ML: fix panic in featuresToTensorAdvanced for 100/106/110-feature models - #72
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…dels featuresToTensorAdvanced wrote fixed offsets copy(tensor[95:105], ...) and copy(tensor[105:115], ...) unconditionally regardless of the allocated tensor length. LoadONNXModel's auto-detect probe includes sizes 100, 106, and 110 (onnx.go loadONNXModelInternal), all narrower than the fixed 115-index write, so a model auto-detected at one of those sizes panicked with a slice-bounds-out-of-range on the first prediction carrying event history, crashing the analyzer process (engine.Predict runs on the detection goroutine with no recover). Add copyTruncated, which clamps each write to the tensor's actual capacity, and route the fingerprint/behavioral feature copies through it so smaller auto-detected sizes get a truncated but valid tensor instead of a panic. Sizes >=116 are unaffected (the existing branches already guard capacity for those layouts).
awlx
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Aug 8, 2026
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Superseded by and merged through #77, which preserves this contribution and includes the follow-up fixes. Thanks for the contribution! |
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Fix a panic in
featuresToTensorAdvancedfor 100/106/110-feature ONNX models (bounds-clamped feature copy).Validation:
go build ./...clean;go test ./pkg/mlpasses.