Cyber Range training

The Fraunhofer Cyber Range combines complex attack simulations with the latest findings from applied research, expert training and the presentation of innovative security tools. Companies can improve the performance of their security teams with realistic attack simulations.

 

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Errors and vulnerabilities in software cause damage running into billions, can ruin a company's reputation and, in the worst case, endanger the safety of people. That's why the Fraunhofer SIT developed VUSC – the code scanner. VUSC (for VUlnerability SCanner) helps companies and developers to detect vulnerabilities in code within minutes.

 

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App security testing tool

Most apps, be they for internet shopping, gaming or social networking, are aimed at private users. But there are hidden risks for businesses. A new test framework will help to uncover gaps in app security and detect malware.

 

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Projects

ChatGPT or human author?

ChatGPT or human author?

Whether application letters, school essays or program codes - with the text AI ChatGPT, texts of all kinds can be generated automatically within seconds. Fraunhofer SIT is researching ways to help recognize texts created with ChatGPT. Among other things, our text forensic experts work with a self-developed method for authorship verification, COAV. This is used to calculate the distances between texts using similarities of text modules and typical consecutive letter strings: Is the text closer to GPT or closer to a human?

Projects

No Patch, no Trust: iOS Data Flow Restriction Bypasses

No Patch, no Trust: iOS Data Flow Restriction Bypasses

The number of ways to bypass iOS data flow restrictions meanwhile has further increased, but Apple still does not fix them. So, the question is: How trustworthy are iOS MDM restrictions if even simple tricks to bypass them are not closed by Apple? Read about new ways to circumvent Apple's iOS MDM Dataflow restrictions and consequences for enterprises on the Appicaptor blog.

Projects

AI against Money Laundering

AI against Money Laundering

In the new research project MaLeFiz (Machine Learning for the Identification of Conspicuous Financial Transactions), researchers are working on a solution that uses machine learning – an artificial intelligence technique – to improve the search for illegal money flows and make it more precise. In addition, the project partners are developing minimum requirements and control mechanisms for Artificial Intelligence solutions used in the financial industry.

Job offers

Fraunhofer SIT seeks scientific staff, partly also for management positions

You will be responsible for planning, leading, executing and representing applied R&D projects, jointly with clients and partners from industry, government agencies and academia.