Description:
We are looking for a Senior Security Research Engineer to take on our hardest analysis work and help set the technical direction of the team. Our geographically dispersed team values positivity and inclusivity in the workplace, clear communication, collaborative learning, and guided mentorship.
Our research is public, and much of it is work you may already know: this team identified the supply chain compromise of the axios npm package, uncovered a new Contagious Interview campaign hiding DPRK malware inside SVG images, and published in-depth analyses of the TCLBANKER banking trojan and the PHANTOMPULSE RAT, each one paired with protections that shipped to customers. If you have a passion for taking apart what adversaries build, and would enjoy the challenge of getting that understanding into customers' hands quickly, join our growing team!
What You Will Be Doing:
- Reverse engineer malware nobody has documented yet. Take apart obfuscated and packed samples across Windows, macOS, and Linux, and recover how they communicate, configure themselves, and stay hidden.
- Operate global data systems to identify and mitigate threats. Work through data from millions of endpoints to surface the activity worth investigating, build the campaign context that tells customers who is targeting them, and push mitigation back out across the fleet.
- Turn every discovery into a shipped protection, and the tooling that scales it. Author the signatures that stop what you find, and build the automation and AI-assisted workflows that make the next investigation faster than the last.
- Build your public research reputation. Publish on Elastic Security Labs, release tools and detection artifacts to our public GitHub repositories, and present at conferences. We encourage a public persona and the relationships in the research community that come with it.
- Collaborate across Elastic Security. Your discoveries become the rules and models that neighboring teams build and ship, and you will work with those teams directly on shared threat intelligence and detection engineering projects.
- Help lead the team's technical direction. Take point on investigations that run for months, raise the bar in review, and mentor researchers earlier in their careers.
What You Bring:
- 6+ years of professional experience reverse engineering malware and researching adversary tradecraft, static and dynamic, across multiple executable formats (PE, ELF, Mach-O) and architectures (x86-64, ARM), including obfuscated and packed code that defeats automated tooling.
- Python development experience for research tooling and automation, plus the ability to read C and C++. Malware arrives in Rust, Go, and NodeJS too, so you are willing to learn a new runtime when a sample demands it.
- YARA authorship and hunting at scale. You write signatures that hold up against the next variant, and you can find a weak signal in a very large telemetry dataset.
- Working knowledge of the fundamentals: Windows and Linux internals, network protocols including HTTP and TLS, and enough applied cryptography to recognize what is protecting a configuration blob.
- Technical writing ability. You can turn a long investigation into a clear, public analysis that other defenders can act on.
- You have a proven track record of using AI to accelerate development, debug complex systems, and optimize code, while still owning the final outcomes.
- Proven ability to seamlessly transition between different projects, codebases, or scrum teams based on dynamic business priorities.
- A collaborative mentality, an eagerness to learn new skills and emerging technologies, and a passion for protecting the world's data from attack!
Bonus Points:
- Vulnerability research or novel technique discovery, with a track record of responsible disclosure.
- Participation in CTFs such as FLARE-ON or NetWars.
- Standing in the community: maintaining an open-source security tool, speaking at conferences (e.g., Black Hat, DEF CON, CODE BLUE, Virus Bulletin), or an established publication record.
- Attribution tradecraft, including joint investigations with external intelligence partners and platforms such as MISP or OpenCTI.
- Behavioral detection engineering beyond signatures, or applying machine learning to malware classification.
- Familiarity with the Elastic Stack (Elasticsearch, Kibana) and Elastic Security.