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Splunk SPLK-5001 Exam - Topic 5 Question 3 Discussion

Actual exam question for Splunk's SPLK-5001 exam
Question #: 3
Topic #: 5
[All SPLK-5001 Questions]

A threat hunter generates a report containing the list of users who have logged in to a particular database during the last 6 months, along with the number of times they have each authenticated. They sort this list and remove any user names who have logged in more than 6 times. The remaining names represent the users who rarely log in, as their activity is more suspicious. The hunter examines each of these rare logins in detail.

This is an example of what type of threat-hunting technique?

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Suggested Answer: A

Contribute your Thoughts:

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Ammie
3 months ago
Co-Occurrence Analysis seems off for this scenario.
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Juliann
3 months ago
Surprised they didn't look at the context of those logins!
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Roslyn
3 months ago
Not so sure about that, could it be Outlier Frequency Analysis instead?
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Paul
4 months ago
I agree, it makes sense to focus on rare logins!
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Tammi
4 months ago
This is definitely Least Frequency of Occurrence Analysis.
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Dortha
4 months ago
Time Series Analysis doesn't seem right either; this is more about the frequency of logins rather than tracking changes over time.
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Xochitl
4 months ago
Co-Occurrence Analysis sounds familiar, but I don't think it applies to this scenario since we're looking at individual logins.
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Rossana
4 months ago
I remember practicing a question about identifying rare behaviors, so Outlier Frequency Analysis could also fit here.
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Lettie
5 months ago
I think this might be related to Least Frequency of Occurrence Analysis, but I'm not entirely sure.
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Carey
5 months ago
Alright, I've got an idea. The threat hunter is focusing on the users who have logged in less frequently, so I'm guessing this is some kind of outlier analysis technique. Let me double-check the options.
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Antonio
5 months ago
Wait, I'm a bit confused. Are we looking for the technique that the threat hunter used, or the type of threat they were trying to detect? I want to make sure I understand the question properly.
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Colette
5 months ago
Okay, let's see. The key seems to be identifying the users who have logged in rarely, as their activity is more suspicious. I think I've got this.
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Jennie
5 months ago
Hmm, this seems like a tricky one. I'll need to think it through carefully to make sure I don't miss any important details.
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Renea
5 months ago
This seems straightforward. The threat hunter is looking for users with low login frequency, which is a type of Least Frequency of Occurrence Analysis. I'm confident that's the right answer.
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Antonio
5 months ago
I'm a bit confused by the options here. I'll need to review my notes on wireless networking modes to figure out the right combination. Gotta make sure I don't overthink this.
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Harley
1 year ago
I'm feeling lucky, so I'm gonna go with 'Outlier Frequency Analysis'. It's like the cybersecurity version of finding a needle in a haystack, but with more hacking and less hay.
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Filiberto
1 year ago
Hah! 'Time Series Analysis'? What is this, a history class? Nah, I'm betting the answer is 'Least Frequency of Occurrence Analysis'. It's all about finding the reclusive login unicorns.
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Whitney
1 year ago
D: Definitely, it's all about finding those outliers in the login data.
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Catrice
1 year ago
C: I think that technique helps to pinpoint suspicious activity more effectively.
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Socorro
1 year ago
Definitely, focusing on those rare logins can uncover suspicious activity.
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Celeste
1 year ago
Yeah, that makes sense. It's like finding the rare login unicorns.
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Mira
1 year ago
B: Yeah, it makes sense to focus on the users who rarely log in.
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Britt
1 year ago
A: I agree, 'Least Frequency of Occurrence Analysis' sounds like the right choice.
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Selma
1 year ago
I think it's 'Least Frequency of Occurrence Analysis'.
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Vicky
1 year ago
I think it's D) Outlier Frequency Analysis because it targets suspicious activity based on low frequency logins.
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Tarra
1 year ago
I'm not sure, but I think it could also be A) Least Frequency of Occurrence Analysis.
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Kimberlie
1 year ago
I agree with Dwight, because the technique focuses on identifying unusual behavior.
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Sharee
1 year ago
I'm gonna go with 'Co-Occurrence Analysis' on this one. Gotta keep an eye on those users who are always hanging out together, you know? They might be up to no good.
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Reuben
1 year ago
I agree with you, it's important to focus on those rare logins to identify any suspicious activity.
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Celeste
1 year ago
I think it's 'Outlier Frequency Analysis'. Those users who rarely log in could be the outliers in this case.
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Sean
2 years ago
Hmm, I'm not sure about this one. Maybe it's 'Outlier Frequency Analysis'? After all, rare logins are kind of like the black sheep of the login family, right? They stand out, so we gotta look into them.
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Wenona
1 year ago
A: Definitely, it's all about identifying those unusual patterns in login activity.
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Frank
1 year ago
B: Yeah, I agree. It's important to focus on those outliers to catch any potential threats.
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Gaston
1 year ago
A: I think you're right, 'Outlier Frequency Analysis' makes sense. Those rare logins could indicate something suspicious.
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Dwight
2 years ago
I think the answer is D) Outlier Frequency Analysis.
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Clay
2 years ago
Wow, 'Least Frequency of Occurrence Analysis' sounds like the perfect answer! I mean, who doesn't love a good ol' 'frequency of occurrence' analysis, am I right? It's like the detective work of the cybersecurity world.
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Nobuko
1 year ago
It's like narrowing down the suspects in a cyber investigation.
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Josue
1 year ago
Definitely, focusing on the rare logins can help identify suspicious behavior.
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Rebecka
1 year ago
Yeah, that makes sense. It's like finding the outliers in user activity.
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Shawnta
1 year ago
I think it's 'Least Frequency of Occurrence Analysis'.
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