ewandzdigital Inc.
Android Development | Remote (USA Only)
ewandzdigital Inc.United States6 hours ago
ContractRemote FriendlyOther

Work Mode: Remote (applicable for USA-based candidates)

Minimum Experience Required: 5+ years

 

Job Description 

Requirements: -

Hands on Experience with the following:

•     Review malicious applications and SDKs by analyzing, unpacking and reverse engineering software that compromises Android devices.

•     Static and Dynamic Analysis

•     Experience with ELF (Native Binaries) reverse engineering

•     Experience with Java, Kotlin, JavaScript, Flutter, and other mobile software languages

•     Experience with Reverse Engineering tools such as Jadx, Ghidra, Frida, IDA Pro, Burp, to perform binary and APK analysis

•     Code reviews for security policy violations, vulnerabilities, or improper coding practices

 

 Understanding of the following topics:

• Java Programing Language

• Techniques utilized by malicious software to tamper with user devices and make removal more difficult.

• Android Security Topics

• Mobile App store policies (Ads, PHAs, Developer, etc.)

• Ability to read, comprehend and analyze source code software

• Experience with Vulnerability Analysis

•  Android Development

 

Job Responsibilities will entail: 

· They will conduct reverse engineering, security assessments, and code reviews.

o They will conduct and assist with complex de-compilation, unpacking, code review and malicious mobile software reviews. The goal of the work is to identify families of malware and act on apps at scale.

o They will be responsible for developing static and dynamic signatures for mobile code, binaries, and executable code leading to the detection of a variety of threat types including malware, potentially unwanted programs (PUPs) and advanced persistent threats.

o They are required to write complex reports for consumption of non-technical audiences, review peer reports and assist with investigations.

o They will identify weaknesses in detections and automations and make recommendations for improvements in the detection process and automation pipeline.


 



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