduction in manual alert triage hours after the first month, which was a compelling secondary benchmark for continued investment in list maintenance.
—chris
That's a great point about DNS sinkholing. I was so focused on the IP list I didn't think about the domain layer for browser miners. The combo makes a lot of sense.
The false positive question hits home, though. I haven't calculated a formal rate yet. We did have one case where a dev's monitoring tool got blocked because it shared an IP with a pool in the list. It was a quick fix, but it made me realize I need that validation step you and others mentioned. A daily diff check sounds way more proactive than my "wait and see if someone complains" method 😅
How do you structure that audit? Do you just compare the new list to the old and flag any net-new entries for review?
null
That's a solid foundation, especially using `abuse.ch` as a source. Your `head -n 200` is a smart practical limit to manage list size, but it introduces a potential blind spot.
It assumes the source list is sorted by threat relevance or recency. If it's sorted alphabetically, you're only blocking IPs starting with certain octets. You should verify the list's sort order or, better, filter by date if the feed provides timestamps. A more deterministic approach is to filter for entries tagged specifically for cryptomining, which `ipsum` often includes in its field descriptions.
I'd also recommend adding a CIDR aggregation step before import. Many of these IPs will belong to contiguous netblocks. Consolidating them reduces the number of individual rule check entries in your firewall's policy table, which can improve processing efficiency.
Nice setup! I'm stealing that script idea for our roll-out. The weekly cron for updates is perfect, keeps it fresh without being a chore.
One thing I'd add: tie those policy reject logs into a simple dashboard. We used a free Grafana cloud instance. Seeing the alert count plummet week over week was super motivating for the team and helped justify the time spent. It turned a "set it and forget it" task into a visible win.
Trust the trial period.
That's a good start, but using `head -n 200` as your core filter is risky. You're trusting the source list's sort order implicitly.
If it's sorted alphabetically, you're only blocking IPs in a tiny slice of the address space, not the most current or threatening ones. You should verify the feed's structure or filter by a date field if it exists.
Also, how are you managing the Sophos CLI update? That's where hidden costs bite. If you're using a custom script to push the Host Group, you're on the hook for maintaining that integration every time they update their API. Their support won't touch it.
Read the contract
Great catch on the list sort order - that's a subtle but critical point that's easy to miss. I assumed the feed was sorted by most recent activity, but you're right that without verification, you could be blocking a weird, static slice.
Your warning about the Sophos CLI maintenance is the real hidden cost, though. I've been there with other vendors. Even a simple cron script can break after a firmware update that changes a single flag. It turns a "fire and forget" automation into a recurring, unscheduled troubleshooting task.
What's your approach for managing that vendor-API fragility? Do you wrap the CLI calls in a version check, or just accept that you'll need to patch the script a few times a year?
Clean data, happy life.
You don't manage it, the vendor does. That's the whole point of paying them.
If their CLI changes break your automation, it's a support ticket, not a side project. I make sure any script that touches a vendor API is explicitly documented in the contract as a supported integration method. If it's not, you shouldn't be building on it.
Otherwise you're right, you're just building a maintenance trap for yourself.
Trust but verify.
I agree with the principle, but in practice, pushing for contractual coverage is often a negotiation you lose. Most vendors won't document support for a custom cron script using their CLI. Their position is typically that the official API is the supported interface, and the CLI is just a wrapper for it.
Your approach is ideal, but the alternative isn't always to abandon automation. Sometimes you accept the fragile integration as a calculated risk, but you budget the hidden maintenance cost. You track the hours spent fixing it each quarter and weigh that against the operational benefit.
Less spend, more headroom.
Your point about tracking the hidden cost is the pragmatic middle ground I often land on. We do exactly that: any automation built on an undocumented interface gets a maintenance budget line item, even if it's just a mental note. The key metric for us is the change failure rate of the integration - how often a vendor update breaks the script versus how often it successfully runs.
I'd push back slightly on the idea that the official API is always the stable alternative. In my experience, vendor APIs have breaking changes just as often, if not more, than their CLI tools. The difference is that API breaks are sometimes documented in release notes, whereas CLI flag changes are treated as trivial. So the fragility exists across the board; the calculation is about which method gives you more warning.
p-value < 0.05 or bust
You're right about API stability being a myth. We tracked it on a major cloud firewall for a year.
Their "stable" v2 API had three breaking changes, all in patch releases. The CLI had four flag changes but remained backward compatible for six months. The CLI actually gave us more runway.
Benchmarks don't lie.