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Jason T Geffner

from Seattle, WA
Age ~41
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Also known as:
Jason R
Related to:
Ethyl H GeffnerLouis GeffnerBarry GeffnerWes Geffner
Connected to:
Evan B Geffner, 28Adam C Geffon, 51Karen A Geffon, 50Wayne H Geffon, 55Adeline A Geffrard, 43Anna K Geffrard, 43Christina Geffrard, 31Ilsonet A Geffrard, 41Jurlean W Geffrard, 70Lynda Geffrard, 59

Jason Geffner Phones & Addresses

  • Seattle, WA
  • 1605 Nash Ave, Austin, TX 78704
  • 17426 Bothell Way NE, Bothell, WA 98011
  • Los Gatos, CA
  • Baldwin, NY
  • Fayetteville, NY
  • 360 Nueces St APT 1616, Austin, TX 78701

Work

Company: Devnetwork Aug 2018 Position: Advisory board member

Education

Degree: Bachelors, Bachelor of Science School / High School: Cornell University 2000 to 2004 Specialities: Computer Science

Skills

Computer Security • Penetration Testing • Reverse Engineering • Malware Analysis • Security • Vulnerability Assessment • Security Research • Network Security • Application Security • Web Application Security • Internet Security • Information Security • Operating Systems • Cloud Computing • X86 Assembly • Cryptography • Ida • Viruses • Security Audits • Network Forensics • Assembly • Manufacturing • Cybersecurity

Industries

Computer & Network Security

Resumes

Resumes

Jason Geffner Photo 1

Senior Architect, Information Security

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Location:
Austin, TX
Industry:
Computer & Network Security
Work:
Devnetwork
Advisory Board Member
Google Dec 1, 2016 - Nov 2017
Senior Security Engineer - Team Lead
Electronic Arts (Ea) Dec 1, 2016 - Nov 2017
Director, Security Engineering'); Drop Table Contacts
Google Aug 2016 - Dec 2016
Senior Security Engineer
Crowdstrike Aug 2015 - Aug 2016
Principal Security Researcher
Education:
Cornell University 2000 - 2004
Bachelors, Bachelor of Science, Computer Science Edith Cowan University
Skills:
Computer Security
Penetration Testing
Reverse Engineering
Malware Analysis
Security
Vulnerability Assessment
Security Research
Network Security
Application Security
Web Application Security
Internet Security
Information Security
Operating Systems
Cloud Computing
X86 Assembly
Cryptography
Ida
Viruses
Security Audits
Network Forensics
Assembly
Manufacturing
Cybersecurity

Publications

Us Patents

Automated Malware Signature Generation

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US Patent:
8201244, Jun 12, 2012
Filed:
Sep 19, 2006
Appl. No.:
11/523199
Inventors:
Ning Sun - Bellevue WA, US
Patrick Winkler - Redmond WA, US
Chengyun Chu - Redmond WA, US
Hong Jia - Redmond WA, US
Jason Geffner - Bothell WA, US
Tony Lee - Sammamish WA, US
Jigar Mody - Bellevue WA, US
Frank Swiderski - Seattle WA, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06F 12/14
G08B 23/00
US Classification:
726 22, 726 1, 726 2, 726 3, 726 23, 726 24, 713165, 713167, 713193
Abstract:
Automated malware signature generation is disclosed. Automated malware signature generation includes monitoring incoming unknown files for the presence of malware and analyzing the incoming unknown files based on both a plurality of classifiers of file behavior and a plurality of classifiers of file content. An incoming file is classified as having a particular malware classification based on the analyzing of incoming unknown files and a malware signature is generated for the incoming unknown file based on the particular malware classification. Access is provided to the malware signature.

Stateless Bi-Directional Proxy

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US Patent:
20070079366, Apr 5, 2007
Filed:
Oct 3, 2005
Appl. No.:
11/242562
Inventors:
Jason Geffner - Bothell WA, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06F 15/16
US Classification:
726012000
Abstract:
A system and a method for redirecting data packets, the system comprising a stateless bi-directional proxy for redirecting data packets, said data packets including a header and a body, said header including a source address that identifies the source of the data packet and a destination address that identifies the destination of the data packet. The stateless bi-directional proxy comprises: a first and second input/output interfaces for receiving and sending data packets; a storage component for storing source and destination addresses; and a processing component for changing the source and destination addresses of the received data packets to stored source and destination addresses.

