Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-09 10:19 UTC

Mehrdoost / devsecops-radar

🛡️ Unify Trivy, Semgrep, Poutine & Zizmor scans into one AI-enhanced, offline-ready dashboard. Track CI/CD security trends, get LLM-powered analysis, and enforce policies — the open-source DevSecOps command center.

Python · JavaScript · HTMLCustom license★ 1 star⑂ 0 forkssince May 2026View on GitHub ↗
KindCommand-line toolPluginNetwork serviceLibraryWeb interfacehow this is determined

Mehrdoost/devsecops-radar holds a health index of 56 out of 100, placing it in the Moderate band. It scores highest on Engineering Quality (89/100) and lowest on AI Readiness (34/100). It was last updated 65 days ago. A single contributor accounts for most of its recent work.

56
overall / 100
Moderate

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

56
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 54 is calibrated to 56 on the published index scale (record calibration 2026-08-02).

Ownership

MdmPersonal account
3 followers7 public repossince Aug 2020

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIdevsecops-radar0.5.01022765 days ago

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

61Moderate · 21% of overall
How it's scored
18/36Push recency — last push 65 days ago
1.4/36Commit cadence — 2/52 weeks with commits
9/18Commit volume — 9 commits in the last year
7/10OpenSSF Scorecard: Maintained — 9 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 7
Inputs used
commits_last_year9
human_commit_share—
days_since_last_push65
active_weeks_last_year2

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 11 releases published
36/36Release recency — latest release 65 days ago
27/27Release cadence — a release every ~5.6 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count11
latest_release_tagv1.0.0
releases_from_tagsno
days_since_latest_release65
mean_days_between_releases5.6
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

39Weak · 17% of overall
How it's scored
0/60Stars — 1 stars
0/25Forks — 0 forks
0/15Watchers — 0 watchers
Inputs used
forks0
stars1
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

86Excellent
How it's scored
22.5/22.5README
16.9/22.5License — license file present, not a recognized license
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges9
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicescodecov.io, shields.io
has_pull_request_templateyes
How it's scored
26.8/80Monthly downloads — 102 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesdevsecops-radar
dependents—
ecosystemspypi
total_downloads—
monthly_downloads102
unverified_packages_excluded—
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

34At Risk · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0/22.5Commit distribution — top contributor authored 100% of commits
1.4/13.5Contributor breadth — 1 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1
How it's scored
0/42Issue resolution — no issues or no data
0/30PR acceptance — no decided pull requests or no data
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/9 approved changesets -- score normalized to 0
Inputs used
merged_prs0
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio—
closed_unmerged_prs0
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Issue resolution, PR acceptance, Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
4.3/25Owner reach — 3 followers of Mehrdoost
18.6/25Track record — 7 public repos, account ~6 yr old
Inputs used
followers3
owner_typeUser
is_verified—
owner_loginMehrdoost
public_repos7
account_age_days2,202
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 65 days ago
20/20Version history — 27 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesdevsecops-radar
ecosystemspypi
any_deprecatedno
min_days_since_publish65

Engineering Quality

Are baseline engineering and documentation practices in place?

89Excellent · 19% of overall
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

85Excellent
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 14 topics
10/10Wiki
Inputs used
topicsapplication-security, ci-cd, cybersecurity, cybersecurity-tools, dashboard, devops-tools, devsecops, security-tools, semgrep, trivy, vulnerability-managemen, ai, ai-discovery, ai-tools
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

56Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
0/2.5CI-Tests — no data
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/9 approved changesets -- score normalized to 0
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5License — license file detected
5.2/7.5Maintained — 9 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 7
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — no SAST tool detected
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
6.8/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5.3
Excluded from scoring (no data or not applicable): CI-Tests, Signed-Releases. Remaining weights renormalized.
How it's scored
9.1/35Direct dependencies free of known advisories — 2 affected: chromadb 0.6.3 (high 8.8), flask-cors 4.0.2 (moderate 5.3)
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
35.3/40No advisories left outstanding — 1 advisory-carrying package(s) unaddressed past 90 days; oldest published 537 days ago
Inputs used
sourceosv
advisories9
affected_packages2
assessed_packages100
unassessed_packages0
affected_by_severityhigh 1, moderate 1
direct_affected_packages2
Matched the pypi:devsecops-radar@0.5.0 runtime dependency closure — what installing the published package pulls in — 100 packages. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

34At Risk · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit history — no data
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share—
agent_instruction_files—
agent_instruction_max_bytes—
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — Dockerfile
0/10Demonstrated agent practice — no data
0/8Automated maintenance — no data
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share—
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.
How it's scored
0/45Type-checkable code — Python without a type-check config
49.9/55Manageable file sizes — 7/76 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes1,117,939
source_files_sampled76
oversized_source_files7

Key facts

1GitHub stars
1contributors
9commits, last 12 months
65days since last push
11releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

More detail

OpenSSF Scorecard 5.3 / 10
5.3aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-09-09 10:19 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
n/aCI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/9 approved changesets -- score normalized to 0
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
7Maintained9 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 7
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTno SAST tool detected
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
9Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 17
RegistryPackageVersion constraintManifest
PyPIflask>=3.0,<4.0pyproject.toml
PyPIflask-cors>=4.0,<5.0pyproject.toml
PyPIwaitress>=3.0,<4.0pyproject.toml
PyPIpsutil>=5.9,<6.0pyproject.toml
PyPItenacity>=8.0,<10.0pyproject.toml
PyPIpyyaml>=6.0,<7.0pyproject.toml
PyPIrequests>=2.31,<3.0pyproject.toml
PyPIrich>=13.0,<14.0pyproject.toml
PyPIloguru>=0.7,<1.0pyproject.toml
PyPIreportlab>=4.0,<5.0pyproject.toml
PyPIsqlalchemy>=2.0,<3.0pyproject.toml
PyPIpydantic>=2.0,<3.0pyproject.toml
PyPIpyjwt>=2.8,<3.0pyproject.toml
PyPIhttpx>=0.27,<1.0pyproject.toml
PyPIwerkzeug>=3.0,<4.0pyproject.toml
PyPIpython-dotenv>=1.0,<2.0pyproject.toml
PyPIchromadb>=0.4.0,<1.0pyproject.toml
All dependencies not collected

The resolved dependency set could not be collected for this report: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

Dependency advisories 2

Installing pypi:devsecops-radar@0.5.0 pulls in 100 packages, direct and transitive: 2 carry known advisories, of which 2 are direct dependencies.

PackageVersionRelationSeverityAdvisoriesFixed in
chromadb0.6.3directhigh3—
flask-cors4.0.2directmoderate66.0.0

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.