This is the artifact associated with the paper "Mitigating Injection Attacks against Encrypted Applicationsvia View-Based Partitioning". It consists of a Python library that implements a view-based partitioning framework for mitigating injection attacks in E2EE applications and the associated evaluation pipeline used to produce the results in the paper. It includes: Filesystem partitioner (Section 5.1) injection_attacks_mitigation_framework/end_to_end/dedup_files.py injection_attacks_mitigation_framework/partitioner/types/filesystem.py Multi-stream deduplication library (Section 5.1) injection_attacks_mitigation_framework/multi_stream/dedup.py SQLite application-layer and data-layer partitioners (Section 5.2) injection_attacks_mitigation_framework/end_to_end/compress_sqlite*.py injection_attacks_mitigation_framework/partitioner/types/sqlite*.py XML application-layer and data-layer partitioners (Section 5.2) injection_attacks_mitigation_framework/end_to_end/compress_xml*.py injection_attacks_mitigation_framework/partitioner/types/xml*.py Multi-stream compression library (Section 5.2) injection_attacks_mitigation_framework/multi_stream/compress.py Evaluation pipeline, including scripts to generate fresh synthetic data and evaluate framework implementations (Section 7.1) evaluation/data_generation evaluation/data_population The synthetic data specifically used by our experimental evaluation (Section 7.2) evaluation/helper_data evaluation/stats