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Software-GesundheitsberichtSchema 0.11.0 · Metriken 1.13.0 · 2026-07-17 15:22 UTC

greenbone / ospd-openvas

ospd-openvas is an OSP server implementation to allow GVM to remotely control an OpenVAS Scanner

PythonAGPL-3.0★ 80 Sterne⑂ 63 Forksseit Juni 2018Auf GitHub ansehen ↗

greenbone/ospd-openvas erreicht einen Gesundheitsindex von 72 von 100 und liegt damit im Bereich Gut. Am stärksten schneidet es bei Engineering Quality (80/100) ab, am schwächsten bei AI Readiness (44/100). Zuletzt vor 3 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.

72
gesamt / 100
Gut

Software-Gesundheitsindex

Metriken werden auf einer Skala von 1–100 in gewichtete Kategorien gruppiert. Der Gesamtwert beginnt als ihr Mittel; sobald öffentliche Evidenz die Richtlinie für Hochrisikojurisdiktionen auslöst, wird die Bewertung angepasst und erhält die Obergrenze 49 (Gefährdet). AI Readiness liegt außerhalb.

72
Exzellent85-100Vorbildlich; erfüllt im Wesentlichen alle geprüften Kriterien
Gut70-84Gesund; geringfügige Lücken
Mittel50-69Akzeptabel mit deutlichen Lücken; Überprüfung empfohlen
Gefährdet30-49Erhebliche Schwächen; eine Übernahme erfordert Vorsicht
Kritisch1-29Schwerwiegende Probleme (aufgegeben, nur ein Maintainer, keine Hygiene)
VitalitätCommunity &VerbreitungNachhaltigkeit &GovernanceEngineering-QualitätSicherheitAI Readiness

Bewertungsprofil

Jede Achse ist eine Kategorie. Die Form zählt mehr als der Durchschnitt — ein gesundes Projekt füllt die gesamte Fläche, während ein Profil aus Spitzen und Kratern bedeutet, dass Stärke in einer Dimension Risiken in einer anderen verdeckt.

Eigentümerschaft

GreenboneOrganisation
1.310 Follower68 öffentliche Reposseit Sept. 2017

Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlichtTags
PyPIospd-openvas22.10.3-36vor 3 Tagenopenvasgreenbone-vulnerability-managementvulnerability-scanningospopen-scanner-protocol
Gogithub.com/greenbone/ospd-openvasv22.10.3+incompatible-38vor 3 Tagen

Metriken nach Kategorie

Vitalität

Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?

77Gut · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 3 Tagen
9.7/36Commit-Rhythmus — 14/52 Wochen mit Commits
14/18Commit-Volumen — 35 Commits im letzten Jahr
8/10OpenSSF Scorecard: Maintained — 8 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 8
Verwendete Eingangsdaten
commits_last_year35
human_commit_share
days_since_last_push3
active_weeks_last_year14
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 38 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 3 Tagen
19.8/27Release-Rhythmus — ein Release etwa alle 90,3 Tage
8/10OpenSSF Scorecard: Signed-Releases — 5 out of the last 5 releases have a total of 5 signed artifacts.
Verwendete Eingangsdaten
releases_count38
latest_release_tagv22.10.3
releases_from_tagsnein
days_since_latest_release3
mean_days_between_releases90,3

Community & Verbreitung

Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?

54Mittel · 18 % des Gesamtindex
Wie die Bewertung erfolgt
30.8/60Stars — 80 Stars
14.9/25Forks — 63 Forks
6.4/15Watcher — 15 Watcher
Verwendete Eingangsdaten
forks63
stars80
watchers15
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Wie die Bewertung erfolgt
22.5/22.5README
22.5/22.5Lizenz — anerkannte Lizenz (AGPL-3.0)
0/18CONTRIBUTING-Leitfaden
0/13.5Verhaltenskodex
0/7.2Issue-Vorlage
6.3/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingnein
has_issue_templatenein
has_code_of_conductnein
has_pull_request_templateja

Nachhaltigkeit & Governance

Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?

