Hate Accounts

February 10, 2022 – Member meeting 1-Bot Sentinel organized hate accounts – 2 log4J with Whitesource

Registration for February 10 7:00 PM PST to 9:00 PM – 2 CPE for full attendance

Session One: Christopher Bouzy – Using machine learning and artificial intelligence to make social media platforms safer. This discussion examines organized hate groups in social media, including a technical and policy discussion.

Visit Bot Sentinel – Dashboard and you’ll be astounding at the actionable data available to risk managers and good social citizens who want a safe social media experience. Why aren’t social media platforms reasonably secure and why is the experience of social media so much worse for some people than others.

You may have read the news about hate accounts that target Meghan Markle, but the effort to expose this coordinated ring of hate accounts is really just the tip of the iceberg.

Learn more at Bot Sentinel – Press

Meet Christopher Bouzy, the founder and CEO of Bot Sentinel. (Speak with Mr. Bouzy via Twitter Christopher Bouzy (@cbouzy) / Twitter
Bot Sentinel is a free platform developed to detect and track propaganda trollbots and untrustworthy Twitter accounts. Bot Sentinel uses machine learning and artificial intelligence to classify suspicious Twitter accounts, and then we store those accounts in a database to track each account daily. We use the data we collect to understand how propaganda accounts influence unsuspecting Twitter users. Our team developed our machine learning model using 2500 ordinary Twitter accounts tweeting about politics, current news, and other various topics. We also used 2500 trollbot accounts we identified by examining the text of their tweets. In total, we used a combined 5,000,000 tweets from ordinary and trollbot accounts to build our model.

Session Two: Do you have insecure Log4j versions in your code? Let’s find out. A hands-on discussion with our friends at WhiteSource

Session Two: Do you have insecure Log4j versions in your code? And how do you fix it easily?  A discussion with our friends at WhiteSource

The recently published critical vulnerability in Apache’s widely popular Log4j Java library (CVE-2021-44228) has sent software development outfits into a tailspin, and additional fix-related CVEs are piling up. 

As is often the case with open source dependencies, it is ubiquitous across open source and third-party applications, meaning that the vulnerable library is most probably used by many applications in your codebase.

Is your codebase vulnerable?

WhiteSource provides a couple of free tools that can quickly scan your projects to find vulnerable Log4j versions and provides the exact path — both to direct or indirect dependencies, along with the fixed version for speedy remediation.

Meet our speakers: Sam Quakenbush and Jack Marsal

Meet Jack Marsal. Jack Marsal has spent the past 18 years working for cyber security and IT security companies covering various domains — application security, endpoint security, network security, email security, and cloud security. He is currently the Sr. Director of Product Marketing for WhiteSource Software. Prior to WhiteSource, Jack has held senior positions at Dynatrace, Armis, CloudPassage, Forescout, McAfee, and Trend Micro. Jack received his MBA and a Bachelor of Science in Engineering from Tulane University.
Sam Quakenbush is the Global Director of Sales Engineering at WhiteSource with over 10 years of experience in development, application security, and consulting. He has traveled all over the world advising customers on how to implement a Secure Software Development Lifecycle using industry leading application security solutions and best practices.

Sam Quakenbush | Global Director – Sales Engineering | WhiteSource
sam.quakenbush@whitesourcesoftware.com | +1.317.902.4132

Is your codebase vulnerable?

WhiteSource Log4j Detect is a free CLI tool that quickly scans your projects to find vulnerable Log4j versions and provides the exact path — both to direct or indirect dependencies, along with the fixed version for speedy remediation.

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