T08 · Insecure Dependencies
Warning
- Location
requirements.txt:1- Finding
Unpinned Third-Party Dependencies Permit Unreviewed Package Releases
- Content
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Vulnerability Details
File Location:
requirements.txt:1-5,clawhub.json:14-20, andSKILL.md:57-61
Vulnerability Type: Supply-chain exposure through non-reproducible dependency resolution
Risk Level: MediumComplete Code Snippets
requirements.txt:1-5:text nba_api>=1.2.0 pandas>=2.0.0 numpy>=1.24.0 matplotlib>=3.7.0 requests>=2.31.0clawhub.json:14-20:json "pip": [ "nba_api>=1.2.0", "pandas>=2.0.0", "numpy>=1.24.0", "matplotlib>=3.7.0", "requests>=2.31.0" ]SKILL.md:57-61:markdown ## Dependency Installation ```bash pip install nba_api pandas numpy matplotlib requeststext ### Technical Analysis The project specifies only minimum dependency versions and does not provide an exact lockfile or package integrity hashes. The installation command in `SKILL.md` is even less restrictive because it contains no version constraints at all. Consequently, separate installations may resolve to different and previously unreviewed package releases. Python packages can execute code during installation and whenever imported. If an allowed upstream package release or its distribution channel is compromised, installation can introduce attacker-controlled code even though the audited project source remains unchanged. This is a supply-chain risk rather than evidence that any currently named package is malicious. The audit also found that `requests` and `matplotlib` are declared but are not directly imported by the project scripts. Unless they are required transitively or for an undocumented feature, retaining them unnecessarily expands the dependency and vulnerability surface. ### Attack Path 1. An attacker compromises the publisher account, build pipeline, or distribution artifact of one of the allowed dependencies and publishes a malicious version that satisfies the open-ended constraint. 2. A user or automa ...[truncated 1202 chars]- Remediation
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Remediation Suggestions
- Pin every direct dependency to an exact, reviewed version rather than using minimum-version constraints.
- Generate and commit a reproducible lockfile that also resolves and pins all transitive dependencies.
- Record cryptographic hashes for every permitted distribution and install with hash enforcement, such as
pip install --require-hashes -r requirements.txt. - Update
SKILL.mdso its installation command uses the locked dependency file instead of unconstrained package names. - Remove
requestsandmatplotlibif dependency analysis confirms that the Skill does not require them. - Perform dependency updates through a controlled review process that includes vulnerability scanning, provenance verification, automated tests, and review of material package changes.
- Install dependencies in an isolated virtual environment under a non-privileged account, and restrict runtime filesystem and network permissions to the minimum required for NBA API access and report generation.
- Prefer trusted package indexes and disable unapproved supplemental indexes to reduce dependency-confusion exposure.