A software application to analyze the effects of temporal and environmental metrics on overall CVSS v2 score
Bibliographic record
Abstract
The Common Vulnerability Scoring System (CVSS) is an emerging standard for scoring the impact of vulnerabilities. The CVSS base score has been widely adopted by the industry as a framework for exchanging general vulnerability information, while CVSS temporal and environmental scores, which estimate the effect of vulnerabilities within specific environments, is yet to become part of routine IT risk assessment methodologies. To mitigate the effects of vulnerabilities in an environment, a large number of combinations of environmental metric group values can be manipulated. Due to the unavailability of an efficient CVSS tool, identification of the optimum combination for reducing the score to an acceptable level is a daunting task. This paper reports on a software application developed to help to mitigate the risks and study the effects of temporal and environmental metrics on the overall CVSS v2 score. The developed software solution will be released under the Creative Commons Attribution 3.0.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".