If you’ve encountered the string “185.63.253.2pp” in a web server log, firewall alert, analytics report, or moderation queue, it can look suspicious at first glance. After all, it resembles an IP address, and IP-like strings often show up during investigations. However, the extra letters at the end—“pp”—change the meaning significantly. In fact, this exact format is not a standard IP address representation. Therefore, the smartest first step is to interpret the string correctly before you block anything or escalate an incident.
This article explains what 185.63.253.2pp likely represents, why it shows up, how to normalize it safely, and what practical steps you can take if it appears in your environment. Along the way, you’ll also learn why “dirty indicators” like this can cause false positives, wasted time, or ineffective blocks if they aren’t handled carefully.
1) Why “185.63.253.2pp” is not a normal IPv4 address
To begin with, a standard IPv4 address contains only numbers and dots, split into four parts (octets), such as:
203.0.113.88.8.8.8185.63.253.2
In contrast, the string “185.63.253.2pp” includes letters. Because of that, it fails strict IP validation in nearly every tool that expects a real IPv4 literal. Consequently, if you copy this string into a firewall rule, a WAF allow/deny list, or an IP reputation checker, it may be rejected—or worse, it may be stored as a meaningless string that doesn’t block anything.
That said, the presence of letters doesn’t mean the entire string is useless. Instead, it usually means the IP portion is real and the suffix is extra metadata. So, when you see “185.63.253.2pp,” the most likely “real” IP is:
185.63.253.2
Meanwhile, “pp” is typically a tag, a formatting artifact, or an obfuscation trick.
2) Why do letters like “pp” get appended to an IP?
There are several common reasons this happens. Importantly, most of them are not mysterious. Rather, they come from how data is logged, exported, copied, or labeled.
A) Log formatting and parsing quirks
In many systems, data is logged as a series of fields. However, if a delimiter is missing—or a parser misreads field boundaries—two adjacent fields can merge. For example, you might have a row like:
- IP:
185.63.253.2 - Tag:
pp
Then, a broken export or copy/paste step produces:
185.63.253.2pp
As a result, you see a single token that looks like an IP with junk attached.
B) Human shorthand and internal labels
Sometimes, “pp” is added intentionally by a human reviewer. For instance, teams may label traffic sources with short codes such as:
vpnbotproxypp
Additionally, “pp” might mean “proxy pool,” “private proxy,” “policy profile,” or some internal abbreviation. Even so, there is no universal definition. Therefore, you should treat “pp” as a local label unless you know the tool or workflow that generated it.
C) Mild obfuscation to bypass simplistic filters
In more suspicious cases, the suffix is used to dodge naive pattern matching. For example, a low-quality filter might block anything that matches a strict IP regex. However, if an attacker appends letters, the string might avoid detection in casual moderation or poorly designed scripts. Thus, “pp” could be a simple way to hide an IP in plain sight.
Nevertheless, obfuscation is not automatically proof of malicious intent. Instead, it’s a signal that you should look at behavior and context.
3) The correct way to handle this: preserve raw data, normalize the indicator
When investigating, you should do two things at once. First, keep the original string for traceability. Second, extract the clean IP for analysis and enforcement.
Specifically:
- Observed value (raw):
185.63.253.2pp - Normalized indicator (actionable):
185.63.253.2
By doing this, you avoid several common mistakes. For example, you won’t accidentally block a non-existent “IP,” and you also won’t lose the original evidence that explains how the string appeared.
Moreover, normalization helps with correlation. After all, your SIEM, WAF, firewall, and application logs will generally store IPs in clean formats. So, you want your indicator to match what those systems can understand.
4) Why you might see an address like 185.63.253.2 in the first place
Once normalized, the IP may appear to belong to hosting infrastructure rather than a home ISP. Generally speaking, hosting IPs are used for servers, VPN exits, reverse proxies, and automated systems. Therefore, they show up frequently in logs—sometimes for legitimate reasons and sometimes for abuse.
Legitimate reasons (common and normal)
For example, the IP might be tied to:
- Monitoring services (uptime checks and availability probes)
- API integrations (server-to-server communication)
- VPN exit nodes used by real users
- Corporate gateways where many employees share one outbound IP
- Crawlers and bots that are not necessarily harmful
In other words, hosting IP ≠ attack by default.
Suspicious reasons (also common)
On the other hand, the same kinds of networks are often used for:
- Credential stuffing and brute-force login attempts
- Comment spam and form spam
- Vulnerability scanning (probing for common admin paths)
- Aggressive scraping and content harvesting
- Exploit attempts against known plugins or misconfigurations
Accordingly, you should judge the IP based on actions, not assumptions.
