Security Researcher

Key Responsibilities

Own detections end to end: research the behavior, write the logic, validate it, and ship it into our EDR product.
Develop and enhance file-based and behavioral detections for Windows and macOS (YARA, Sigma, and our own behavioral rule formats).
Perform in-depth analysis of malware and adversarial behavior across both platforms to identify detection opportunities.
Map detection coverage against adversary tradecraft (MITRE ATT&CK and real-world campaigns), find the gaps, and prioritize what to build next.
Test and validate detections against real samples and emulated adversary behavior before they reach customers.
Work with the telemetry our agent collects, and tell engineering when it isn’t enough: identify the event sources and sensor capabilities needed to detect what you’re seeing.
Collaborate with engineering teams to incorporate detection logic into our cross-platform security agent.
Hunt for new and emerging threats using threat intelligence platforms (retrohunts, livehunts, and hunting rule development), and turn what you find into shipped coverage.
Contribute to our Vulnerability product as an intelligence researcher: triage newly disclosed CVEs, then enrich and correct the public data behind them (affected version ranges, product and vendor naming, advisory gaps and inconsistencies) so that what we report as vulnerable reflects reality.
Research how vendors version, name, and distribute their software, and develop vulnerability detection methods that match accurately against real-world software inventories.
Build and maintain the tooling and automation your work depends on: analysis pipelines, threat monitoring, sample processing, and rule testing workflows.
Continuously monitor emerging threats and trends across Windows and macOS ecosystems, and surface research-driven recommendations into the product roadmap.
Review teammates’ detection content and help raise the quality bar across the team.
Author blog posts and present findings at industry conferences, and document research clearly for both internal and external audiences.

Qualifications

3–5 years of experience in cybersecurity, with a hands-on focus on detection engineering and malware analysis. Depth on Windows is what the team most needs today; working familiarity with macOS and a willingness to build depth there is expected.
Proven track record building file-based and behavioral detections for endpoints (YARA, Sigma) and shipping them into a product or production environment.
Experience taking a detection from research through testing and release, and maintaining it over time as adversary behavior changes.
Strong understanding of OS internals and endpoint security mechanisms on Windows and macOS (ETW and kernel callbacks, Endpoint Security APIs), and of the telemetry they produce.
Working knowledge of adversary tradecraft and detection coverage frameworks (MITRE ATT&CK).
Experience with malware analysis tools and techniques (Binary Ninja, Ghidra, IDA, WinDbg, Sysinternals, or Mac Monitor).
Experience hunting with threat intelligence platforms (VirusTotal, Google Threat Intelligence, or equivalent), including retrohunting and hunting rule development.
Working knowledge of the CVE and vulnerability data ecosystem (NVD, vendor advisories, CPE and version matching), and a critical eye for where that data is incomplete, ambiguous, or simply wrong.
Proficiency with security-focused scripting and data analysis (Python, PowerShell, Bash, SQL), and comfort working with large sample sets.
Demonstrated ability to communicate research externally through blog posts, conference talks, or published work.

Preferred Qualifications

Experience developing or contributing to EDR or next-gen antivirus products.
Experience with detection-as-code practices: version-controlled rules, peer review, and automated rule testing.
Experience leveraging AI tools to accelerate threat research, detection development, and analysis workflows.
Experience applying machine learning or statistical methods to malware classification, including building and evaluating against labeled sample corpora.
Experience with malware detonation environments, sandboxing, or automated dynamic analysis.
Familiarity with both Windows and macOS threat landscapes and platform-specific attack techniques.
Demonstrated ability to assess and prioritize vulnerabilities using industry-standard frameworks and data sources (severity scoring, exploit prediction, known-exploited catalogs).