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Palo Alto Networks PSE-Strata Exam - Topic 2 Question 111 Discussion

Actual exam question for Palo Alto Networks's PSE-Strata exam
Question #: 111
Topic #: 2
[All PSE-Strata Questions]

Access to a business site is blocked by URL Filtering inline machine learning (ML) and

considered as a false-positive.

How should the site be made available?

Show Suggested Answer Hide Answer
Suggested Answer: C

Contribute your Thoughts:

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Ricki
2 months ago
D could work, but it might be too broad of a change.
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Henriette
2 months ago
I disagree, C is more effective for exceptions.
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Georgeanna
2 months ago
B seems like the best option to me.
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Fabiola
3 months ago
Wait, can we really trust ML to not block legit sites?
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Jesus
3 months ago
A would just disable security, not a good idea!
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Ashley
3 months ago
Changing the action of the real-time detection category seems like it could help, but I’m not confident if that’s the best option.
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Merrilee
3 months ago
I'm not entirely sure, but I feel like adding it as an exception in the inline ML profile could work. It sounds familiar.
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Laura
4 months ago
I remember practicing a similar question where we had to create a custom URL category. That might be the right approach here.
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Blair
4 months ago
I think disabling URL Filtering inline ML might be too drastic. We need to keep some level of protection, right?
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Lisbeth
4 months ago
Creating a custom category and adding it to the ML profile exception seems like the safest bet. I'll go with that.
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Margery
4 months ago
Disabling the URL filtering ML seems like a risky move. I'll see if I can find a more targeted solution.
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Virgilio
4 months ago
Okay, I think I've got a strategy here. I'll try creating a custom URL category and adding it to the security policy.
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Tijuana
5 months ago
Hmm, I'm a bit unsure about this. I'll have to review the URL filtering settings and ML profile in more detail.
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Ranee
5 months ago
This seems like a tricky one. I'll need to think through the different options carefully.
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Alesia
7 months ago
D, all the way! Change the action of the real-time detection category on the URL filtering profile. What could go wrong? *laughs nervously*
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Arlen
5 months ago
B) Create a custom URL category and add it to the Security policy
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Madalyn
5 months ago
A) Disable URL Filtering inline ML
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Leonora
7 months ago
Ah, the age-old question of URL Filtering and false positives. I'd say go with C, it's the surgical strike approach!
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Emile
7 months ago
Hmm, I'm torn between B and C. But I think C might be the better option since it allows you to keep the inline ML profile intact while making an exception for the site.
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Marica
5 months ago
Yes, that sounds like the best course of action in this situation.
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Sharen
5 months ago
So, should we go ahead and create a custom URL category and add it on exception of the inline ML profile?
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Tracey
5 months ago
Yeah, I agree. It's important to keep the inline ML profile intact while still allowing access to the site.
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Olive
5 months ago
I think C is the better option as it allows you to make an exception for the site.
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Vivienne
7 months ago
I think changing the action of real-time detection category on URL filtering profile could also work.
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Almeta
7 months ago
I'm going with C. Creating a custom URL category and adding it as an exception to the inline ML profile seems like the best approach to me.
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Nu
7 months ago
I agree with Jade, creating a custom URL category and adding it on exception of the inline ML profile seems like a good idea.
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Carlee
7 months ago
Definitely B. Creating a custom URL category and adding it to the Security policy is the way to go. It's the most straightforward and effective solution.
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Nickolas
5 months ago
Let's go with option B then, it seems like the most effective choice.
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Dan
5 months ago
Agreed, creating a custom URL category is the way to go.
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Carmela
6 months ago
I think B is the best option. It's the most direct solution.
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Jade
7 months ago
I disagree, creating a custom URL category and adding it to the Security policy might be a better solution.
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Bulah
7 months ago
I think we should disable URL Filtering inline ML.
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