Alright, so today I’m gonna walk you through something I was messing with recently: figuring out if something smells fishy enough to actually dig deeper. I’m calling it “investigation merits” – basically, does this even warrant our time?
The Backstory
So, I was looking at some logs, just routine stuff, right? But something felt off. A couple of weird errors, a spike in traffic from a strange IP… nothing concrete, but my gut was screaming “SOMETHING’S UP!”. But, you know, you can’t chase every shadow, otherwise you’ll be running around in circles all day.
Step 1: The Initial Sniff Test
First thing I did was try to get a broader view. I pulled some aggregated data. I wanted to see if this was just a one-off thing, or if there was a pattern emerging.
- Checked the error rates: Were those errors isolated, or were we seeing a general increase across the board? I looked at different timeframes (past hour, past day, past week) to see if there was a trend.
- Examined traffic patterns: Is that weird IP just hitting one endpoint, or is it poking around all over the place? I wanted to know the scope of its activity.
- Looked for anomalies: Anything else out of the ordinary? Spikes in resource usage, unusual database queries, anything that didn’t quite fit.
Step 2: Drilling Down on the Weirdness
Okay, so the initial sniff test confirmed that, yeah, something was definitely not right. The error rates were elevated, that IP was all over the place, and there were some weird authentication attempts. Time to get granular.
- Investigated the errors: What were these errors saying? Were they related to each other? Were they exploitable? I traced the errors back to the code to understand what was causing them.
- Analyzed the traffic from that IP: What endpoints was it hitting? What data was it sending? Was it trying to inject anything malicious? I used tools like `tcpdump` and `Wireshark` to capture and analyze the network traffic.
- Checked the user accounts: Were any accounts compromised? Were there any suspicious login attempts? I looked at the audit logs to see who was logging in from where and when.
Step 3: Putting the Pieces Together
At this point, I had a bunch of data points. Now it was time to connect the dots. Was this a targeted attack? A botnet? Just some random script kiddie messing around?
- Looked for commonalities: Did the errors, traffic, and login attempts share any common characteristics? Were they all targeting the same vulnerability?
- Consulted threat intelligence feeds: Was that IP address known to be malicious? Were those error messages associated with any known exploits? I checked sites like VirusTotal and AlienVault OTX.
- Formulated a hypothesis: Based on the data, what was the most likely scenario? What was the attacker trying to achieve?
The Outcome
Turns out, it was a botnet trying to exploit a known vulnerability in one of our older services. Thankfully, we had already patched the vulnerability, but the botnet was still trying to exploit it. So, while it wasn’t a critical issue, it was still something we needed to address.
The Wrap-Up
The key takeaway here is not to ignore your gut feeling. If something feels off, it probably is. But don’t just jump to conclusions. Take the time to gather the data, analyze it, and connect the dots. That’s how you separate the real threats from the noise.
Hope this helps! Lemme know if you have any questions.
