Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-09 01:38 UTC

kaifcodec / user-scanner

🕵️‍♂️ (2-in-1) Email & Username OSINT suite featuring native MCP support for deep data extraction just from a single Email/Username. Analyzes 550+ actively maintained scan vectors (175+ email / 375+ username) for security research, investigations, and digital footprinting.

PythonMIT★ 4,727 stars⑂ 474 forkssince Oct 2025View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

kaifcodec/user-scanner holds a health index of 92 out of 100, placing it in the Excellent band. It scores highest on Vitality (98/100) and lowest on AI Readiness (60/100). It was last updated 1 day ago. A single contributor accounts for most of its recent work.

92
overall / 100
Excellent

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.

92
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 78 is calibrated to 92 on the published index scale (record calibration 2026-08-02).

Ownership

KaifPersonal account
445 followers30 public repossince Jan 2022

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 publishTags
PyPIuser-scanner1.5.1.219,1921181 day agoosintemail-osintusername-osintpythoncli-toolcybersecuritythreat-intelligencesecurity

Metrics by category

Vitality

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

98Exceptional · 21% of overall
How it's scored
36/36Push recency — last push 1 days ago
31.8/36Commit cadence — 46/52 weeks with commits
18/18Commit volume — 1,377 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 20 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year1,377
human_commit_share1
days_since_last_push1
active_weeks_last_year46

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 37 releases published
36/36Release recency — latest release 11 days ago
27/27Release cadence — a release every ~19.5 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count37
latest_release_tagv1.5.1
releases_from_tagsno
days_since_latest_release11
mean_days_between_releases19.5
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?

78Good · 17% of overall
How it's scored
59.6/60Stars — 4,727 stars
22.3/25Forks — 474 forks
8.6/15Watchers — 36 watchers
Inputs used
forks474
stars4,727
watchers36
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges7
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno
How it's scored
57.1/80Monthly downloads — 19,192 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesuser-scanner
dependents—
ecosystemspypi
total_downloads—
monthly_downloads19,192
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?

68Good · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
6/22.5Commit distribution — top contributor authored 73% of commits
13.5/13.5Contributor breadth — 48 contributors
10/10OpenSSF Scorecard: Contributors — project has 4 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled48
top_contributor_share0.733
How it's scored
41.3/42Issue resolution — 98% of issues closed
26.3/30PR acceptance — 425/485 decided PRs merged
10.8/13Newcomer PR acceptance — 5/6 first-time contributors' PRs merged in 30d
9/15OpenSSF Scorecard: Code-Review — Found 19/28 approved changesets -- score normalized to 6
Inputs used
merged_prs425
open_issues2
closed_issues113
prs_merged_7d11
prs_decided_7d12
prs_merged_30d52
prs_decided_30d55
issue_closed_ratio0.983
closed_unmerged_prs60
first_time_authors_30d4
first_time_prs_merged_30d5
first_time_prs_decided_30d6
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
19/25Owner reach — 445 followers of kaifcodec
20.1/25Track record — 30 public repos, account ~4 yr old
Inputs used
followers445
owner_typeUser
is_verified—
owner_loginkaifcodec
public_repos30
account_age_days1,685
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 1 days ago
20/20Version history — 118 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesuser-scanner
ecosystemspypi
any_deprecatedno
min_days_since_publish1

Engineering Quality

Are baseline engineering and documentation practices in place?

80Excellent · 19% of overall
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 23 out of 23 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 17 topics
0/10Wiki
Inputs used
topicsosint, osint-tool, python, osint-tools, email-osint, osint-email, cybersecurity, cybersecurity-tools, threat-intelligence, ethical-hacking, ethical-hacking-tools, redteam-tools, redteaming, identification, pentesting, infosec, osint-username
has_wikino
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?

70Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
4.5/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 23 out of 23 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
4.5/7.5Code-Review — Found 19/28 approved changesets -- score normalized to 6
2.5/2.5Contributors — project has 4 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 20 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
1.5/5SAST — SAST tool is not run on all commits -- score normalized to 3
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
7.5/7.5Token-Permissions — GitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6.3
Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages19
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:user-scanner@1.5.1.2 runtime dependency closure — what installing the published package pulls in — 19 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.

60Moderate · 4% of overall
How it's scored
45/45Agent instructions — AGENTS.md, CLAUDE.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 100 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share1
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes5,203
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 — Nix
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixyes
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/651 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes26,568
source_files_sampled651
oversized_source_files0

Key facts

4,727GitHub stars
48contributors
1,377commits, last 12 months
1days since last push
37releases
1bus factor
2open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi download statistics for 'user-scanner' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced
  • pypi download figures for user-scanner carried forward from the previous scan (stats endpoint unavailable this scan)

More detail

Star and fork history 0 ★ / 474 ⇿
0Stars
474Forks
37Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

0100200300400500474262025-102026-042026-09
Major 0Minor 5Patch 11
OpenSSF Scorecard 6.3 / 10
6.3aggregate

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 01:38 UTC

10Binary-Artifactsno binaries found in the repo
6Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests23 out of 23 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
6Code-ReviewFound 19/28 approved changesets -- score normalized to 6
10Contributorsproject has 4 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 20 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
3SASTSAST tool is not run on all commits -- score normalized to 3
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 5
RegistryPackageVersion constraintManifest
PyPIhttpx>=0.27,<0.29pyproject.toml
PyPIsocksio>=1.0,<2pyproject.toml
PyPIcolorama>=0.4,<1pyproject.toml
PyPIcurl_cffi>=0.7,<1pyproject.toml
PyPIrich>=13.0.0pyproject.toml
All dependencies 10

Full resolved dependency set from the GitHub dependency graph: 5 direct and 5 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcolorama—direct
PyPIcurl-cffi—direct
PyPIhttpx—direct
PyPIrich—direct
PyPIsocksio—direct
PyPIflit-core—indirect
PyPImcp—indirect
PyPIpillow—indirect
PyPIreportlab—indirect
PyPIsvglib—indirect
Dependency advisories 0

Installing pypi:user-scanner@1.5.1.2 pulls in 19 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

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.