T08 · Insecure Dependencies
Note
- Location
- requirements.txt:1
- Finding
- Unpinned Third-Party Dependency Permits Unreviewed Package Changes## Vulnerability Details **File Location**: `requirements.txt:1`; installation instructions at `README.md:53` and `SKILL.md:171-177` **Vulnerability Type**: Unpinned third-party dependency **Risk Level**: Low **Complete Code Snippet**: ```text numpy ``` The associated installation instructions use: ```bash pip install numpy ``` ### Technical Analysis The project declares `numpy` without a fixed version or integrity hash. Following the documented installation procedure therefore causes `pip` to resolve a mutable package version at installation time rather than a release that was reviewed with this Skill. This does not demonstrate that the legitimate NumPy package is malicious. However, it weakens dependency reproducibility and exposes installations to future upstream compromise, repository-account compromise, unsafe index configuration, or incompatible package changes. No lock file, package hash, or explicit package index is provided to constrain resolution. ### Attack Path 1. A user follows the documented `pip install numpy` instruction or installs from `requirements.txt`. 2. `pip` contacts its configured package index and resolves the dependency at that time. 3. If the configured index, package metadata, maintainer account, or selected release has been compromised, an attacker-controlled distribution may be downloaded. 4. Installation hooks or imported package code execute with the permissions of the user running the installation or Skill. 5. The malicious dependency could access any files, credentials, or network resources available to that account. This path is conditional on compromise or unsafe configuration of the dependency source; the audited repository itself does not retrieve a remote payload directly. ### Impact Assessment Successful supply-chain exploitation could result in arbitrary code execution under the installing user's account. The accessible scope would include that user's files, envir ...[truncated 314 chars]
- Remediation
- ## Remediation Suggestions 1. Pin NumPy to a reviewed version or narrowly bounded compatible range. 2. Generate a hash-locked requirements file, for example with `pip-compile --generate-hashes`. 3. Install with hash enforcement: ```bash python3 -m pip install --require-hashes -r requirements.txt ``` 4. Document use of the official Python Package Index or an organization-controlled package mirror. 5. Install dependencies inside a dedicated, non-privileged virtual environment. 6. Add automated dependency vulnerability and update review, rather than accepting new releases implicitly.