T08 · Insecure Dependencies
Warning
- Location
requirements.txt:1- Finding
Unpinned Third-Party Dependency Permits Unreviewed Future Releases
- Content
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=0.7.0 ``` Related installation instructions in `SKILL.md:23-28`: ```bash pip install -r requirements.txt ``` ```bash pip install google-genai ``` ### Technical Analysis The dependency specification accepts any `google-genai` release at or above version `0.7.0`. The documented manual installation command is even less restrictive. Consequently, installation is not reproducible and may retrieve a future package version that was never reviewed with this Skill. Python packages can execute code during installation or when imported. The script imports this dependency and provides it with access to the Gemini API key: ```python from google import genai from google.genai import types client = genai.Client(api_key=api_key) ``` There is no evidence that the currently published dependency is malicious. The vulnerability is the absence of an exact reviewed version and integrity hashes, which increases exposure to compromised future releases, account compromise at the package publisher, or an incompatible release. ### Attack Path 1. An attacker compromises the upstream package publisher, distribution account, or a future permitted release. 2. The attacker publishes a malicious `google-genai` version satisfying `>=0.7.0`. 3. A user follows the documented `pip install` command. 4. Package-controlled code executes during installation or when `gemini_cite.py` imports the dependency. 5. The malicious code inherits the invoking user’s local permissions and can access process data, including `GEMINI_API_KEY`, research queries, and available network connectivity. This path depends on an upstream supply-chain compromise; no direct compromise is present in the audited repository. ### Impact Assessment A compromised dependency could execute with the privileges of the user running ...[truncated 707 chars]- Remediation
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``` 2. Generate and verify cryptographic hashes for the package and all transitive dependencies, then install with: ```bash pip install --require-hashes -r requirements.txt ``` 3. Use a dependency lock file generated from a trusted package index to make installations reproducible. 4. Update `SKILL.md` so the manual installation example also specifies the exact reviewed version rather than installing the latest available release. 5. Establish a controlled dependency-update process that includes changelog review, vulnerability scanning, package-origin verification, and regression testing before changing the pinned version. 6. Run the Skill under a minimally privileged account or isolated environment, and expose only the environment variables and files required for operation. ]]>