sambapipe.py

Upload and load a shared object file on a vulnerable Samba server

$ sambaPipe.py -so [path/to/file.so] [domain]/[username]:[password]@[target]

$ sambaPipe.py -so [path/to/file.so] -hashes [LM_HASH:NT_HASH] [domain]/[username]:[password]@[target]

$ sambaPipe.py -so [path/to/file.so] -k -no-pass [domain]/[username]:[password]@[target]

$ sambaPipe.py -so [path/to/file.so] -dc-ip [dc_ip] [domain]/[username]:[password]@[target]

$ sambaPipe.py -so [path/to/file.so] -port [port] [domain]/[username]:[password]@[target]

python sambapipe.py [OPTIONS] <input_file>
Alternatively, if made executable and in PATH:
sambapipe.py [OPTIONS] <input_file>

-h, --help
    Displays a help message and exits. Useful for understanding the specific implementation's options.

-i <file>, --input <file>
    Specifies the input SAM or BAM alignment file to be processed.

-o <file>, --output <file>
    Defines the path for the output processed SAM, BAM, or VCF file.

-r <file>, --reference <file>
    Path to the reference genome FASTA file, essential for many downstream analyses.

-t <num>, --threads <num>
    Sets the number of CPU threads or cores to be used for parallel processing, speeding up tasks.

--filter <criteria>
    Applies specific filtering rules to reads, such as minimum mapping quality, removing duplicates, or unmapped reads.

--sort-order <order>
    Specifies the desired sort order for the output BAM file (e.g., coordinate, queryname).

--skip-qc
    Option to skip initial quality control steps if already performed.

sambapipe.py is typically a Python script designed to act as a bioinformatics pipeline or a component within one, primarily focused on the processing and analysis of Sequence Alignment/Map (SAM) and Binary Alignment Alignment/Map (BAM) files. These files are standard formats in genomics, storing high-throughput sequencing reads aligned to a reference genome.

As a non-standard command, its exact functionalities vary significantly depending on its specific implementation, often developed for particular research projects or institutional workflows. Common tasks performed by such a script might include: initial quality control, filtering reads based on mapping quality or flags, sorting and indexing alignment files, merging multiple BAM files, performing variant calling, or preparing data for downstream analyses like SNP detection, structural variant identification, or expression quantification.

It serves to automate complex, multi-step bioinformatics workflows, integrating various command-line tools such as samtools, bcftools, BWA, or GATK into a cohesive pipeline, thereby streamlining data processing and ensuring reproducibility. Users should refer to the specific script's documentation or source code for precise usage and options.

sambapipe.py is not a standard, pre-installed Linux command. It is typically a custom Python script developed for specific bioinformatics projects or pipelines. As such, its exact functionality, available options, and dependencies can vary wildly between implementations.

Users must consult the specific script's documentation, source code, or the project maintainers for accurate usage instructions. Running an unknown sambapipe.py script without understanding its purpose and origin could lead to unexpected data processing, incorrect results, or security risks. It often requires a Python environment with specific libraries and external bioinformatics tools (e.g., samtools, bcftools) installed and accessible in the system's PATH.

A common workflow automated by sambapipe.py might involve:

1. Input: Raw FASTQ files (or pre-aligned SAM/BAM).
2. Alignment: Aligning reads to a reference genome using tools like BWA.
3. SAM/BAM Processing: Converting SAM to BAM, sorting, indexing, merging, and removing duplicates using samtools.
4. Quality Control: Filtering reads based on mapping quality, read length, or other metrics.
5. Variant Calling: Identifying genetic variations (SNPs, indels) using tools like bcftools or GATK.

The concept behind scripts like sambapipe.py emerged with the advent of high-throughput sequencing and the subsequent explosion in genomic data. As the volume and complexity of sequencing data grew, manual processing became impractical. Bioinformaticians began developing custom scripts, often in Python due to its versatility and rich ecosystem, to automate multi-step workflows involving alignment files (SAM/BAM).

These scripts typically integrate existing, specialized command-line tools (like samtools, BWA, GATK) into a single, cohesive pipeline, enabling researchers to efficiently process raw sequencing reads through alignment, quality control, variant calling, and other analyses. sambapipe.py represents this common practice of creating project-specific or laboratory-specific pipelines to standardize and streamline bioinformatics data processing.

samtools(1), bcftools(1), bwa(1), python(1)