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Sentinel-IR 0.4 adds Python support, native-code detection, SHA-256 audit logging and 484 tests

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Sentinel-IR is a tool that turns source files into a compact structural representation for AI agents, and version 0.4 extends it to Python. The release adds detection of unsafe deserialization, such as pickle loads and certain yaml, joblib and torch calls, along with flagging of native-code access like ctypes and FFI packages. Calls are resolved through a file's imports, so aliased or indirect invocations are still caught. The MCP server now includes an audit log secured with SHA-256 hashing. All components are released under the Apache-2.0 license, with the test suite growing to 484 tests.

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