Open-Source Code Quality, Security and Technical Debt Review
This report summarizes scanner evidence for
DiningFactory/panda-vpn-pro with 17,203 GitHub stars.
SynthScan examined 244 lines of code across
1 source files, recording
0 pattern matches
distributed across 0 syntactic categories.
The legacy adjusted pattern signal is 0.0
(Low pattern signal); it is not an authorship estimate.
Use the findings to ask whether maintainers can explain intent, verify dependencies, simplify
unnecessary scaffolding, and focus review effort. Risk Payload v1 adds ownership, supply-chain,
over-engineering, and review-effort vectors when available. These are prompts for
human verification, not probabilities, security findings, or measured maintenance costs.
0.0
Adjusted Signal
0.0
Raw Pattern Score
100%
Time Factor
2026-10-31
Last Push
17.2K
Stars
—
Language
244
Lines of Code
1
Files
0
Pattern Hits
2026-10-31
Scan Date
0.00
HC Hit Rate
Risk Review · Payload v1
Use each vector to guide manual verification of the underlying findings.
Are imports declared and package/API names verified? 0 finding(s).
Agent Over-Engineering Ratio0.0/100 · LOW
Are wrappers, guards, and repeated structures necessary? 0 finding(s).
PR Review Velocity Impact0.0/100 · LOW
Which changes need focused human review? 0 finding(s).
What These Metrics Mean
Adjusted Signal
Legacy pattern score normalized per 1,000 scanned lines and multiplied by the repository-level time factor. It is not an estimate of AI authorship.
Raw Pattern Score
Sum of severity- and context-weighted pattern findings before applying the time factor.
Time Factor
A coarse multiplier based on repository last-push metadata. It does not identify when individual code was written.
Pattern Hits
Count of configured pattern findings. Review each location and surrounding code before acting.
HC Hit Rate
High- and critical-severity findings per scanned file. Severity is a configured detector weight, not proof of a vulnerability or authorship.
Lines / Files
Scan coverage denominators used by the legacy normalized score.
Pattern-Signal History
This chart tracks the legacy adjusted pattern score across scan runs. Changes can reflect source changes, scan coverage, or detector/scoring versions; they do not measure AI adoption or prove that a team refactored code. Compare runs only when their scoring versions are compatible. The dashed line tracks the raw pattern-hit count.
Severity Breakdown
Groups findings by configured severity weight. Severity is not a confidence estimate,
security rating, or proof that a package is missing. Verify imports against the project's
manifests and inspect each finding in its local design context.
CRITICAL 0HIGH 0MEDIUM 0LOW 0
Directory Score Breakdown
This horizontal bar chart shows where configured pattern scores accumulate across directories.
Treat the bars as locations to inspect, not as evidence of authorship or code quality. Use the
file-level findings to decide whether a directory needs a focused ownership, dependency,
complexity, or review check.
Pattern Findings
The scanner identified 0 distinct pattern matches
across 0 syntactic categories.
Each entry below represents a discrete location in the source code where the engine recorded
a detector match to inspect in context.
Expand any category row to inspect the individual file paths, line numbers, code snippets,
and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table:
The Severity column indicates the configured finding weight (CRITICAL / HIGH / MEDIUM / LOW).
The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal —
legacy comment-context matches receive a ×1.5 score weight.
The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window,
each receiving an additional ×1.5 density multiplier under the legacy scoring model.
Adjusted legacy signal; badge bands: 25 / 50 / 75 (different from dashboard bands).