On the Discoverability of npm Vulnerabilities in Node.js Projects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The reliance on vulnerable dependencies is a major threat to software systems. Dependency vulnerabilities are common and remain undisclosed for years. However, once the vulnerability is discovered and publicly known to the community, the risk of exploitation reaches its peak, and developers have to work fast to remediate the problem. While there has been a lot of research to characterize vulnerabilities in software ecosystems, none have explored the problem taking the discoverability into account. Therefore, we perform a large-scale empirical study examining 6,546 Node.js applications. We define three discoverability levels based on vulnerabilities lifecycle (undisclosed, reported, and public). We find that although the majority of the affected applications (99.42%) depend on undisclosed vulnerable packages, 206 (4.63%) applications were exposed to dependencies with public vulnerabilities. The major culprit for the applications being affected by public vulnerabilities is the lack of dependency updates; in 90.8% of the cases, a fix is available but not patched by application maintainers. Moreover, we find that applications remain affected by public vulnerabilities for a long time (103 days). Finally, we devise DepReveal, a tool that supports our discoverability analysis approach, to help developers better understand vulnerabilities in their application dependencies and plan their project maintenance.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it