Password Recovery Initializing backend runtime for device #2. Please be patient...
2024-09-05 12:51:49
This error message indicates that a device (e.g. GPU) was initialized with an out-of-memory situation, causing the OpenCL command to fail to allocate memory (). This is usually related to the GPU's lack of available memory, possibly due to the following reasons:clEnqueueNDRangeKernel()CL_MEM_OBJECT_ALLOCATION_FAILURE
Cause analysis
Insufficient GPU memory: Your GPU doesn't have enough memory to handle tasks called for by Hashcat or other tools. For example, when you're trying to crack a very large hash file or using very high crack strength, the video memory requirements increase significantly.
Other processes are taking up GPU memory: There may be other processes running on your GPU that are taking up a lot of video memory and Hashcat is unable to allocate enough memory.
GPU driver issues: In some cases, GPU driver versions are incompatible or have bugs, which may cause memory management problems. Updating the driver may help resolve this issue.
Memory allocation limitations: Some OpenCL implementations may have size limits on individual memory allocations. If your task requires more than a single block of memory for this limit, memory allocation will also fail.
Resolution
Reduced Attack Parameters:
Reduce the batch size (or and parameters) to reduce the memory footprint.--workload-profile-n-u
Use smaller hash lists or split large files into smaller parts.
Shut down other GPU-hogging processes:
Confirm that no other processes are using the GPU. You can use Task Manager (Windows) or (Linux/Windows, for NVIDIA GPUs) to check your current video memory usage.nvidia-smi
Adjust device selection:
Select different devices (if you have more than one GPU) by using parameters.-d
To update or reinstall the GPU driver:
Make sure your GPU drivers are up to date, especially if you're using a newer GPU or operating system version.
Use a lower hashing algorithm pattern:
Using a lower mode, if applicable, may reduce memory requirements.
Add more physical memory:
If you have multiple GPUs, consider adding 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 deal with the problem of low memory.