llm-torch-profiler-analysis

No direct evidence of malware (e.g., exfiltration, backdoor, destructive actions) is present in this fragment. However, the script significantly increases supply-chain execution risk by using --trust-remote-code and by generating and injecting a TensorRT-LLM py_executor Python override into a container. Tokens are also propagated to multiple subprocesses. If the called scripts or remote model repositories are compromised, this harness could execute attacker-controlled code. Recommend reviewing the referenced runner scripts (run_*_profile_host.sh) and make_trtllm_py_executor_override.py, and avoid or strictly control --trust-remote-code for untrusted model sources.