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CodeSan

Financiado

Cerrado

Code Sanitization for Vulnerability Pruning and Exploitation Mitigation

Despite massive efforts in securing software, about 60 security bugs are publicly reported each month. Systems software is prone to low level bugs caused by undefined behavior (memory corruption, type confusion, or API confusion).... ver más

28/02/2025

EPFL

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 2 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2019-09-23

ERC-2019-STG: ERC Starting Grant

I+D

Cerrada hace 6 años

0% 100% 100%

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

2 Participantes

EPFL

1.50M€ | Lider

SIDASA

733.73K€ | Participante

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Duración del proyecto: 65 meses Fecha Inicio: 2019-09-23
Fecha Fin: 2025-02-28

Líder del proyecto

ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 1M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Despite massive efforts in securing software, about 60 security bugs are publicly reported each month. Systems software is prone to low level bugs caused by undefined behavior (memory corruption, type confusion, or API confusion). Exploits abuse undefined behavior to execute attacker specified code, or to leak information. We propose code sanitization (CodeSan), a comprehensive approach to improve code quality. CodeSan will sanitize software by (i) automating bug discovery during development through software testing and (ii) protecting deployed software through reflective mitigations. CodeSan trades formal completeness for practical scalability in three steps: First, policy-based sanitization makes undefined behavior (through violations of memory safety, type safety, or API flow safety) explicit and detectable given concrete test inputs. Second, automatic test case generation increases testing coverage for large programs without the need for pre-existing test cases, enabling broader and automated use of policy-based sanitization. Third, for deployed software, reflective mitigations place runtime checks precisely where they are needed based on data-flow and control-flow coverage from our testing efforts. CodeSan complements formal approaches by protecting software that is currently out of reach due to its size, complexity, or low level nature. CodeSan is a compelling, comprehensive, and adaptive approach to thoroughly address undefined behavior for complex software. The three proposed thrusts complement each other naturally and will immediately guard large software systems such as Google Chromium, Mozilla Firefox, the Android system, or the Linux kernel, making them resilient against attacks. In line with PI Payer’s track record on open sourcing his group’s research artifacts on cast sanitization, transformative fuzzing, or control-flow hijacking mitigations, all prototypes produced during CodeSan will be released as open-source.

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