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Active HORIZON European Commission

A Principled Plan to Prevent Transient Execution Attacks

€2.5M EUR

Funder European Commission
Recipient Organization Stichting Vu
Country Netherlands
Start Date Jan 01, 2025
End Date Dec 31, 2029
Duration 1,825 days
Number of Grantees 1
Roles Coordinator
Data Source European Commission
Grant ID 101141972
Grant Description

Ghostbuster is a research program to stop advanced transient execution attacks, which by themselves already rank among the most advanced attacks everby finding vulnerable code fragments, analyzing them for exploitability, and injecting mitigations where needed.

The vulnerabilities such as Spectre, Meltdown and others originate in vulnerable hardware and allow data leakage across all security boundaries.

Recently, my team and I showed that even more advanced attacks exist by combining transient execution with traditional software exploitation. Today, we have no way of even detecting these hybrid attacks, let alone stop them.

While we keep finding new variants, vendors have indicated that they cannot fix them all, as it would cripple performance.

The hope is that developers identify and harden vulnerable code snippets (e.g., with instructions that stop transient execution).

Unfortunately, finding vulnerable snippets is hard, beyond the abilities of top programmers, and even more so for the new hybrid attacks.

Can it be done automatically?The challenge is daunting and involves all interaction between the code and a myriad of obscure CPU resources, requiring expertise in hardware, operating systems, fuzzing, program analysis, etc.

State-of-the-art (and limited) tools do not even aim for mitigation and simply report potential issueswith many false positives and negatives.

Unlike existing solutions that detect the snippets through pattern matching, Ghostbuster takes a principled approach and considers the fundamental conditions enabling attackswithout resorting to, say, symbolic execution, which scales poorly to large programs.

It models the fundamental conditions of (steps of) an attack in terms of control + dataflow properties and translates the models into detectors.

After detecting the code that looks vulnerable, it runs additional (possibly heavy-weight) exploitability analysis and, if need be, mitigates the issue by removing some of the enabling conditions

All Grantees

Stichting Vu

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