Public record
Software health reportschema 0.26.0 · metrics 2.10.0 · 2026-07-22 01:37 UTC

pallets / markupsafe

Safely add untrusted strings to HTML/XML markup.

Python · CBSD-3-Clause★ 693 stars⑂ 187 forkssince Jun 2010View on GitHub ↗

pallets/markupsafe holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Engineering Quality (91/100) and lowest on Vitality (35/100). It was last updated 297 days ago. A single contributor accounts for most of its recent work.

78
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.

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

Ownership

PalletsOrganization
2,372 followers17 public repossince Jan 2016

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIMarkupSafe3.0.3-35297 days ago

Metrics by category

Vitality

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

35Weak · 21% of overall
How it's scored
3.6/36Push recencylast push 297 days ago
1.4/36Commit cadence2/52 weeks with commits
9.7/18Commit volume11 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year11
human_commit_share0.97
days_since_last_push297
active_weeks_last_year2
How it's scored
27/27Ships releases13 releases published
16.2/36Release recencylatest release 297 days ago
12.6/27Release cadencea release every ~146.4 days
8/10OpenSSF Scorecard: Signed-Releases4 out of the last 5 releases have a total of 4 signed artifacts.
Inputs used
releases_count13
latest_release_tag3.0.3
releases_from_tagsno
days_since_latest_release297
mean_days_between_releases146.4

Community & Adoption

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

82Excellent · 17% of overall
How it's scored
46.1/60Stars693 stars
18.9/25Forks187 forks
8.1/15Watchers30 watchers
Inputs used
forks187
stars693
watchers30
growth_stateorganic
growth_factor_pct100

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (BSD-3-Clause)
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_badges
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services
has_pull_request_templateyes

Sustainability & Governance

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

72Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
4.5/22.5Commit distributiontop contributor authored 80% of commits
13.5/13.5Contributor breadth43 contributors
10/10OpenSSF Scorecard: Contributorsproject has 17 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled43
top_contributor_share0.802
How it's scored
40.5/42Issue resolution96% of issues closed
23.4/30PR acceptance285/366 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
1.5/15OpenSSF Scorecard: Code-ReviewFound 3/22 approved changesets -- score normalized to 1
Inputs used
merged_prs285
open_issues5
closed_issues139
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.965
closed_unmerged_prs81
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
24.3/25Owner reach2,372 followers of pallets
21.1/25Track record17 public repos, account ~10 yr old
Inputs used
followers2,372
owner_typeOrganization
is_verified
owner_loginpallets
public_repos17
account_age_days3,838
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
26/35Publish recencylatest publish 297 days ago
20/20Version history35 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesMarkupSafe
ecosystemspypi
any_deprecatedno
min_days_since_publish297

Engineering Quality

Are baseline engineering and documentation practices in place?

91Excellent · 19% of overall
How it's scored
24/24CI workflows4 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
6.4/6.4.editorconfig
12/20OpenSSF Scorecard: CI-Tests6 out of 10 merged PRs checked by a CI test -- score normalized to 6
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://markupsafe.palletsprojects.com
10/10Repository description
10/10Topics7 topics
0/10Wiki
Inputs used
topicspython, html, template-engine, html-escape, markupsafe, jinja, pallets
has_wikino
homepagehttps://markupsafe.palletsprojects.com
docs_sitehttps://markupsafe.palletsprojects.com
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

57Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
2.2/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
1.5/2.5CI-Tests6 out of 10 merged PRs checked by a CI test -- score normalized to 6
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0.8/7.5Code-ReviewFound 3/22 approved changesets -- score normalized to 1
2.5/2.5Contributorsproject has 17 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
5/5Fuzzingproject is fuzzed
2.5/2.5Licenselicense file detected
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
5/5Packagingpackaging workflow detected
4.5/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 9
0/5SASTSAST tool is not run on all commits -- score normalized to 0
4.5/5Security-Policysecurity policy file detected
6/7.5Signed-Releases4 out of the last 5 releases have a total of 4 signed artifacts.
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities22 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate5.7

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.

61Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
13.7/40Legible commit history25 of 97 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.258
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapdocs/Makefile
22/22Automated tests
11/11Lint / format config
11/11Static type checkingsrc/markupsafe/py.typed
10/10Reproducible environmentdevcontainer, lockfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance2 of the last 100 commits are automated dependency updates
9/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 9
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontaineryes
has_linter_configyes
typecheck_configssrc/markupsafe/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.02
How it's scored
27/45Type-checkable codePython with type-check config (src/markupsafe/py.typed)
55/55Manageable file sizes0/13 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes12,736
source_files_sampled13
oversized_source_files0

Key facts

693GitHub stars
43contributors
11commits, last 12 months
297days since last push
13releases
1bus factor
5open issues
PyPIpackage ecosystems

More detail

Star and fork history 693 ★ / 187 ⇿
693Stars
187Forks
13Releases

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.

0125250375500625750693180182010-062018-072026-07
Major 2Minor 1Patch 9

Each point covers 15 days.

OpenSSF Scorecard 5.7 / 10
5.7aggregate

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 · 2026-07-22 01:37 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
6CI-Tests6 out of 10 merged PRs checked by a CI test -- score normalized to 6
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 3/22 approved changesets -- score normalized to 1
10Contributorsproject has 17 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
10Fuzzingproject is fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
10Packagingpackaging workflow detected
9Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 9
0SASTSAST tool is not run on all commits -- score normalized to 0
9Security-Policysecurity policy file detected
8Signed-Releases4 out of the last 5 releases have a total of 4 signed artifacts.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities22 existing vulnerabilities detected
All dependencies 0

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

RegistryPackageVersionRelation
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies to assess

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 v0.26.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.