Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-28 18:38 UTC

CiscoISE / ciscoisesdk

Cisco Identity Services Engine Platform SDK for Python

PythonMIT★ 70 stars⑂ 17 forkssince May 2021View on GitHub ↗

CiscoISE/ciscoisesdk holds a health index of 81 out of 100, placing it in the Excellent band. It scores highest on Vitality (76/100) and lowest on AI Readiness (54/100). It was last updated today. A single contributor accounts for most of its recent work.

81
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.

81
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 69 is calibrated to 81 on the published index scale (record calibration 2026-08-02).

Ownership

61 followers9 public repossince May 2021

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIciscoisesdk2.4.6145,762510 days agociscoidentity-services-enginesdk

Metrics by category

Vitality

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

76Good · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
6.9/36Commit cadence10/52 weeks with commits
13.6/18Commit volume32 commits in the last year
10/10OpenSSF Scorecard: Maintained15 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year32
human_commit_share0.96
days_since_last_push0
active_weeks_last_year10
How it's scored
27/27Ships releases50 releases published
36/36Release recencylatest release 0 days ago
19.8/27Release cadencea release every ~83.7 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count50
latest_release_tagv2.4.6
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases83.7
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?

64Moderate · 17% of overall
How it's scored
29.8/60Stars70 stars
10/25Forks17 forks
5.6/15Watchers11 watchers
Inputs used
forks17
stars70
watchers11
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized 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_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno
How it's scored
68.8/80Monthly downloads145,762 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesciscoisesdk
dependents
ecosystemspypi
total_downloads
monthly_downloads145,762
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?

67Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
6.5/22.5Commit distributiontop contributor authored 71% of commits
6.8/13.5Contributor breadth5 contributors
10/10OpenSSF Scorecard: Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
Inputs used
bus_factor1
contributors_sampled5
top_contributor_share0.709
How it's scored
39/42Issue resolution93% of issues closed
24.4/30PR acceptance48/59 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
15/15OpenSSF Scorecard: Code-Reviewall changesets reviewed
Inputs used
merged_prs48
open_issues3
closed_issues39
prs_merged_7d1
prs_decided_7d1
prs_merged_30d1
prs_decided_30d1
issue_closed_ratio0.929
closed_unmerged_prs11
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 backingorganization-owned
0/20Verified domain
12.9/25Owner reach61 followers of CiscoISE
17.9/25Track record9 public repos, account ~5 yr old
Inputs used
followers61
owner_typeOrganization
is_verifiedno
owner_loginCiscoISE
public_repos9
account_age_days1,938

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 0 days ago
20/20Version history51 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesciscoisesdk
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

74Good · 19% of overall
How it's scored
24/24CI workflows1 workflow(s)
24/24Tests present
16/16Linter config.flake8
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 11 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://ciscoisesdk.readthedocs.io/en/latest/
10/10Repository description
10/10Topics4 topics
0/10Wiki
Inputs used
topicspython, ise, cisco, identity-services-engine
has_wikino
homepagehttps://ciscoisesdk.readthedocs.io/en/latest/
docs_sitehttps://ciscoisesdk.readthedocs.io/en/latest/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

66Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
0/2.5CI-Tests0 out of 11 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Reviewall changesets reviewed
2.5/2.5Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
0/10Dangerous-Workflowdangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained15 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
6.8/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
6.8/7.5Vulnerabilities1 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate5.7
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories2
affected_packages1
assessed_packages58
unassessed_packages3
affected_by_severitymoderate 1
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 58 resolved dependencies against OSV. 3 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

54Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
32.8/40Legible commit history59 of 96 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.615
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapdocs/Makefile
22/22Automated tests
11/11Lint / format config.flake8
0/11Static type checking
10/10Reproducible environmentlockfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance2 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesPipfile.lock, poetry.lock
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.02
How it's scored
0/45Type-checkable codePython without a type-check config
54/55Manageable file sizes101/5,689 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes1,004,367
source_files_sampled5,689
oversized_source_files101

Key facts

70GitHub stars
5contributors
32commits, last 12 months
0days since last push
50releases
1bus factor
3open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:ciscoisesdk@2.4.6; advisories assessed against the repository dependency graph instead

More detail

Star and fork history 0 ★ / 17 ⇿
0Stars
17Forks
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.

