Document Password Recovery Master Initializing backend runtime for device #2. Please be patient...
The error message
indicates that there was an insufficient memory condition when initializing the device (such as the GPU), causing the OpenCL command clEnqueueNDRangeKernel() to fail memory ALLOCATION (CL_MEM_OBJECT_ALLOCATION_FAILURE). This is usually related to insufficient available memory on the GPU, possibly due to the following reasons:
Cause analysis
Insufficient GPU memory : Your GPU does not have enough memory to handle the tasks required by Hashcat or other tools. For example, when you try to crack a very large hash file or use very high cracking strength, the memory requirements increase significantly.
Other processes are using GPU memory: There may be other processes running on your GPU that are using a lot of memory, causing Hashcat to be unable to allocate enough memory.
GPU Driver Issues: Sometimes, incompatible GPU driver versions or bugs can lead to memory management issues. Updating the driver may help resolve this issue.
Memory Allocation Limit: Some OpenCL implementations may have size limits on individual memory allocations. If your task requires a single block of memory that exceeds this limit, memory allocation failures will also occur.
Workaround
Reduce attack parameters:
Reduce batch size (
--workload-profileor-nand-uparameters) to reduce memory footprint.Run with a smaller hash list or split a large file into smaller parts.
Close other processes using the GPU:
Confirm that no other processes are using the GPU. You can use Task Manager (Windows) or
nvidia-smi(Linux/Windows, for NVIDIA GPUs) to check the current memory usage.Adjust device selection:
Select different devices (if there are multiple GPUs) by using the
-dparameter.Update or reinstall GPU drivers:
Make sure your GPU drivers are up to date, especially if you are using a newer GPU or operating system version.
Use a lower hash algorithm pattern:
Using a lower pattern, if applicable, may reduce memory requirements.
Add more physical memory:
If you have multiple GPUs, consider adding more physical memory or swapping to a GPU with more memory.
By trying the above methods, you should be able to find a suitable solution to the problem of insufficient memory.