Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-16 13:08 UTC

tlsfuzzer / python-ecdsa

pure-python ECDSA signature/verification and ECDH key agreement

PythonCustom license★ 973 stars⑂ 343 forkssince Apr 2010View on GitHub ↗

tlsfuzzer/python-ecdsa holds a health index of 77 out of 100, placing it in the Good band. It scores highest on Engineering Quality (82/100) and lowest on AI Readiness (41/100). It was last updated 100 days ago. A single contributor accounts for most of its recent work.

77
overall / 100
Good

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.

77
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 66 is calibrated to 77 on the published index scale (record calibration 2026-08-02).

Ownership

tlsfuzzerOrganization
32 followers4 public repossince Nov 2020

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIecdsa0.19.243,985,92223174 days ago

Metrics by category

Vitality

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

46Weak · 21% of overall
How it's scored
9.9/36Push recency — last push 100 days ago
3.5/36Commit cadence — 5/52 weeks with commits
10.8/18Commit volume — 15 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year15
human_commit_share1
days_since_last_push100
active_weeks_last_year5
How it's scored
27/27Ships releases — 17 releases published
27/36Release recency — latest release 174 days ago
12.6/27Release cadence — a release every ~252.7 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count17
latest_release_tagpython-ecdsa-0.19.2
releases_from_tagsno
days_since_latest_release174
mean_days_between_releases252.7

Community & Adoption

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

72Good · 17% of overall
How it's scored
48.5/60Stars — 973 stars
21.1/25Forks — 343 forks
9.3/15Watchers — 49 watchers
Inputs used
forks343
stars973
watchers49
growth_stateorganic
growth_factor_pct100
How it's scored
22.5/22.5README
16.9/22.5License — license file present, not a recognized license
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges8
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicescoveralls.io, github.com, readthedocs.org, shields.io
has_pull_request_templateno
How it's scored
80/80Monthly downloads — 43,985,922 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesecdsa
dependents—
ecosystemspypi
total_downloads—
monthly_downloads43,985,922
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?

66Good · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
5.7/22.5Commit distribution — top contributor authored 75% of commits
13.5/13.5Contributor breadth — 47 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled47
top_contributor_share0.746
How it's scored
37.9/42Issue resolution — 90% of issues closed
25.6/30PR acceptance — 168/197 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs168
open_issues16
closed_issues147
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.902
closed_unmerged_prs29
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
10.9/25Owner reach — 32 followers of tlsfuzzer
16.7/25Track record — 4 public repos, account ~5 yr old
Inputs used
followers32
owner_typeOrganization
is_verifiedno
owner_logintlsfuzzer
public_repos4
account_age_days2,129

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 174 days ago
20/20Version history — 23 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesecdsa
ecosystemspypi
any_deprecatedno
min_days_since_publish174

Engineering Quality

Are baseline engineering and documentation practices in place?

82Excellent · 19% of overall
How it's scored
24/24CI workflows — 2 workflow(s)
24/24Tests present
16/16Linter config — tox.ini
0/9.6Pre-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_configno

Documentation

85Excellent
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 6 topics
10/10Wiki
Inputs used
topicspython, elliptic-curves, cryptography, digital-signatures, ecdsa, ecdh
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?

74Good · 16% of overall
How it's scored
30/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
20/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestsdocs/requirements.txt, requirements.txt, setup.cfg, setup.py
has_codeql_workflowyes
has_security_policyyes
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. 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_packages1
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:ecdsa@0.19.2 runtime dependency closure — what installing the published package pulls in — 1 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.

41Weak · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
14.4/40Legible commit history — 27 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.27
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config — tox.ini
0/11Static type checking
0/10Reproducible environment
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 — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
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
50.1/55Manageable file sizes — 3/34 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes91,272
source_files_sampled34
oversized_source_files3

Key facts

973GitHub stars
47contributors
15commits, last 12 months
100days since last push
17releases
1bus factor
16open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Star history carried forward from 2026-07-21: GitHub restricted the stargazers API to repository admins, so it can no longer be collected. The repository has 973 stars today.
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Star and fork history 976 ★ / 343 ⇿
976Stars
343Forks
17Releases

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.

Star history is shown as collected on 2026-07-21. GitHub restricted the stargazers API to repository administrators in July 2026, so this series can no longer be extended; the current star total above remains live.

02004006008001,000975335122010-042018-062026-09
Major 0Minor 0Patch 0

Each point covers 15 days.

All dependencies 13

Full resolved dependency set from the GitHub dependency graph: 0 direct and 13 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcffi—indirect
PyPIcoverage—indirect
PyPIcoveralls—indirect
PyPIhypothesis—indirect
PyPIidna—indirect
PyPIinflect—indirect
PyPImock2.0.0indirect
PyPIpyopenssl—indirect
PyPIpytest—indirect
PyPIsix—indirect
PyPIsphinx-rtd-theme—indirect
PyPItox—indirect
PyPIunittest2—indirect
Dependency advisories 0

Installing pypi:ecdsa@0.19.2 pulls in 1 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.