The purpose of this whitepaper is to describe the capabilities provided by the InQuest platform related to identifying the exposure of sensitive information. With the recent explosion of data breach reports in the news, preventing the loss of sensitive data has become an area of focus for many organizations.
Through the construction of statistical models based off of past observations on the commonalities and differences that malicious and benign files tend to share with one another, a properly tuned machine learning algorithm makes a great partner for a signature author, providing insights that a human expert might not have thought of.
Here's what our customers are saying
Prior to having InQuest, file decompression, decoding and post-processing were all manual steps that were very time consuming for us. Now that we're using InQuest, all of those steps are automated and it has given us the ability to apply these steps to not only files we think are suspicious, but all files received by our users.
Having the ability to search historically based on file content is like having our own internal VirusTotal Retrohunt.
The threat score calculation and assignment being performed by InQuest's engine makes it easy for us to sift through the legitimate sessions and focus on the real threats targeting our users.
InQuest provides a complete network forensics picture, from session details such as header information to file details such as the hash, size, type and even the raw file.
The data loss prevention coverage InQuest provides for data-in-transit is second to none.
The InQuest platform is unlike any other network-based security system we've seen. The performance of their native capture engine and analytic capabilities are unparalleled in terms of the throughput it can support and the number of files it can dissect and analyze.
The third-party integrations with multiav and sandbox solutions are seamless. We have never had a security platform that made it so easy to automate all of our static and dynamic file analysis efforts.
Over half of our customer’s traffic is encrypted and InQuest is the first security platform we’ve seen with a specific focus on using SSL related indicators of compromise to detect the bad guy’s infrastructure.
The threat intelligence InQuest is able to gather and disseminate via their reputation and threat feeds has alerted us to numerous customer compromises. They are truly at the cutting edge when it comes to identifying threat actor infrastructure as it is deployed.
It’s pretty amazing that they are able to support capturing, reassembling, processing, storing and inspecting content at speeds over 20Gb without dropping traffic all in a 1U box.
We’ve been customers for several years now and up until the recent acquisition of their appliances we were running their collectors on 4U boxes with flash storage cards. As a result of that acquisition, we went from having to deal with three different vendors to one vendor, reduced our rackspace footprint as well as our power consumption which all resulted in a huge cost savings for us. Kudos to InQuest!
Through their data orchestration and workflow, they’ve made it really easy for us to establish repeatable workflows from within their UI. That has saved our SOC analysts a considerable amount of time and has enabled them to pivot through data from numerous systems all from a single pane of glass.
Introducing the InQuest Malware Discovery Engine (MDE)! A new default-on static analysis integration designed to identify malicious logic embedded in the most commonly used file types. Alerts from this subsystem are automatically factored into the InQuest Threat Score Engine to produce our File and Session Threat Scores.
MDE leverages the AV community to identify garden-variety malware quickly, so InQuest can focus on those hard to detect threats targeting your Enterprise.
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