74Gut · 24 % des Gesamtindex
Wie die Bewertung erfolgt
9/54Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab
11.1/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 50 % der Commits
13.5/13.5Breite der Beitragenden — 31 Beitragende
10/10OpenSSF Scorecard: Contributors — project has 6 contributing companies or organizations
Verwendete Eingangsdaten
bus_factor1
contributors_sampled31
top_contributor_share0,505
Wie die Bewertung erfolgt
44.2/46.8Issue-Lösungsquote — 94 % der Issues geschlossen
33.6/38.3PR-Annahme — 915/1.042 entschiedene PRs gemergt
10.5/15OpenSSF Scorecard: Code-Review — Found 12/17 approved changesets -- score normalized to 7
Verwendete Eingangsdaten
merged_prs915
open_issues3
closed_issues52
issue_closed_ratio0,945
closed_unmerged_prs127
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
22.4/25Reichweite des Inhabers — 1.310 Follower von greenbone
25/25Kontohistorie — 68 öffentliche Repos, Kontoalter ca. 8 Jahre
Verwendete Eingangsdaten
followers1.310
owner_typeOrganization
is_verified
owner_logingreenbone
public_repos68
account_age_days3.227

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 2 Paket(e) auf go, pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 3 Tagen
20/20Versionshistorie — 38 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packagesospd-openvas, github.com/greenbone/ospd-openvas
ecosystemsgo, pypi
any_deprecatednein
min_days_since_publish3

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

80Gut · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 13 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration — .pylintrc
0/9.6Pre-Commit-Hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 24 out of 24 merged PRs checked by a CI test -- score normalized to 10
Verwendete Eingangsdaten
has_cija
has_testsja
has_editorconfignein
has_linter_configja
has_precommit_confignein
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
0/15Dokumentations-/Homepage-Site
10/10Repository-Beschreibung
10/10Topics — 5 Topics
0/10Wiki
Verwendete Eingangsdaten
topicspython, base, openvas, techops, tooling
has_wikinein
homepage
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?

72Gut · 16 % des Gesamtindex
Wie die Bewertung erfolgt
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — keine Daten
2.5/2.5CI-Tests — 24 out of 24 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
5.2/7.5Code-Review — Found 12/17 approved changesets -- score normalized to 7
2.5/2.5Contributors — project has 6 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5Lizenz — license file detected
6/7.5Maintained — 8 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 8
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
5/5SAST — SAST tool is run on all commits
5/5Security-Policy — security policy file detected
6/7.5Signed-Releases — 5 out of the last 5 releases have a total of 5 signed artifacts.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
5.2/7.5Vulnerabilities — 3 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate7,2
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): branch_protection. Die verbleibenden Gewichte wurden renormalisiert.

AI Readiness

Wie gut ist das Repository dafür ausgestattet, mit KI-Coding-Agenten entwickelt und gepflegt zu werden? Ein unabhängiges, experimentelles Badge — Gewicht 0,0, es wird eigenständig ausgewiesen und verändert den Gesamt-Gesundheitswert nicht.

44Gefährdet · 0 % des Gesamtindex
Wie die Bewertung erfolgt
0/45Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln
0/15Maschinenlesbare Doku (llms.txt)
0/40Lesbare Commit-Historie — keine Daten
Verwendete Eingangsdaten
has_llms_txtnein
legible_history_share
agent_instruction_files
agent_instruction_max_bytes
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lesbare Commit-Historie. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
18/18Bootstrap mit einem Befehl — smoketest/Makefile
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration — .pylintrc
0/11Statische Typprüfung
10/10Reproduzierbare Umgebung — Dockerfile, lockfile
0/10Belegte Agentenpraxis — keine Daten
5/8Automatisierte Wartung — Abhängigkeits-Automatisierung konfiguriert, in den erfassten Commits nicht beobachtet
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfilesgo.sum, poetry.lock
has_dockerfileja
typed_languagenein
bootstrap_filessmoketest/Makefile
has_devcontainernein
has_linter_configja
typecheck_configs
agent_commit_share
toolchain_manifests
dependency_bot_commit_share0
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Belegte Agentenpraxis. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
0/45Typprüfbarer Code — Python ohne Typprüfungs-Konfiguration
55/55Handhabbare Dateigrößen — 0/95 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes56.303
source_files_sampled95
oversized_source_files0

Eckdaten

80GitHub-Sterne
31Mitwirkende
35Commits, letzte 12 Monate
3Tage seit letztem Push
38Releases
1Bus-Faktor
3offene Issues
Go, PyPIPaket-Ökosysteme

Weitere Details

OpenSSF Scorecard 7.2 / 10
7.2Gesamtwert

Unabhängige, werkzeugneutrale Sicherheitsbewertung durch das quelloffene OpenSSF Scorecard. Jede Prüfung honoriert eine Sicherheits-Praxis, nicht das Werkzeug eines bestimmten Anbieters. Prüfungen, die Scorecard nicht ermitteln konnte, sind mit k. A. markiert und vom Sicherheitswert ausgeschlossen (nie als null gezählt).Scorecard v5.5.0 · 2026-07-17 15:21 UTC

