At 02:40 on a Tuesday, the on-call engineer at a mid-size publisher opens the CDN dashboard and sees one user-agent string dominating the top-talkers list: Bytespider. The Slack channel fills up with the word "attack" within minutes. Someone proposes a blanket block. Someone else asks whether blocking will hurt the SEO team's crawl budget. Nobody has yet answered the first question: is anything actually broken?
Any crawler with a reputation for heavy request volume quickly triggers concern. That reputation is exactly why a spike carrying its name triggers a reflex. The reflex skips three steps: proving that the load hurt readers or the origin, checking whether the label is even true, and choosing a response small enough to reverse.
This guide walks through the incident in that order. It's written for platform engineers, SREs and security leads who sit behind Cloudflare or another CDN and need a defensible decision, not a gut call. The goal is a containment you can explain in the postmortem and a recovery you can measure.
A Bytespider label is a claim, not a diagnosis
A user-agent header is text the client chose to send. Anyone running curl can write Bytespider into it in four seconds. So when your dashboard groups traffic under that name, it's grouping requests that claim a name, nothing more.
That distinction matters because the label drives the story your team tells itself. "Bytespider is hammering us" sounds like a known actor with a known behavior, and it suggests a known fix. "Some clients using the Bytespider string are sending a lot of requests" is a weaker sentence, but it's the accurate one, and it keeps your options open.
Spoofed crawler names are common. Centinel's published research found that 84% of requests claiming to be GPTBot on a typical news site were fake. Those figures come from other crawler names, not Bytespider, so don't read them as a Bytespider rate. They do show how cheap the borrowed-name trick is, and that a famous name in the logs tells you little about who sent the request.
So start the incident with a rule: write the label into your notes as "claims to be Bytespider" until you have evidence for anything stronger. Keep the word "attack" out of the ticket title for now. An attack is a statement about harm and intent, and you've shown neither yet.
Three questions structure everything below. Did the traffic hurt anyone? Who is the requester behind the label? What is the smallest control that fixes the harm? Answer them in that order.
Establish impact before you call it an attack
High request volume is a measurement. Impact is a consequence. Plenty of crawler spikes are loud on a chart and harmless to readers, and a few quiet ones drain an origin. Measure the consequence.
Pull these numbers for the spike window and for the same window one week earlier:
- Origin CPU, connection count and database query latency. Edge-served cache hits cost almost nothing, so a spike that never reaches origin is a bandwidth line item, not an outage.
- Cache hit ratio. Crawlers that walk deep archive URLs or append query strings can bypass cache and land every request on origin.
- Error rates for human-looking traffic: 5xx responses, timeouts, and slow time to first byte on your highest-value pages.
- Rendering and ad-serving delays, if your stack ties them to origin responses.
- CDN egress and request billing, which is a legitimate harm even when readers are fine.
Then make a call, and write it down. If readers saw normal latency and origin stayed under its headroom, you have a cost and policy question, not an incident. You may still decide to limit the traffic, but you can do it on a calm schedule with a robots.txt change and a rate rule, not at 3 a.m. with a block.
If origin latency climbed in step with the spike and 5xx rates rose for ordinary visitors, you have real impact, and urgency is justified. Even then, impact tells you the load is the problem. It doesn't tell you the label is honest.
A useful habit: put a one-line impact statement at the top of the incident doc, with numbers. "Origin p95 rose from 310 ms to 1.9 s between 02:35 and 03:20; cache hit ratio fell from 91% to 64%." That line decides whether you escalate, and it becomes your baseline for the recovery check later.
Separate the claimed name from the requester: what the logs can and cannot show
Now look at who is behind the string. Your logs carry several fields, and they differ sharply in how much they can prove.
The user-agent is the weakest field, because the client writes it. The source IP is stronger, but only if you're reading the right one. Behind a CDN, the peer your server sees is the CDN edge. The client address lives in a forwarded header such as CF-Connecting-IP on Cloudflare, and you should trust that header only when the request arrived through your CDN's network. Check this before you build anything on IP data. A rule keyed to the edge address will either match everyone or no one.
