T08 · Insecure Dependencies
Warning
- Location
- SKILL.md:144
- Finding
- Unpinned Third-Party Python Dependencies## Vulnerability Details **File Location**: `SKILL.md`, lines 144–148 **Vulnerability Type**: Unpinned and integrity-unverified third-party dependencies **Risk Level**: Medium ### Vulnerable Code ```markdown ### Python 核心依赖 ```bash pip install pandas numpy scipy matplotlib seaborn ``` ``` ### Technical Analysis The documented installation command resolves mutable package versions from the Python package index configured in the user's environment. It does not specify reviewed versions, use a lockfile, verify package hashes, or identify a trusted index. Consequently, the installed dependency set is neither reproducible nor integrity-verified. Package installation can also execute package build hooks when source distributions are selected. A compromised package release, malicious package-index configuration, or future unsafe version could therefore introduce attacker-controlled code during installation or subsequent import. There is also a dependency declaration mismatch: the skill metadata declares only `pandas` and `numpy`, while the installation command additionally introduces `scipy`, `matplotlib`, and `seaborn`. This weakens dependency review and inventory controls. ### Attack Path 1. A user follows the installation instructions in `SKILL.md`. 2. `pip` queries the package index configured in the user's environment and resolves unspecified package versions. 3. An attacker compromises an upstream release or influences the configured index or mirror. 4. `pip` downloads the attacker-controlled distribution without hash verification. 5. Malicious code executes through package build hooks during installation or when the package is later imported. 6. The payload runs with the privileges of the user or service account performing the installation or analysis. ### Impact Assessment Successful exploitation could execute arbitrary code with the privileges of the installing user. Depending on that account's access, the attacker could read or modify local files, ...[truncated 402 chars]
- Remediation
- ## Remediation Suggestions 1. Replace the direct installation command with a reviewed, version-pinned dependency file. 2. Generate and retain hashes for every direct and transitive dependency, then install with `pip install --require-hashes -r requirements.txt`. 3. Use a lockfile or constraints file to make dependency resolution reproducible. 4. Explicitly configure and document the trusted package index; avoid untrusted extra indexes and mirrors. 5. Prefer reviewed binary wheels and restrict source builds where operationally practical. 6. Scan dependencies for known vulnerabilities and automate controlled update review. 7. Synchronize `SKILL.md`, package metadata, and any dependency manifest so all direct dependencies—including `scipy`, `matplotlib`, and `seaborn`—are declared consistently. 8. Perform installation in an isolated virtual environment or container under a least-privileged account.