10Binary-Artifactsno binaries found in the repo
k. A.Branch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
10CI-Tests24 out of 24 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
7Code-ReviewFound 12/17 approved changesets -- score normalized to 7
10Contributorsproject has 6 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
8Maintained8 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 8
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
8Signed-Releases5 out of the last 5 releases have a total of 5 signed artifacts.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7Vulnerabilities3 existing vulnerabilities detected
Direkte Abhängigkeiten 10
RegistryPaketVersionsvorgabeManifest
PyPIredis>=4.5.0,<7.2.0pyproject.toml
PyPIpsutil>=5.5.1,<8.0.0pyproject.toml
PyPIpackaging>=20.4,<27.0pyproject.toml
PyPIlxml>=4.5.2,<7.0.0pyproject.toml
PyPIdefusedxml>=0.6,<0.8pyproject.toml
PyPIdeprecated^1.2.10pyproject.toml
PyPIpaho-mqtt>=1.6,<3pyproject.toml
PyPIpython-gnupg>=0.4.8,<0.6.0pyproject.toml
Gogithub.com/eclipse/paho.golangv0.10.0smoketest/go.mod
Gogithub.com/google/uuidv1.3.0smoketest/go.mod
Alle Abhängigkeiten 70

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 12 direkte und 58 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
Gogithub.com/eclipse/paho.golang0.10.0direkt
Gogithub.com/eclipse/paho.golangv0.10.0direkt
Gogithub.com/google/uuid1.3.0direkt
Gogithub.com/google/uuidv1.3.0direkt
PyPIdefusedxml0.7.1direkt
PyPIdeprecated1.3.1direkt
PyPIlxml6.1.1direkt
PyPIpackaging26.2direkt
PyPIpaho-mqtt2.1.0direkt
PyPIpsutil7.2.2direkt
PyPIpython-gnupg0.5.6direkt
PyPIredis7.0.1direkt
Gogithub.com/davecgh/go-spew1.1.1indirekt
Gogithub.com/davecgh/go-spewv1.1.1indirekt
Gogithub.com/google/go-cmp0.5.6indirekt
Gogithub.com/google/go-cmpv0.5.6indirekt
Gogithub.com/gorilla/websocketv1.4.2indirekt
Gogithub.com/pmezard/go-difflibv1.0.0indirekt
Gogithub.com/stretchr/objxv0.1.0indirekt
Gogithub.com/stretchr/testifyv1.7.0indirekt
Gogolang.org/x/sync0.0.0-20210220032951-036812b2e83cindirekt
Gogolang.org/x/syncv0.0.0-20210220032951-036812b2e83cindirekt
Gogolang.org/x/xerrorsv0.0.0-20191204190536-9bdfabe68543indirekt
Gogopkg.in/check.v1v0.0.0-20161208181325-20d25e280405indirekt
Gogopkg.in/yaml.v33.0.1indirekt
Gogopkg.in/yaml.v3v3.0.1indirekt
PyPIanyio4.12.1indirekt
PyPIastroid3.3.11indirekt
PyPIasync-timeout5.0.1indirekt
PyPIautohooks25.11.0indirekt
PyPIautohooks-plugin-black23.10.0indirekt
PyPIautohooks-plugin-pylint23.10.0indirekt
PyPIblack25.11.0indirekt
PyPIcertifi2026.1.4indirekt
PyPIclick8.1.8indirekt
PyPIcolorama0.4.6indirekt
PyPIcolorful0.5.8indirekt
PyPIdill0.4.1indirekt
PyPIexceptiongroup1.3.1indirekt
PyPIh110.16.0indirekt
PyPIh24.3.0indirekt
PyPIhpack4.1.0indirekt
PyPIhttpcore1.0.9indirekt
PyPIhttpx0.28.1indirekt
PyPIhyperframe6.1.0indirekt
PyPIidna3.15indirekt
PyPIimportlib-metadata8.7.1indirekt
PyPIisort6.1.0indirekt
PyPImarkdown-it-py3.0.0indirekt
PyPImccabe0.7.0indirekt
PyPImdurl0.1.2indirekt
PyPImypy-extensions1.1.0indirekt
PyPIpathspec1.0.4indirekt
PyPIplatformdirs4.4.0indirekt
PyPIpontos26.2.0indirekt
PyPIpygments2.20.0indirekt
PyPIpylint3.3.9indirekt
PyPIpython-dateutil2.9.0.post0indirekt
PyPIpytokens0.4.1indirekt
PyPIpytoolconfig1.3.1indirekt
PyPIrich14.3.3indirekt
PyPIrope1.14.0indirekt
PyPIsemver3.0.4indirekt
PyPIshtab1.8.0indirekt
PyPIsix1.17.0indirekt
PyPItomli2.4.0indirekt
PyPItomlkit0.14.0indirekt
PyPItyping-extensions4.15.0indirekt
PyPIwrapt2.1.1indirekt
PyPIzipp3.23.0indirekt
JSON-Rohbericht maschinenlesbar
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                "key": "fuzzing",
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                "name": "Signed-Releases",
                "detail": "5 out of the last 5 releases have a total of 5 signed artifacts.",
                "points": 6,
                "status": "partial",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "3 existing vulnerabilities detected",
                "points": 5.2,
                "status": "partial",
                "details": [],
                "max_points": 7.5
              }
            ]
          },
          {
            "key": "high_risk_jurisdiction_exposure",
            "band": "excellent",
            "name": "High-Risk Jurisdiction Exposure",
            "note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
            "notes": [
              {
                "code": "jurisdiction_evidence_limits",
                "params": {}
              }
            ],
            "value": 100,
            "inputs": {
              "meaning": "self-published location evidence; not nationality or citizenship",
              "red_flag": false,
              "exposures": [],
              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
              ],
              "review_only_matches": 0,
              "assessed_self_published_locations": 6
            },
            "components": [
              {
                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
                "detail": "no confirmed policy-scope location match",
                "points": 100,
                "status": "met",
                "details": [
                  {
                    "code": "jurisdiction_no_match",
                    "params": {}
                  }
                ],
                "max_points": 100
              }
            ]
          }
        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