Once you have the real client address, group the Bytespider-labelled requests by source network and ask practical questions:
- Do the addresses cluster in a small number of hosting or cloud networks, or scatter across consumer ISPs?
- Does the same address set also appear under other user-agent strings during the window?
- Does the request pattern look like a crawler (sitemap-driven, steady pacing, robots.txt fetched first) or like extraction (sequential IDs, deep pagination, no asset requests)?
- Do TLS and HTTP characteristics stay consistent across the "same" crawler, or vary from request to request?
An operator-published list of crawler IP ranges, where one exists, is a better identity check than the header. If the operator publishes nothing you can verify against, say so in your notes. Having no verification method is a finding: the name can't be confirmed from your side, and your policy has to rest on behavior and impact instead.
The logs can't show intent or ownership. A residential proxy exit, a shared office address and a real crawler all look like "an IP" in a row. Our post on residential proxy scraper detection covers why an address label alone proves neither a person nor a scraper.
Preserve the raw log slice before you change anything. The scraper incident response guide explains why evidence disappears the moment a block takes effect.
Scope containment: AI Crawl Control, custom rules and log-first testing
Containment should be the smallest change that removes the measured harm. Start with the gentlest tool that could work and move up only when the numbers say so.
If you run Cloudflare, its AI Crawl Control feature (per Cloudflare's documentation, which you should check for your plan) lets you see AI crawlers by name and set a policy per crawler, such as allow or block. This suits the case where the traffic really is a declared AI crawler and your question is policy: do we want this crawler on our content at all? Pair it with robots.txt, which well-behaved crawlers read. Treat robots.txt as a request, not enforcement.
For anything the crawler-level control doesn't cover, write a custom rule. Scope it to the evidence you collected:
- Match the claimed user-agent string AND the path pattern that is hurting origin (for example, archive pagination or search URLs), not the whole site.
- Prefer a rate limit or managed challenge over a hard block for the first pass. Both are easier to undo and both give you data about who responds.
- Exclude paths your real readers and approved crawlers need: article pages for search engines, feeds you syndicate, and any partner integrations.
Then test in log-only mode first. Run the rule for a day, or at least a few hours of peak traffic, and review what it would have matched. Look for surprises: legitimate monitoring tools, partner fetchers, your own staging checks. Our walkthrough on bot false positive testing shows how to verify visitors before you enforce.
Only after the log run looks clean should you flip the rule to challenge or block, and set a calendar reminder to review it. Temporary incident rules have a habit of becoming permanent, then blocking something nobody remembers. Name the rule with the incident ID and the date so the next engineer can find its reason.
What header matching does not do: renamed scrapers and identity
Here's the uncomfortable limit of everything in the previous section: a rule that matches the string Bytespider stops clients that keep using that string. It stops nobody else.
A scraper that wants your content and sees itself blocked changes one header and returns. The same extraction can come back as a generic browser user-agent, from the same infrastructure, ten minutes later. Your dashboard will show the Bytespider line falling to zero and look like a win, while the origin load continues under a different name. This is the most common false ending to these incidents.
The inverse also happens. If a real crawler honors your rule and a lookalike scraper doesn't, you've blocked the cooperative actor and left the abusive one running. Header matching rewards honesty and punishes nothing else.
So watch behavior, not names, after you deploy. Track request volume to the protected paths regardless of user-agent. If total load on those paths holds steady while the labelled traffic drops, the extraction moved, and your rule only changed its costume.
This is the gap Centinel Analytica is built for. It tells real visitors from scrapers that look like them, then applies allow, challenge or block policy through your existing CDN or edge. Your Cloudflare, CloudFront, Akamai or Fastly setup stays in place. The decision rests on what the requester is, not on what it calls itself. Chasing a list of user-agent strings is the alternative, and the list is always one rename behind.
For publishers weighing what to allow and what to refuse, the AI crawler policy template gives a starting structure that separates stated policy from enforcement.
Validate recovery for readers and origin
A quiet dashboard is not recovery. Recovery means the harm you measured in the impact step is gone and nothing new broke. Check both halves.
