Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-28 02:17 UTC

PyCQA / bandit

Bandit is a tool designed to find common security issues in Python code.

PythonApache-2.0★ 8,243 stars⑂ 828 forkssince Apr 2018View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

PyCQA/bandit holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Community & Adoption (93/100) and lowest on AI Readiness (59/100). It was last updated 3 days ago. 2 contributors account for most of its recent work.

94
overall / 100
Exceptional

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.

94
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 80 is calibrated to 94 on the published index scale (record calibration 2026-08-02).

Ownership

1,026 followers29 public repossince Sep 2014

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIbandit1.9.429,052,17450183 days ago

Metrics by category

Vitality

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

74Good · 21% of overall
How it's scored
36/36Push recencylast push 3 days ago
20.1/36Commit cadence29/52 weeks with commits
15.3/18Commit volume49 commits in the last year
6/10OpenSSF Scorecard: Maintained7 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 6
Inputs used
commits_last_year49
human_commit_share0.43
days_since_last_push3
active_weeks_last_year29
How it's scored
27/27Ships releases29 releases published
16.2/36Release recencylatest release 183 days ago
19.8/27Release cadencea release every ~45.4 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count29
latest_release_tag1.9.4
releases_from_tagsno
days_since_latest_release183
mean_days_between_releases45.4
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?

93Exceptional · 17% of overall
How it's scored
60/60Stars8,243 stars
24.3/25Forks828 forks
10.3/15Watchers71 watchers
Inputs used
forks828
stars8,243
watchers71
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (Apache-2.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges8
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesgithub.com, readthedocs.org, shields.io
has_pull_request_templateno
How it's scored
80/80Monthly downloads29,052,174 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesbandit
dependents
ecosystemspypi
total_downloads
monthly_downloads29,052,174
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?

72Good · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
11.5/22.5Commit distributiontop contributor authored 49% of commits
13.5/13.5Contributor breadth98 contributors
10/10OpenSSF Scorecard: Contributorsproject has 28 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled98
top_contributor_share0.491
How it's scored
30.7/42Issue resolution73% of issues closed
24.3/30PR acceptance489/604 decided PRs merged
0/13Newcomer PR acceptance0/2 first-time contributors' PRs merged in 30d
15/15OpenSSF Scorecard: Code-Reviewall changesets reviewed
Inputs used
merged_prs489
open_issues193
closed_issues527
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d2
issue_closed_ratio0.732
closed_unmerged_prs115
first_time_authors_30d2
first_time_prs_merged_30d0
first_time_prs_decided_30d2
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domain
21.7/25Owner reach1,026 followers of PyCQA
22.8/25Track record29 public repos, account ~11 yr old
Inputs used
followers1,026
owner_typeOrganization
is_verifiedno
owner_loginPyCQA
public_repos29
account_age_days4,367
How it's scored
25/25Published & resolvable1 package(s) on pypi
26/35Publish recencylatest publish 183 days ago
20/20Version history50 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesbandit
ecosystemspypi
any_deprecatedno
min_days_since_publish183

Engineering Quality

Are baseline engineering and documentation practices in place?

92Excellent · 19% of overall
How it's scored
24/24CI workflows5 workflow(s)
24/24Tests present
16/16Linter configtox.ini
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://bandit.readthedocs.io
10/10Repository description
10/10Topics7 topics
0/10Wiki
Inputs used
topicslinter, bandit, security-tools, security-scanner, security, static-code-analysis, python
has_wikino
homepagehttps://bandit.readthedocs.io
docs_sitehttps://bandit.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

75Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
2.5/2.5CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
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 28 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
4.5/7.5Maintained7 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 6
5/5Packagingpackaging workflow detected
0.5/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 1
0/5SASTSAST tool is not run on all commits -- score normalized to 0
5/5Security-Policysecurity policy file detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
6.8/7.5Vulnerabilities1 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6.9
Excluded from scoring (no data or not applicable): Branch-Protection, 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
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages6
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:bandit@1.9.4 runtime dependency closure — what installing the published package pulls in — 6 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.

59Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history43 of 43 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share1
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format configtox.ini
0/11Static type checking
10/10Reproducible environmentDockerfile
8/10Demonstrated agent practice4 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance48 of the last 100 commits are automated dependency updates
1/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 1
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileyes
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0.04
toolchain_manifests
dependency_bot_commit_share0.48
How it's scored
0/45Type-checkable codePython without a type-check config
54.7/55Manageable file sizes1/196 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes65,560
source_files_sampled196
oversized_source_files1
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesexamples
Inputs used
example_dirsexamples
has_mcp_signalno
api_schema_files
interfaces_expected_of
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

8,243GitHub stars
98contributors
49commits, last 12 months
3days since last push
29releases
2bus factor
193open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 828 ⇿
0Stars
828Forks
29Releases

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.

02004006008001,000814102018-042022-062026-08
Major 0Minor 5Patch 24

Each point covers 8 days.

OpenSSF Scorecard 6.9 / 10
6.9aggregate

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 02:16 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
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 28 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
6Maintained7 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 6
10Packagingpackaging workflow detected
1Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 1
0SASTSAST tool is not run on all commits -- score normalized to 0
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
9Vulnerabilities1 existing vulnerabilities detected
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
PyPIbeautifulsoup4indirect
PyPIcoloramaindirect
PyPIcoverageindirect
PyPIflake8indirect
PyPIpylint1.9.4indirect
PyPIpyyamlindirect
PyPIrichindirect
PyPIsphinxindirect
PyPIsphinx-copybuttonindirect
PyPIsphinx-rtd-themeindirect
PyPIstestrindirect
PyPIstevedoreindirect
PyPItesttoolsindirect
Dependency advisories 0

Installing pypi:bandit@1.9.4 pulls in 6 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 statisticsPyPI.