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ThreatFabric Tech Stack

Mobile fraud detection platform powered by threat intelligence and behavioral AI

Computer and Network Security Amsterdam, North Holland 51–200 employees Founded 2015 Privately Held

ThreatFabric detects mobile fraud and malware threats using Python, Java, Kafka, and ML frameworks (TensorFlow, PyTorch, scikit-learn) paired with Android/iOS SDKs. The tech stack reveals a dual focus: streaming data processing (Kafka, PySpark, Pandas) for high-volume threat detection, and mobile client instrumentation (Android, Kotlin, Swift, JNI, C++) for on-device behavior analysis. Active projects on behavior biometrics AI and detection algorithm enhancement signal a shift toward predictive fraud prevention over reactive rule-based systems.

Tech Stack 35 technologies

Core StackKafka Python Java PostgreSQL AWS Docker Redis Maven PySpark Pandas scikit-learn NumPy TensorFlow PyTorch Databricks Kotlin C++ Swift SQL Spring Boot Spring Web Gradle Git Polars Keras Android Android Studio JNI Android SDK iOS+3 more

What ThreatFabric Is Building

◆Challenges

Architectural transitions
Modernization initiatives
Detecting fraud patterns
Enhancing fraud detection
Monitoring detection performance
Processing high volumes of data
Protecting digital products from malware and fraud
Strengthening fraud detection platform
Improving software deployment processes
Secure cloud-native operations

▲Active Projects

Mobile android sdk development
Enhancing commercial mobile services tools
Improving detection algorithms
Developing fraud detection rules
Next-generation behavior biometrics ai system
Testing framework development
Modern qa practices implementation
Ci/cd pipeline improvement
Integration projects with new customers
Shaping new product features through customer feedback

Hiring Activity

Steady10 roles · 4 in 30d

Department

Engineering

6

Product

2

Data

1

Sales

1

Security

1

Support

1

Seniority

Senior

7

Mid

5

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About ThreatFabric

ThreatFabric detects fraud and malware threats across mobile channels by combining threat research with behavioral AI. The company serves financial institutions and digital services providers globally, protecting customer accounts and devices from account takeover, credential theft, and malicious applications. The platform ingests high volumes of mobile telemetry and threat signals through Kafka, processes them with Python/PySpark, and runs inference on TensorFlow and PyTorch models to identify fraudulent patterns in real time. Recent focus areas include architectural modernization, CI/CD pipeline improvements, and expanding behavior-based detection capabilities.

HeadquartersAmsterdam, North Holland

Company Size51–200 employees

Founded2015

Hiring MarketsNetherlands

Frequently Asked Questions

What programming languages does ThreatFabric use?

Primary languages are Python, Java, Kotlin, and Swift. Python powers backend processing (PySpark, pandas, scikit-learn, TensorFlow, PyTorch); Java and Kotlin run Spring Boot services and Android SDK development; Swift handles iOS instrumentation.

What is ThreatFabric working on?

Active projects include next-generation behavior biometrics AI, mobile Android SDK development, improving fraud detection algorithms, CI/CD pipeline modernization, and integrations with new customers. Recent focus areas are architectural transitions and modern QA practices.