optimizing-attention-flash
Pass
Audited by Gen Agent Trust Hub on Oct 1, 2026
Risk Level: SAFEEXTERNAL_DOWNLOADSCOMMAND_EXECUTIONINDIRECT_PROMPT_INJECTION
Full Analysis
- [SAFE]: The skill is a legitimate technical resource for performance optimization in machine learning. The provided Python snippets for PyTorch and the flash-attn library follow authoritative implementation patterns and lack any malicious intent.
- [EXTERNAL_DOWNLOADS]: The instructions recommend installing well-known, industry-standard packages (
torch,transformers,flash-attn) from official package registries. These dependencies are necessary for the skill's stated purpose. - [COMMAND_EXECUTION]: The skill uses standard system commands for environment diagnostics (
nvidia-smi) and package management (pip,python -c). These operations are appropriate for configuring and verifying hardware support for high-performance computing tasks. - [INDIRECT_PROMPT_INJECTION]: The skill demonstrates processing text sequences through machine learning models, which represents an inherent attack surface for indirect prompt injection.
- Ingestion points: Untrusted text sequences are processed in
references/transformers-integration.mdvia tokenizer and model generation calls. - Boundary markers: The provided code examples do not include specific delimiters or instructions to ignore embedded commands in the input text.
- Capability inventory: The environment allows for package installation and execution of complex machine learning logic using GPU resources.
- Sanitization: The snippets do not demonstrate input sanitization, which is typical for low-level library implementation documentation.
Audit Metadata