Skip to content

feature: automatically identify code removed previously for being malicious. #95

Open
@AngeloD2022

Description

@AngeloD2022

A couple ideas for approaching this (just spitballing, possible better solutions exist as well):

  • taking a cryptographic hash of a file (language agnostic but inflexible to minor code changes)
  • computing a locality-sensitive hash of the malicious file using opcode disassembly or AST features (python-specific)
    • the similarity of another file to a known malicious hash could be taken using the Levinshtein distance of the hash of a file with a known malicious file's hash.

This would obviously require a database of some sort (and committing thereto malicious file hashes in response to reports).

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions