Thesis topic: Tracing Data Exposure in Agentic AI
FramnaSammanfattning
Framna is seeking final-year master's students for a thesis project focused on the privacy implications of agentic AI systems. Located in Stockholm, students will collaborate with a team of developers, designers, and analysts while working on real-world challenges. The project involves analyzing data flows in AI setups and developing tools for auditing privacy risks. This opportunity allows students to engage in a supportive environment, enhancing their learning experience while contributing toJobbet i korthet
Anställningstyp
visstid
Det här erbjuder vi
Collaborative work environment with experienced professionalsAccess to social and learning activitiesOpportunity to produce impactful researchEngagement with industry leaders and innovative projects
Ansök senast: Öppet tillsvidare
Publicerad: 2026-08-28
Beskrivning
Are you a final-year master's student looking for a thesis project that blends real-world impact with cutting-edge tech?
At Framna, we are passionate about creating digital products that shape markets and make everyday life better - and we want you to be part of it.
Every year, we welcome a group of master's students into our Stockholm studio to spend their final semester with us. You will sit alongside our developers, designers, testers, analysts, and product delivery leads, get a place to sit in our cozy office, and join our social and learning activities - from lunch-and-learns to our weekly Friday demos and AWs. It is a chance to do your thesis in a collaborative setting, surrounded by people who are happy to share what they know.
Background
AI agents can now autonomously browse the web, run code, call APIs, and interact with external services. But as these systems become more capable, a critical question emerges: what data are they actually sharing, and with whom?
Most attention has focused on what users consciously share with their AI provider. Far less is understood about the data that agents transmit as a side effect of doing their job, through web search, documentation lookups, package registries, browser automation, and third-party tools.
In this thesis project, you will instrument real agentic AI setups to observe how data moves during task execution, build a threat model for the privacy risks that emerge, and develop a prototype tool for auditing and visualising those data flows.
What you will do
Some potential tasks within this thesis include:
Who you are
This thesis may suit you if you:
About Framna
Framna means 'to bring forward' in Old Norse. And that is exactly what we do. We partner with industry leaders (and those about to be) to create excellent digital products that define markets, reshape industries, and deliver meaningful impact.
Born from the union of digital agencies Bontouch, Move, and Shape, Framna emerged from a strong, product-led culture. Today, over 600 of us collaborate across ten studios in Denmark, the Netherlands, Poland, Sweden, Switzerland, and the US.
Every day, millions of users around the world rely on the products we help shape. From seamless payments to daily commutes, from better health management to smarter shopping. Our work supports more than €150 million in daily transactions and consistently earns an average App Store rating of 4.5.
Together with some of the world's most ambitious brands, including Essity, SJ, Swish, and SEB, we craft products that lead markets and push boundaries. Because when products win, businesses win. We call it Win by product.
Our hiring process
Do you want to meet the team in person? Join us on September 17th for our Master's Thesis Evening! You will hear more about our upcoming thesis topics, meet the team behind our projects, and get a feel for how we work at the intersection of creativity and technology. Sign up here!
Department Students Role Master Thesis Locations Stockholm Employment type Temporary
At Framna, we are passionate about creating digital products that shape markets and make everyday life better - and we want you to be part of it.
Every year, we welcome a group of master's students into our Stockholm studio to spend their final semester with us. You will sit alongside our developers, designers, testers, analysts, and product delivery leads, get a place to sit in our cozy office, and join our social and learning activities - from lunch-and-learns to our weekly Friday demos and AWs. It is a chance to do your thesis in a collaborative setting, surrounded by people who are happy to share what they know.
Background
AI agents can now autonomously browse the web, run code, call APIs, and interact with external services. But as these systems become more capable, a critical question emerges: what data are they actually sharing, and with whom?
Most attention has focused on what users consciously share with their AI provider. Far less is understood about the data that agents transmit as a side effect of doing their job, through web search, documentation lookups, package registries, browser automation, and third-party tools.
In this thesis project, you will instrument real agentic AI setups to observe how data moves during task execution, build a threat model for the privacy risks that emerge, and develop a prototype tool for auditing and visualising those data flows.
What you will do
Some potential tasks within this thesis include:
- Selecting one or more agentic AI setups where the tool layer runs locally and the model is accessed remotely, and instrumenting them to observe communication and data flows during realistic tasks
- Planting uniquely identifiable canary strings in a synthetic test project and tracking where they appear in outgoing traffic
- Mapping information flows between the LLM, local files, tools, operating system, browser, and external services
- Identifying network communication, API calls, telemetry, and other potential data leakage channels
- Developing a threat model and categorization of privacy risks specific to agentic AI systems
- Implementing a lightweight auditing or visualisation tool that records and presents data flows during an agent execution
- Producing recommendations for building more privacy-preserving agentic AI systems
Who you are
This thesis may suit you if you:
- Are interested in cybersecurity, privacy engineering, or agentic systems
- Are curious about how AI agents behave under the hood, and what they might reveal without meaning to
- Enjoy instrumentation, systems analysis, and building tools that surface hidden behaviour
- Plan to start your master's thesis project in January 2027
- Have the opportunity to work from our Stockholm studio
About Framna
Framna means 'to bring forward' in Old Norse. And that is exactly what we do. We partner with industry leaders (and those about to be) to create excellent digital products that define markets, reshape industries, and deliver meaningful impact.
Born from the union of digital agencies Bontouch, Move, and Shape, Framna emerged from a strong, product-led culture. Today, over 600 of us collaborate across ten studios in Denmark, the Netherlands, Poland, Sweden, Switzerland, and the US.
Every day, millions of users around the world rely on the products we help shape. From seamless payments to daily commutes, from better health management to smarter shopping. Our work supports more than €150 million in daily transactions and consistently earns an average App Store rating of 4.5.
Together with some of the world's most ambitious brands, including Essity, SJ, Swish, and SEB, we craft products that lead markets and push boundaries. Because when products win, businesses win. We call it Win by product.
Our hiring process
- Psychometric assessment - personality and logic test
- Interview with our recruiter
- Case assignment
- Case interview
Do you want to meet the team in person? Join us on September 17th for our Master's Thesis Evening! You will hear more about our upcoming thesis topics, meet the team behind our projects, and get a feel for how we work at the intersection of creativity and technology. Sign up here!
Department Students Role Master Thesis Locations Stockholm Employment type Temporary
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Thesis topic: Tracing Data Exposure in Agentic AI
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