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Netsparker - A False-Positive-Free Web Application Security Scanner
Netsparker web application security scanner automatically exploits detected vulnerabilities to ensure no false positives are reported.
- sebcat 13y agoHow can you have blind-/boolean based SQL injection without any false positives? I would at least expect some level of false positives for these methods as they generally imply causation from correlation.
- 616c 13y agoHow can you have any kind of system without false positives? Even medical tests have false positives, and there is a lot more review than this stuff. But, copy writing is art and science. Keep the fluff away from HN skeptics, and you should be fine. :-)
- jamesaguilar 13y agoWell, if you don't have any positives . . .
- ZirconCode 13y agoYes, the word Free is also highlighted in bold on the homepage, while False-Positive isn't. I assumed it was a free service for a good 5 seconds. If that was intentional or not, I can't tell.
- necmi 13y agoI already using Netsparker for 3 years, they're best solution
- andybak 13y ago4 months on HN and this is your first comment? Hmmmmmmmm.
- andybak 13y agoI'm flagging this. The submitter looks suspicious and so does the first commenter.
- billadoid 13y agoI already using Νetsparker fοr 3 years, they're best solutiοn
- dgroves 13y agoFalse positives are only a part of a matrix of statistical results known as [sensitivity and specificity](https://en.wikipedia.org/wiki/Sensitivity_and_specificity https://en.wikipedia.org/wiki/Sensitivity_and_specificity): * True positive = correctly identified * False positive = incorrectly identified * True negative = correctly rejected * False negative = incorrectly rejected Using these four values, we can actually calculate the likelihood of a given event. However, to have high specificity (low false positives) you must lower sensitivity (false negatives). So what you are doing is reducing a type 1 error in exchange for an increase of a type 2 error. Sensitivity is related to ability to identify positive results! This particularly disastrous in security, since we can determine likelihood from good statistics; and use this in our risk management 'risk = impact * likelihood.'