T08 · Insecure Dependencies
Warning
- Location
- SKILL.md:27
- Finding
- Unpinned Third-Party Dependencies## Vulnerability Details **File Location**: `SKILL.md`, lines 27–29 **Vulnerability Type**: Supply-chain risk from mutable dependency resolution **Risk Level**: Medium **Complete Code Snippet**: ```bash pip install pdfplumber openpyxl python-docx pytesseract pillow ``` ### Technical Analysis The installation command specifies package names without exact versions or integrity hashes. Consequently, each installation can resolve different package and transitive-dependency versions from the configured package index. This makes the installed code mutable after the Skill has been reviewed and prevents reproducible verification of its dependency set. If an upstream package, maintainer account, release process, package index, or transitive dependency is compromised, malicious code could run during package installation or when `processor.py` imports and uses the affected library. The code also imports `pandas` at `processor.py:80`, but the documented command does not install it, which may prompt users to perform an additional unreviewed installation. This finding identifies dependency-management exposure; the reviewed files contain no evidence that the project itself controls or has compromised any named package. ### Attack Path 1. An attacker compromises a named package, one of its transitive dependencies, its publishing account, or the package source used by the victim. 2. The attacker publishes a malicious release that satisfies the unconstrained dependency request. 3. A user or automated agent follows the instruction in `SKILL.md` and runs the provided `pip install` command. 4. The resolver downloads the current malicious release because no reviewed version or hash is enforced. 5. Malicious code executes during installation or later when the dependency is imported while processing a document. ### Impact Assessment Successful exploitation could execute code with the privileges of the account running `pip` or `processor.p ...[truncated 522 chars]
- Remediation
- ## Remediation Suggestions 1. Create a reviewed dependency manifest that pins every direct dependency to an exact version, including `pandas`, which is imported by `processor.py`. 2. Generate and retain a lock file that fixes transitive dependency versions. 3. Require cryptographic hashes for downloaded distributions, such as through a hash-locked requirements file installed with `pip install --require-hashes`. 4. Download packages only from an explicitly configured, trusted package index or an internally controlled artifact repository. 5. Review and scan dependency updates before modifying the lock file; use automated vulnerability and provenance checks where available. 6. Install dependencies in an isolated virtual environment under a non-privileged account rather than using administrative or system-wide installation. 7. Keep installation documentation synchronized with actual imports so users are not prompted to install missing packages ad hoc.