First, compare against the baseline line you wrote at the start. Within an hour of the rule going live, you want to see origin p95 latency back near its pre-spike value, cache hit ratio recovering, and connection counts under their headroom. If the labelled traffic dropped but origin metrics didn't move, the load was never the labelled traffic, and you've been treating the wrong thing.
Second, look for collateral damage. Pull the same reader-facing numbers you used for impact: 5xx rates, challenge-solve rates if you used challenges, and bounce or session counts on article pages. A fall in sessions that tracks your rule's start time is a false positive until proven otherwise. Check your search engine crawl stats too, since an overly broad rule can quietly block the crawlers you want. Verify real Googlebot by reverse DNS, not by the user-agent string, for the same reason this whole article distrusts names.
Third, watch for displacement over the next two to three days. Extraction that moves under a new name will show up as sustained request pressure on the same URL patterns from new source networks. If you see that, your containment worked on the label and failed on the behavior, and it's time for the next tier of controls rather than another header tweak.
Close the loop with a short written verdict: impact confirmed or not, what was changed, what the metrics did afterward, and whether the rule stays, narrows or goes. A rule with no verdict is technical debt with a date on it.
Incident notes to keep and when to escalate beyond header rules
Good notes turn a stressful night into a reusable playbook. Keep these, in this order:
- The impact statement with before and after numbers, and the exact time window.
- The raw log slice, stored outside the system you're about to change.
- The distinction between the claimed name and anything you verified about the requester, including which header you trusted for the client IP and why.
- Each rule you added: its match conditions, its action, its mode (log, challenge, block), the date, and the owner.
- What the log-only run would have matched, including any legitimate hits you excluded.
- The recovery verdict and the planned review date.
These notes are also your evidence if a partner, a legal team or an executive asks why a crawler was blocked.
Escalate beyond header and path rules when any of these hold: the load returns under a different user-agent after you contain the first one, source addresses rotate faster than you can list them, the traffic targets login, checkout or API routes where a false positive costs revenue, or the extraction is of content you license or sell. At that point you're no longer managing a named crawler. You're separating real visitors from software that imitates them, and static string rules can't do that job.
For ecommerce teams, the price scraping protection guide shows how to test controls on product pages. For publishers, bot mitigation for publishers covers handling unknown crawlers at the edge.
Conclusion
Treat the next spike labelled Bytespider as a hypothesis to test, not a verdict to act on. Measure impact first, record the name as a claim, contain narrowly, and confirm that readers and origin recovered before you close the ticket.
If your containment ended with the Bytespider line dropping while load on the same paths stayed flat, header rules have reached their limit. Then use the 30-minute demo to look at how Centinel applies allow, challenge or block policy through the CDN you already run, based on what the requester is rather than what it calls itself.
Frequently asked questions
Is Bytespider traffic always a real ByteDance crawler?
No. The Bytespider name arrives in a user-agent header, and any client can type that string. Treat it as a claim until you verify the requester through an operator-published IP list or behavior. Centinel's research found 84% of GPTBot-labelled requests on a typical news site were fake, which shows how often crawler names get borrowed.
How do I tell whether a Bytespider spike is actually hurting my site?
Compare origin CPU, database latency, cache hit ratio and reader-facing 5xx rates for the spike window against the same window a week earlier. If readers saw normal speed and origin kept headroom, it is a cost or policy issue, not an outage. Write the before and after numbers into the incident notes.
Will blocking the Bytespider user-agent stop the scraping?
Only if the client keeps using that name. A scraper can change one header and return from the same infrastructure. After any header rule, watch total request volume on the affected paths. If it holds steady while the labelled traffic falls, the extraction moved. Centinel Analytica tells real visitors from scrapers rather than relying on the declared name.
Should I test a bot rule before turning on a block?
Yes. Run the rule in log-only mode through a peak period and review what it would have matched, looking for partner fetchers, monitoring tools and your own checks. Then move to a challenge or rate limit before a hard block, and name the rule with the incident ID so it can be reviewed later.
Can I add bot protection without replacing Cloudflare?
Centinel Analytica states that it works alongside Cloudflare, CloudFront, Akamai and Fastly, and that your CDN or WAF stays in place. It applies allow, challenge or block policy through your existing CDN or edge. Readers should confirm integration details for their own setup during the demo.