Machine Learning vs Cryptocoin Miners Description: With the advent of cryptocurrencies as a prevalent economic entity, attackers have begun turning compromised boxes and environments into cash via cryptocoin mining. This has given rise for the opportunity to detect compromised environments by analyzing network traffic logs for evidence of cryptocoin miners. Specifically, I'll be reviewing various ML and statistical analysis techniques leveraged against VPC Flow Logs. This talk will not be a deep dive of the math involved but instead a general discussion of these techniques and why I chose them.

Speaker's Bio: Jonn Callahan is a principal appsec consultant at nVisium. Jonn was previously heavily involved in the OWASP DC and NoVA chapters. He has been working in appsec for half a decade now, initially within the DoD and now commercially with many high-visibility companies. Recently, Jonn has been digging into ML to find ways to bridge it and the security industry in an intelligent and usable fashion.

Abstract

All modern software, but the most trivial one, relies on common libraries to perform routine work. Your software may be bastion of security, exhaustively tested and evaluated, but once a vulnerability is discovered in a library you depend on, all bets are off. These large and pervasive vulnerabilities quickly become popular targets, exploited by everybody from script kiddies, to professional hackers, to state actors. It is no surprise that the use of vulnerable libraries is included in the OWASP Top 10 list. The Australian Signals Directorate (ASD) lists patching operating systems and applications as two of their top four strategies to mitigate security incidents!

During a recent hacking game, we've identified and exploited a vulnerability not anticipated by the developers. One little crack in a widely used library gave us the footing we needed to construct an attack chain of remote code execution, file upload, data exfil, source code disassembly, and branching into a private network, all despite extremely high level of hardening on the target from unintended attacks. We'll share with you how a safe and fun library exploitation can be in the confines of a hacking game, and how there are serious implications for your corporate applications where the stakes are much higher.

Speakers:

Alexei Kojenov is a Senior Application Security Engineer with years of prior software development experience. During his career with IBM, he gradually moved from writing code to breaking code. Since late 2016, Alexei has been working as a consultant at Aspect Security, helping businesses identify and fix vulnerabilities and design secure applications.

Alex Ivkin is a senior security architect with experience in a broad array of computer security domains, focusing on Identity and Access Governance (IAG/IAM), Application Security, Security Information and Event management (SIEM), Governance, Risk and Compliance (GRC). Throughout his consulting career Alex has worked with large and small organizations to help drive security initiatives and deploy various types of enterprise-class identity management and application security systems. Alex is an established and recognized security expert, a speaker at various industry conferences, holds numerous security certifications, including CISSP and CISM, two bachelor’s degrees and a master’s degree in computer science with a minor in psychology.

Add TAL, improve a threat model!

To improve your (threat) modeling career, you need a better (threat) agent (library)! Threat modeling is a process for capturing, organizing, and analyzing the security of a system based on the perspective of a threat agent. Threat modeling enables informed decision-making about application security risk. In addition to producing a model, typical threat modeling efforts also produce a prioritized list of security improvements to the concept, requirements, design, or implementation. In 2009, OWASP posted wiki pages on threat modeling. Although there was the start of a section on threat agents, it has yet to be completed.

Intel developed a unique standardized threat agent library (TAL) that provides a consistent, up-to-date reference describing the human agents that pose threats to IT systems and other information assets. Instead of picking threat agents based on vendor recommendations and space requirements in Powerpoint, the TAL produces a repeatable, yet flexible enough for a range of risk assessment uses. We will cover both the TAL, the Threat Agent Risk Assessment (TARA), how they can be used to improve threat modeling.

Speaker

Eric Jernigan
Information Security Architect
Umpqua Bank

Eric Jernigan is an Information Security Architect at Umpqua Bank and focuses on risk assessment, Secure project support, information security governance, and security awareness. Prior to this, Eric He has also served as an information security manager and adjunct instructor at PCC. He has also served as an active duty Information Warfare Analyst in the Air National Guard in support of NORTHCOM/NORAD. He has almost twenty years of intelligence, counter-terrorism, Information warfare, information security, and compliance experience. His current professional certifications include CISM, CRISC, and CISSP, so love him. A staunch privacy advocate, he hates Facebook.

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