Help: Banyan blocks a critical internal tool and support says 'by design'.

They're not wrong about escalating past frontline support, but quantifying the business cost is what actually gets traction. "Team is blocked" is a Tuesday for them. "This is costing $2k/hour" gets a bridge call scheduled.

Your admin tool might be triggering a simple heuristic, like a fixed interval polling loop or an uncommon user agent. Without the raw logs, you're just poking in the dark. Demand those logs. If they can't provide them, you've got a compliance problem, not a technical one.

You're right to be frustrated with that response. It's a deflection that prevents meaningful troubleshooting. When I've encountered similar "smart detection" blocks, the most effective path wasn't arguing about the model, but forcing a procedural bypass.

Instead of asking them to explain the anomaly, submit a formal request to have the specific source IP or service account for your admin tool added to a verified allow list *outside* the anomaly detection engine. Frame it as a temporary measure while they investigate. Their willingness or refusal to accommodate this tells you everything about whether their "design" includes operational flexibility for legitimate business tools. If they won't, you're dealing with a rigid system, not a security partner.

Your experience with the "too regular" polling interval is a textbook example of why anomaly detection needs context. It's essentially punishing predictable, legitimate automation.

> after pushing back three times, they finally admitted

This delay is telling. In my own tests, I've found that consistent polling intervals often produce a high anomaly score on the "periodicity" or "burstiness" feature, but that score should be weighted against other factors like source identity and destination. If their model can't incorporate service account context, it's fundamentally flawed for enterprise use.

Escalating to a security engineer is the correct step, but the goal shouldn't just be an explanation. It should be to get the specific feature weightings for that rule. If they can't share that, you're dealing with an opaque system you'll have to work around permanently.

You're absolutely right about asking for the rule ID or anomaly score. I've found that when you ask for a "transaction ID" or "model decision ID" instead of just an "anomaly score," it sometimes trips a different part of their script and they actually pull up the right dashboard.

The self-signed cert theory is a good one, too. That's tripped up more than one of our internal dashboards. Sometimes it's not even the cert itself, but the tool using an older cipher suite that gets flagged as 'weak' and therefore suspicious.

Oh man, that "working as designed" line is the worst. Had a similar thing with a different vendor where our backup scripts got flagged. It turned out to be the connection duration - the model was trained on short human sessions, not a 300-second cron job. Maybe your admin tool has a similar steady pattern that looks weird to their system?

Escalating past first-line support as others said is the only way. And definitely ask for the specific rule ID or feature that triggered it. If they can't tell you, how can you ever trust it?

Good luck, this stuff is so stressful when you're just trying to do your job.

That initial "working as designed" response is so disheartening, especially when you're just trying to get a tool unblocked. I've been in a similar spot with inventory sync tools getting flagged. The advice about escalating to a TAM or solutions architect is solid, but before you get there, have you checked the user agent string or API path the admin tool is using? I once spent days troubleshooting only to find our internal tool was identifying itself with a developer build string that their system had never seen before, and it flagged the entire user agent as an outlier. It might be something simple like that buried in the headers.

That's a great point about the user agent string. It's such a small detail that can cause a huge headache. I've seen similar issues where a tool's default UA gets flagged simply because it's unique or unknown to their threat database.

It's a double-edged sword, though. While it might be the simple fix, it also highlights a model that's too brittle if a single, non-malicious header field can cause a full block. If you can change the UA and it works, that's a relief but also a bit concerning for what else might trigger a false positive down the line.

The brittleness of a model that overweights a single header is a serious operational risk. I've documented cases where a user agent string change did resolve the block, but it masked the underlying issue. The next regression in their model, perhaps triggered by a common TLS cipher change, would cause another outage.

This is why I insist on getting the specific rule weights during escalation. If "unique user agent" contributes more than 20% to an anomaly score, their model is fundamentally unsuited for environments with legitimate custom tooling. A temporary UA fix just kicks the can down the road.

You're hitting on the core issue: the logging and detection systems are optimized for different goals. The volume-driven logging pipeline strips out the very details the model would need to learn context.

I once had to prove a cron job was legitimate, but the only timestamp we had was connection start. Without the process name or command line, support just saw a "long-lived session from a server." That forced us to instrument our own detailed audit logging *outside* the security tool, which kind of defeats the purpose, right?

Their "by design" answer really means the cost of storing raw logs was prioritized over the operational cost of these false positives.

Yeah, the "silent regression" you mention is so real. That model refresh cycle is a killer for any whitelist that isn't rock-solid static. I had a similar fight with a load testing tool - got an exception for its specific traffic pattern, only to have it fail six weeks later after what they called a "minor detection logic update."

Your point about moving traffic out of the path is spot on. It's often the only permanent fix, but getting that dedicated policy is half technical, half political. In my last gig, we had to treat it like a mini-compliance project: documenting the service account, the exact ports, and the business justification just to get it past their security review.

Oh wow, that "working as designed" response is so frustrating. It feels like they're saying the problem is you, not their detection.

I'm new to this whole B2B software buying space, and I'm actually looking at zero trust vendors for my company. This kind of scenario is exactly what I'm scared of. So even if you have a clear policy, their system can just overrule it with no explanation?

Your question about disabling security features is a good one, but that seems like it defeats the whole point of buying the tool, right? You'd be paying for security you can't use.

You're right, that's exactly what's happening. The policy layer is often just a suggestion box. The real enforcement is in a black-box model you can't see or control.

And yes, disabling features does defeat the purpose. But you're missing the real cost: the hours your team burns doing the vendor's support job, digging through logs they chose not to keep. That's the hidden price of every "smart" tool.

That's the hidden cost that never makes it into the feature matrix. You're paying twice: once for the license, and again in your team's time to act as an unpaid forensic unit.

I've seen teams create entire shadow logging infrastructures just to have the evidence to debate a vendor's false positive. It becomes a bizarre, parallel support system.

Ugh, the "by design" brush-off is the worst, isn't it? I've been there, staring at a blocked service account for a deployment tool.

The trick that eventually worked for us was refusing to talk about the "anomaly" and instead demanding they show us the *exact* log line from their collector that triggered the block. Not the interpreted alert, the raw log. It usually forces them to admit the data feeding their model is either missing context or is based on a single, shaky metric like a TLS fingerprint they've decided is "unusual."

Once you have that, you can sometimes build a whitelist rule so specific it bypasses their model. Something like "allow traffic from this source IP to this destination port where the TLS client hello random value is NOT null." It's a silly workaround, but it proved the point that their model was brittle.

Did you get any raw logs from them at all, or just the canned response?

Yeah, "by design" usually means their detection model is overfitting on something trivial. I've seen this exact thing block legacy service accounts that only talk via a specific TLS version. The system flagged it because "no human ever uses TLS 1.1 from this subnet," but it was a perfectly valid automated process.

Your best bet is to pressure support for the raw metric that flagged the session, not their interpreted "anomaly." It's often something like an unusual JA3 hash or a missing HTTP header. Once you know that, you can sometimes craft a hyper-specific allow rule that sidesteps their model without disabling the whole feature. It's a pain, but it works.