        "band": "at_risk",
        "name": "AI Readiness",
        "value": 44,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "critical",
            "name": "Agent context & guidance",
            "note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "legible_commit_history"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 1,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": null,
              "agent_instruction_files": [],
              "agent_instruction_max_bytes": null
            },
            "components": [
              {
                "key": "agent_instructions",
                "name": "Agent instructions",
                "detail": "no CLAUDE.md / AGENTS.md / editor rules",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_agent_instructions",
                    "params": {}
                  }
                ],
                "max_points": 45
              },
              {
                "key": "machine_readable_docs_llms_txt",
                "name": "Machine-readable docs (llms.txt)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 15
              },
              {
                "key": "legible_commit_history",
                "name": "Legible commit history",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "good",
            "name": "Verify loop (build / test / typecheck)",
            "note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "demonstrated_agent_practice"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 73,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [
                "go.sum",
                "poetry.lock"
              ],
              "has_dockerfile": true,
              "typed_language": false,
              "bootstrap_files": [
                "smoketest/Makefile"
              ],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [],
              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": "smoketest/Makefile",
                "points": 18,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "smoketest/Makefile"
                    }
                  }
                ],
                "max_points": 18
              },
              {
                "key": "automated_tests",
                "name": "Automated tests",
                "detail": null,
                "points": 22,
                "status": "met",
                "details": [],
                "max_points": 22
              },
              {
                "key": "lint_format_config",
                "name": "Lint / format config",
                "detail": ".pylintrc",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": ".pylintrc"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 11
              },
              {
                "key": "reproducible_environment",
                "name": "Reproducible environment",
                "detail": "Dockerfile, lockfile",
                "points": 10,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "Dockerfile, lockfile"
                    }
                  }
                ],
                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
                "name": "Demonstrated agent practice",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 10
              },
              {
                "key": "automated_maintenance",
                "name": "Automated maintenance",
                "detail": "dependency automation configured, none observed in the sampled commits",
                "points": 5,
                "status": "partial",
                "details": [
                  {
                    "code": "dependency_bot_config_only",
                    "params": {}
                  }
                ],
                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "moderate",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 55,
            "inputs": {
              "primary_language": "Python",
              "largest_source_bytes": 56303,
              "source_files_sampled": 95,
              "oversized_source_files": 0
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python without a type-check config",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_typecheck_config_language",
                    "params": {
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "0/95 source files over 60KB",
                "points": 55,
                "status": "met",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 95,
                      "oversized": 0
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          }
        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
      }
    ],
    "metrics_version": "1.13.0"
  },
  "warnings": [],
  "report_type": "repository",
  "generated_at": "2026-07-17T15:22:23.683801Z",
  "schema_version": "0.11.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/g/greenbone/ospd-openvas.svg",
  "full_name": "greenbone/ospd-openvas",
  "license_state": "standard",
  "license_spdx": "AGPL-3.0"
}

Bewertungen sind Signale, keine Garantien. Sie spiegeln öffentlich sichtbare Praxis auf GitHub wider — kein Code-Audit und keine Sicherheitsgarantie.

Fehlende Daten werden ausgeschlossen und die Gewichte neu normiert, nie als null bewertet. Die Methodik ist versioniert und offen: Metriken v1.13.0, Schema v0.11.0 — vollständige Methodik · Metriken-Wiki.

Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte StatistikenPyPI, Go.