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TensorFlow HDF5 Security Research PoCs
This repository contains proof-of-concept .h5 model files for an authorized
security audit under the huntr Model Format Vulnerability program (beta). These
artifacts are for defensive validation and coordinated disclosure only, not for
any production or general-purpose use.
Summary
The bundle currently contains three independent PoCs against TensorFlow's
legacy Keras HDF5 loading path in the audited source tree
(1d0f0c1c525442f9bb0e219ea4714ff94e56b374):
legacy_lambda_rce.h5- Demonstrates benign load-time code execution by writing a fixed marker file
in
/tmp.
- Demonstrates benign load-time code execution by writing a fixed marker file
in
cyclic_inbound_nodes_dos.h5- Demonstrates a load-time hang from cyclic Functional graph replay.
oversized_weight_allocation_dos.h5- Demonstrates load-time allocation pressure from a tiny HDF5 file with a huge declared logical tensor.
Files
legacy_lambda_rce.h5,legacy_lambda_rce.py,legacy_lambda_rce_clean_repro.txtcyclic_inbound_nodes_dos.h5,cyclic_inbound_nodes_dos.py,cyclic_inbound_nodes_dos_repro.txtoversized_weight_allocation_dos.h5,oversized_weight_allocation_dos.py,oversized_weight_allocation_dos_repro.txt
Reproduction
Tested on July 29, 2026.
Run each PoC through the public tf.keras.models.load_model() API from a
network-disabled container with:
TF_USE_LEGACY_KERAS=1 python3 <poc_script.py> <mode>
Where:
legacy_lambda_rce.pygenerates and reproduces in one run,cyclic_inbound_nodes_dos.pyusesgenerateandrepromodes,oversized_weight_allocation_dos.pyusesgenerateandrepromodes.
Note
These artifacts are intended only for defensive validation and coordinated disclosure workflows.