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Netskope Exam NSK200 Topic 1 Question 16 Discussion

Actual exam question for Netskope's NSK200 exam
Question #: 16
Topic #: 1
[All NSK200 Questions]

Review the exhibit.

You are asked to create a DLP profile that will ensure that the data shown in the exhibit cannot be uploaded to a user's personal Google Drive.

What must be used to accomplish this task?

Show Suggested Answer Hide Answer
Suggested Answer: B, C

There are two possible scenarios that would cause the behavior of files containing test data for credit cards not triggering DLP events when uploaded to Dropbox. One scenario is that the DLP rule has the severity threshold set to a value higher than the number of occurrences. This means that the rule will only trigger an event if the number of matches for the sensitive data exceeds the specified threshold. For example, if the rule has a severity threshold of 10 and the file contains only 5 credit card numbers, then no event will be generated. To fix this, you can lower the severity threshold or remove it altogether. The other scenario is that the credit card numbers in your test data are invalid 16-digit numbers. This means that the numbers do not pass the Luhn algorithm check, which is a validation method used by Netskope DLP to detect valid credit card numbers. For example, if the number is 1234-5678-9012-3456, then it is not a valid credit card number and will not be detected by Netskope DLP. To fix this, you can use valid test credit card numbers that pass the Luhn algorithm check. The other options are not valid scenarios for this behavior. The Netskope client is not steering Dropbox traffic is not a valid scenario because there are corresponding page events, which means that the traffic is being steered to Netskope.There is no API protection configured for Dropbox is not a valid scenario because API protection is not required for DLP detection on file uploads, which are handled by real-time protection.Reference:DLP Rule Settings1,Credit Card Number Detection2


by Ricki at May 10, 2024, 12:44 PM

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Noelia
1 months ago
I'm just hoping I don't accidentally upload my entire family's financial records to Google Drive. That would be a real 'DLP' moment, am I right? *laughs*
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Kendra
1 months ago
Wait, is this a trick question? I bet the answer is 'all of the above' and the real challenge is finding the most cost-effective solution. *winks*
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Josefa
1 days ago
B) ML image classifier
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Mirta
8 days ago
A) document fingerprinting
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Blair
2 months ago
Hmm, the INTL-PAN-Name rule? Interesting, but I'm not sure that's the right tool for the job. Wouldn't want to get too complicated with this one.
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Amie
24 days ago
C) optical character recognition
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Yuki
1 months ago
B) ML image classifier
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Lilli
1 months ago
A) document fingerprinting
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Sharan
2 months ago
ML image classifier? I don't know, that seems a bit overkill for this task. Optical character recognition might be the simpler and more efficient option.
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Yuette
23 days ago
C) optical character recognition
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Marsha
24 days ago
I agree, optical character recognition would be a more efficient option.
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Maxima
27 days ago
D) INTL-PAN-Name rule
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Tatum
28 days ago
C) optical character recognition
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Malcom
1 months ago
B) ML image classifier
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Justine
2 months ago
A) document fingerprinting
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Sarina
2 months ago
Document fingerprinting sounds like the way to go here. Gotta make sure that sensitive data doesn't end up in the wrong hands on Google Drive.
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Leota
2 months ago
I'm not sure, but I think C) optical character recognition could also be used for this task.
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Shaun
2 months ago
I agree with Eura, document fingerprinting can help prevent the data from being uploaded.
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Eura
2 months ago
I think the answer is A) document fingerprinting.
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