5) How to decide whether it’s harmless or malicious
The most reliable method is to review behavior. In particular, look for patterns rather than isolated events.
A) Request volume and timing
First, check how often it appears:
- A single request per day is usually low risk.
- Repeated bursts over minutes can be suspicious.
- Constant traffic at a steady high rate may indicate automation.
Additionally, compare it to your baseline. If your site normally receives 5 login attempts per hour and suddenly receives 500, that’s a meaningful anomaly.
B) Targeted endpoints
Next, inspect which URLs were requested. For instance, repeated hits to the following are often associated with scanning:
/wp-admin/,/wp-login.php/.env,/config,/backup.zip/phpmyadmin,/administrator- random long paths producing 404s
Similarly, repeated access to sensitive endpoints—admin panels, XML-RPC, password reset routes—can indicate malicious intent.
C) Authentication activity
Then, correlate with login events:
- Many failed logins across many usernames suggests credential stuffing.
- Many failed logins on one account suggests brute forcing.
- Repeated password resets can signal account takeover attempts.
Consequently, even moderate traffic can become “high risk” if it targets authentication.
D) User-agent and header patterns
Also, check request headers:
- Empty or nonsensical user agents often indicate scripts.
- Constantly changing user agents with identical behavior can indicate bot rotation.
- Missing typical browser headers can suggest automation.
That said, some legitimate tools use minimal headers. Therefore, interpret these signals together rather than in isolation.
E) Status codes and outcomes
Finally, analyze results:
- Many 404s can indicate probing.
- Many 401/403s can indicate credential guessing or blocked attempts.
- Many 200s on unusual endpoints can indicate successful enumeration.
As a result, status codes provide a quick “intent snapshot” of what the traffic is doing.
6) Practical responses you can implement immediately
Once you’ve assessed the behavior, choose a proportional response. In general, start with the least disruptive control and escalate only if needed.
If it looks like mild bot traffic
For example, if you see repeated page hits but no login abuse:
- Enable rate limiting on sensitive routes.
- Add bot challenges (CAPTCHA) to forms.
- Use WAF rules for common scanning patterns.
Additionally, consider blocking by behavior (rate, path, method) rather than by IP alone, since hosting IPs can be shared.
If it looks clearly malicious
For instance, if you see brute force, scanning, or spam:
- Temporarily block the normalized IP (
185.63.253.2) for 24–72 hours. - Block repeated access to known sensitive paths.
- Tighten authentication controls: 2FA, lockouts, and anomaly alerts.
Moreover, blocking at the CDN/WAF layer is often safer than blocking at the server, because it reduces load and provides better visibility.
If you’re uncertain
Then prioritize monitoring and evidence gathering:
- Add a short-term alert for repeated triggers from the same IP.
- Log request details more verbosely for suspicious routes.
- Watch for recurrence across multiple days.
In many cases, uncertainty is temporary; behavior becomes clearer with a bit more data.
7) Why “dirty indicators” cause real operational problems
Strings like “185.63.253.2pp” matter because they can break automation. For example, if your blocklist pipeline expects clean IPv4 values, the suffix can prevent enforcement entirely. Likewise, correlation rules may miss matches if the indicator isn’t normalized.
Common mistakes include:
- Blocking the raw string (which won’t match any real network traffic)
- Ignoring the indicator because it fails validation
- Losing context by stripping everything and forgetting where it came from
Therefore, treat the raw value as evidence and the normalized IP as the actionable data. This approach makes both compliance and incident response smoother.
8) A clear interpretation you can use in reports
If you need a concise explanation for a ticket, report, or client update, you can use something like this:
“185.63.253.2pp is not a valid IP format. It likely represents the IP address 185.63.253.2 with an appended tag (‘pp’) caused by logging, labeling, or minor obfuscation. We normalized the indicator to 185.63.253.2 and evaluated activity based on request patterns, endpoints targeted, and authentication outcomes.”
In summary, that statement explains the “what,” the “why,” and the “how” in a way that’s easy to audit.
Final summary
- 185.63.253.2pp is not a standard IPv4 address, because it contains letters.
- Most likely, the actual IP is 185.63.253.2, and “pp” is extra text.
- Accordingly, you should preserve the raw string for evidence and normalize the IP for action.
- Then, determine risk by analyzing behavior: request rate, targeted endpoints, login attempts, headers, and outcomes.
- Finally, respond proportionally using rate limits, WAF/CDN controls, authentication hardening, and temporary blocks when warranted.
If you want, paste a few representative log lines (with any private tokens removed). Then I can help you classify the behavior as normal traffic, scanning, or brute force—using only the information you already have.
