Repository Analysis

chaitin/SafeLine

SafeLine is a self-hosted WAF(Web Application Firewall) / reverse proxy to protect your web apps from attacks and exploits.

3.1 Likely human-written View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of chaitin/SafeLine, a Go project with 21,699 GitHub stars. SynthScan v2.0 examined 12,817 lines of code across 147 source files, recording 42 pattern matches distributed across 7 syntactic categories. The overall adjusted score of 3.1 places this repository in the Likely human-written band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

3.1
Adjusted Score
3.1
Raw Score
100%
Time Factor
2026-07-10
Last Push
21.7K
Stars
Go
Language
12.8K
Lines of Code
147
Files
42
Pattern Hits
2026-07-14
Scan Date
0.01
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 1MEDIUM 4LOW 37

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 42 distinct pattern matches across 7 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. 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 diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Excessive Try-Catch Wrapping24 hits · 15 pts
SeverityFileLineSnippetContext
MEDIUMscripts/manage.py586def get_url(url):CODE
MEDIUMscripts/manage.py675def exec_command(*args,shell=False):CODE
MEDIUMscripts/manage.py683def exec_command_with_loading(*args, cwd=None, env=None):CODE
LOWscripts/manage.py490 except Exception as e:CODE
LOWscripts/manage.py703 except Exception as e:STRING
LOWscripts/manage.py723 except Exception as e:STRING
LOWscripts/manage.py883 except Exception as e:STRING
LOWscripts/manage.py892 except Exception as e:STRING
LOWscripts/manage.py901 except Exception as e:STRING
LOWscripts/manage.py591 except Exception as e:STRING
LOWscripts/manage.py647 except Exception as e:STRING
LOWscripts/manage.py667 except Exception as e:STRING
LOWscripts/manage.py680 except Exception as e:STRING
LOWscripts/manage.py938 except Exception:STRING
LOWscripts/manage.py949 except Exception as e:STRING
LOWscripts/manage.py1153 except Exception as e:STRING
LOWscripts/manage.py1160 except Exception as e:STRING
LOWscripts/manage.py1235 except Exception as e:STRING
LOWscripts/manage.py1281 except Exception as e:STRING
LOWscripts/manage.py1291 except Exception as e:STRING
LOWscripts/manage.py1389 except Exception as e:STRING
LOWscripts/manage.py1429 except Exception as e:STRING
LOWscripts/manage.py1496 except Exception as e:STRING
LOWscripts/manage.py1563 except Exception as e:STRING
Structural Annotation Overuse6 hits · 9 pts
SeverityFileLineSnippetContext
LOWsdk/ingress-nginx/README.md42### Step 1: Install the pluginCOMMENT
LOWsdk/ingress-nginx/README.md73### Step 2: Configure the pluginCOMMENT
LOWsdk/ingress-nginx/README.md88### Step 3: Configure the ingress-controllerCOMMENT
LOWsdk/ingress-nginx/README.md109### Step 3: Enable the pluginCOMMENT
LOWsdk/ingress-nginx/README.md124### Step 4: Set externalTrafficPolicy to LocalCOMMENT
LOWsdk/ingress-nginx/README.md127### Step 5: Test the pluginCOMMENT
Deep Nesting8 hits · 8 pts
SeverityFileLineSnippetContext
LOWscripts/manage.py621CODE
LOWscripts/manage.py633CODE
LOWscripts/manage.py683CODE
LOWscripts/manage.py757CODE
LOWscripts/manage.py836CODE
LOWscripts/manage.py911CODE
LOWscripts/manage.py1002CODE
LOWscripts/manage.py1501CODE
Cross-Language Confusion1 hit · 4 pts
SeverityFileLineSnippetContext
HIGHscripts/manage.py713 return exec_command('systemctl enable docker && systemctl daemon-reload && systemctl restart docker',shell=True)STRING
Self-Referential Comments1 hit · 3 pts
SeverityFileLineSnippetContext
MEDIUM.github/ISSUE_TEMPLATE/bug-report.yaml3# Create a report to help us improveCOMMENT
Over-Commented Block1 hit · 1 pts
SeverityFileLineSnippetContext
LOWmcp_server/README.md61# 2. Edit docker-compose.yml to configure environment variablesCOMMENT
Hyper-Verbose Identifiers1 hit · 0 pts
SeverityFileLineSnippetContext
LOWscripts/manage.py683def exec_command_with_loading(*args, cwd=None, env=None):STRING