Binary Function Database System

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US Patent:
20080250018, Oct 9, 2008
Filed:
Apr 9, 2007
Appl. No.:
11/784801
Inventors:
Jason Geffner - Bothell WA, US
Ning Sun - Bellevue WA, US
Brad Albrecht - Snohomish WA, US
Tony Lee - Sammamish WA, US
Pat Winkler - Redmond WA, US
Chengyun Chu - Redmond WA, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06F 17/30
US Classification:
707 6
Abstract:
A binary function database system is provided in which binary functions are extracted from compiled and linked program files and stored in a database as robust abstractions which can be matched with others using one or more function matching heuristics. Such abstraction allows for minor variations in function implementation while still enabling matching with an identical stored function in the database, or with a stored function with a given level of confidence. Metadata associated with each function is also typically generated and stored in the database. In an illustrative example, a structured query language database is utilized that runs on a central database server, and that tracks function names, the program file from which the function is extracted, comments and other associated information as metadata during an analyst's live analysis session to enable known function information that is stored in the database to be applied to binary functions of interest that are disassembled from the program file.

Automated Malware Signature Generation

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US Patent:
20120260343, Oct 11, 2012
Filed:
Jun 1, 2012
Appl. No.:
13/486518
Inventors:
Ning Sun - Bellevue WA, US
Patrick Winkler - Redmond WA, US
Chengyun Chu - Redmond WA, US
Hong Jia - Redmond WA, US
Jason Geffner - Bothell WA, US
Tony Lee - Sammamish WA, US
Jigar Mody - Bellevue WA, US
Frank Swiderski - Seattle WA, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06F 21/00
US Classification:
726 24
Abstract:
Automated malware signature generation is disclosed. Automated malware signature generation includes monitoring incoming unknown files for the presence of malware and analyzing the incoming unknown files based on both a plurality of classifiers of file behavior and a plurality of classifiers of file content. An incoming file is classified as having a particular malware classification based on the analyzing of incoming unknown files and a malware signature is generated for the incoming unknown file based on the particular malware classification. Access is provided to the malware signature.

Automated Malware Signature Generation

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US Patent:
20190073476, Mar 7, 2019
Filed:
May 29, 2018
Appl. No.:
15/991163
Inventors:
- Redmond WA, US
Patrick Winkler - Redmond WA, US
Chengyun Chu - Redmond WA, US
Hong Jia - Redmond WA, US
Jason Geffner - Bothell WA, US
Tony Lee - Sammamish WA, US
Jigar Mody - Bellevue WA, US
Frank Swiderski - Seattle WA, US
International Classification:
G06F 21/56
Abstract:
Automated malware signature generation is disclosed. Automated malware signature generation includes monitoring incoming unknown files for the presence of malware and analyzing the incoming unknown files based on both a plurality of classifiers of file behavior and a plurality of classifiers of file content. An incoming file is classified as having a particular malware classification based on the analyzing of incoming unknown files and a malware signature is generated for the incoming unknown file based on the particular malware classification. Access is provided to the malware signature.

Irrelevant Code Identification

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US Patent:
20150033339, Jan 29, 2015
Filed:
Jul 29, 2013
Appl. No.:
13/953608
Inventors:
- Laguna Niguel CA, US
Jason Geffner - Austin TX, US
Assignee:
CrowdStrike, Inc. - Laguna Niguel CA
International Classification:
G06F 21/56
US Classification:
726 23
Abstract:
The techniques described herein identify, and/or distinguish between, legitimate code and/or irrelevant code in programs so that an analyst does not have to spend additional time sifting through and/or considering the irrelevant code when viewing the code of the program. Therefore, the analyst can be more efficient when determining a type of a program (e.g., malware) and/or when determining the actions of the program. For instance, a security researcher may be tasked with identifying the malware and/or determining the harmful or deceptive actions the malware executes on a computer (e.g., deletion of a file, the targeting of sensitive information such as social security numbers or credit card numbers, etc.).
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Jason T Geffner from Seattle, WA, age ~41 Get Report