0481216201722021-062023-082025-10
Major 2Minor 9Patch 26

Each point covers 4 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 · 2026-08-28 18:37 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-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
0CI-Tests0 out of 11 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
0Dangerous-Workflowdangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained15 commit(s) and 0 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
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
9Token-Permissionsdetected GitHub workflow tokens with excessive permissions
9Vulnerabilities1 existing vulnerabilities detected
Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPIrequests^2.33.0pyproject.toml
PyPIfastjsonschema^2.16.2pyproject.toml
PyPIrequests-toolbelt^1.0.0pyproject.toml
PyPIxmltodict1.0.4pyproject.toml
All dependencies 61

Full resolved dependency set from the GitHub dependency graph: 8 direct and 53 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIfastjsonschemadirect
PyPIfastjsonschema2.21.2direct
PyPIrequestsdirect
PyPIrequests2.34.2direct
PyPIrequests-toolbeltdirect
PyPIrequests-toolbelt1.0.0direct
PyPIxmltodict1.0.2direct
PyPIxmltodict1.0.4direct
PyPIalabaster0.7.16indirect
PyPIasttokens3.0.1indirect
PyPIbabel2.18.0indirect
PyPIcertifi2026.6.17indirect
PyPIcharset-normalizer3.4.7indirect
PyPIcolorama0.4.6indirect
PyPIdecorator5.3.1indirect
PyPIdocutils0.18.1indirect
PyPIexecuting2.2.1indirect
PyPIflake87.3.0indirect
PyPIidna3.18indirect
PyPIimagesize1.5.0indirect
PyPIiniconfig2.3.0indirect
PyPIipython9.14.1indirect
PyPIipython-pygments-lexers1.1.1indirect
PyPIjedi0.20.0indirect
PyPIjinja23.1.6indirect
PyPImarkupsafe3.0.3indirect
PyPImatplotlib-inline0.2.2indirect
PyPImccabe0.7.0indirect
PyPIpackaging26.2indirect
PyPIparso0.8.7indirect
PyPIpexpect4.9.0indirect
PyPIpluggy1.6.0indirect
PyPIprompt-toolkit3.0.52indirect
PyPIpsutil7.2.2indirect
PyPIptyprocess0.7.0indirect
PyPIpure-eval0.2.3indirect
PyPIpycodestyle2.14.0indirect
PyPIpyflakes3.4.0indirect
PyPIpygments2.20.0indirect
PyPIpytest9.1.1indirect
PyPIpytest-rerunfailures10.3indirect
PyPIreadthedocs-sphinx-search0.3.2indirect
PyPIroman-numerals4.1.0indirect
PyPIsetuptools82.0.1indirect
PyPIsetuptools-scm6.4.2indirect
PyPIsnowballstemmer3.1.1indirect
PyPIsphinx5.3.0indirect
PyPIsphinx-rtd-theme1.3.0indirect
PyPIsphinxcontrib-applehelp2.0.0indirect
PyPIsphinxcontrib-devhelp2.0.0indirect
PyPIsphinxcontrib-htmlhelp2.1.0indirect
PyPIsphinxcontrib-jquery4.1indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
PyPIsphinxcontrib-qthelp2.0.0indirect
PyPIsphinxcontrib-serializinghtml2.0.0indirect
PyPIstack-data0.6.3indirect
PyPItomli2.4.1indirect
PyPItraitlets5.15.1indirect
PyPIurllib32.7.0indirect
PyPIvcs-versioning2.0.1indirect
PyPIwcwidth0.8.1indirect
Dependency advisories 1

This repository publishes no package the index resolves, so its own dependency graph was assessed — 58 packages, which also include development and test pins that never ship: 1 carry known advisories, of which 0 are direct. 3 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
setuptools82.0.1indirectmoderate283.0.0

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.

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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 statisticsPyPI.