Public record
Software health reportschema 0.26.0 · metrics 2.10.0 · 2026-07-22 11:44 UTC

ev-flow / quark-engine

PythonGPL-3.0★ 1,697 stars⑂ 214 forkssince Oct 2019View on GitHub ↗
#defcon#android#blackhat#blackbox#malware-analysis#malware-detection

ev-flow/quark-engine holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Vitality (99/100) and lowest on Security (62/100). It was last updated 7 days ago. 3 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 81 is calibrated to 94 on the published index scale (record calibration 2026-08-02).

Ownership

Even Flow FoundationOrganization
40 followers24 public repossince Oct 2019

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIquark-enginepoints to another repo — not scored26.7.117,3617920 days ago

Metrics by category

Vitality

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

99Exceptional · 21% of overall

Development activity

99Exceptional
How it's scored
36/36Push recency — last push 7 days ago
34.6/36Commit cadence — 50/52 weeks with commits
18/18Commit volume — 119 commits in the last year
10/10OpenSSF Scorecard: Maintained — 25 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year119
human_commit_share0.78
days_since_last_push7
active_weeks_last_year50

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 84 releases published
36/36Release recency — latest release 20 days ago
27/27Release cadence — a release every ~33.5 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count84
latest_release_tagv26.7.1
releases_from_tagsno
days_since_latest_release20
mean_days_between_releases33.5
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?

67Good · 17% of overall

Popularity & adoption

81Excellent
How it's scored
52.4/60Stars — 1,697 stars
19.4/25Forks — 214 forks
8.8/15Watchers — 39 watchers
Inputs used
forks214
stars1,697
watchers39
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

50Moderate
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (GPL-3.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges—
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno

Sustainability & Governance

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

80Excellent · 23% of overall

Maintainer resilience (bus factor)

74Good
How it's scored
36/54Bus factor — 3 contributor(s) cover half of all commits
14.8/22.5Commit distribution — top contributor authored 34% of commits
13.5/13.5Contributor breadth — 31 contributors
10/10OpenSSF Scorecard: Contributors — project has 6 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled31
top_contributor_share0.34

Issue & PR responsiveness

86Excellent
How it's scored
34.4/42Issue resolution — 82% of issues closed
25.6/30PR acceptance — 518/608 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Inputs used
merged_prs518
open_issues57
closed_issues257
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio0.818
closed_unmerged_prs90
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.

Ownership & stewardship

80Excellent
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain — verified-domain status not read for this organization
11.6/25Owner reach — 40 followers of ev-flow
22.2/25Track record — 24 public repos, account ~6 yr old
Inputs used
followers40
owner_typeOrganization
is_verified—
owner_loginev-flow
public_repos24
account_age_days2,456
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

92Excellent · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 14 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 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 site — https://doc.quark-engine.com
0/10Repository description
10/10Topics — 6 topics
10/10Wiki
Inputs used
topicsdefcon, android, blackhat, blackbox, malware-analysis, malware-detection
has_wikiyes
homepagehttps://doc.quark-engine.com
docs_sitehttps://doc.quark-engine.com
has_readmeyes
has_docs_diryes
has_descriptionno

Security

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

62Moderate · 16% of overall

Security posture

53Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.5/2.5CI-Tests — 30 out of 30 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
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 6 contributing companies or organizations
0/10Dangerous-Workflow — dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 25 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
5/5SAST — SAST tool is run on all commits
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 26 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5.3
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 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_packages44
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:quark-engine@26.7.1 runtime dependency closure — what installing the published package pulls in — 44 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.

79Good · 4% of overall

Agent context & guidance

82Excellent
How it's scored
45/45Agent instructions — CLAUDE.md
0/15Machine-readable docs (llms.txt)
36.9/40Legible commit history — 54 of 78 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.692
agent_instruction_filesCLAUDE.md
agent_instruction_max_bytes6,692

Verify loop (build / test / typecheck)

77Good
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config
0/11Static type checking
10/10Reproducible environment — Dockerfile, lockfile
8/10Demonstrated agent practice — 4 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 12 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesPipfile.lock
has_dockerfileyes
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.04
toolchain_manifests—
dependency_bot_commit_share0.12

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/95 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes38,670
source_files_sampled95
oversized_source_files0

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — demos, examples
Inputs used
example_dirsdemos, examples
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

1,697GitHub stars
31contributors
119commits, last 12 months
7days since last push
84releases
3bus factor
57open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi package 'quark-engine' points at a different repository (https://github.com/quark-engine/quark-engine); excluded from ecosystem scoring

More detail

Star and fork history 0 ★ / 214 ⇿
0Stars
214Forks
83Releases

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.

0408012016020024021262019-112023-032026-07
Major 0Minor 0Patch 77

Each point covers 7 days.

OpenSSF Scorecard 5.3 / 10
5.3aggregate

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 · 2026-07-22 11:44 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 6 contributing companies or organizations
0Dangerous-Workflowdangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained25 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool is run on all commits
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities26 existing vulnerabilities detected
All dependencies 132

Full resolved dependency set from the GitHub dependency graph: 0 direct and 132 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIalabaster—indirect
PyPIalabaster1.0.0indirect
PyPIandroguard3.4.0a1indirect
PyPIannotated-types0.7.0indirect
PyPIanyio4.12.1indirect
PyPIasn1crypto1.5.1indirect
PyPIasttokens3.0.1indirect
PyPIbabel2.17.0indirect
PyPIblack26.3.1indirect
PyPIcertifi2026.1.4indirect
PyPIcharset-normalizer3.4.4indirect
PyPIcli-helpers2.7.0indirect
PyPIclick—indirect
PyPIclick8.0.4indirect
PyPIclick-default-group1.2.4indirect
PyPIcolorama—indirect
PyPIcolorama0.4.4indirect
PyPIcommonmark—indirect
PyPIcondense-json0.1.3indirect
PyPIconfigobj5.0.9indirect
PyPIcontourpy1.3.2indirect
PyPIcycler0.12.1indirect
PyPIdecorator5.2.1indirect
PyPIdelegator-py0.1.1indirect
PyPIdextrace—indirect
PyPIdistro1.9.0indirect
PyPIdocutils0.21.2indirect
PyPIexceptiongroup1.3.1indirect
PyPIexecuting2.2.1indirect
PyPIflask3.1.3indirect
PyPIfonttools4.61.1indirect
PyPIfrida15.2.2indirect
PyPIfrida-tools11.0.0indirect
PyPIgraphviz—indirect
PyPIgraphviz0.18.2indirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpx0.28.1indirect
PyPIidna3.11indirect
PyPIimagesize1.4.1indirect
PyPIiniconfig2.3.0indirect
PyPIipython8.18.0indirect
PyPIitsdangerous2.2.0indirect
PyPIjedi0.19.2indirect
PyPIjinja2—indirect
PyPIjinja23.1.6indirect
PyPIjiter0.12.0indirect
PyPIkiwisolver1.4.10rc0indirect
PyPIlangchain0.2.11indirect
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PyPImatplotlib-inline0.2.1indirect
PyPImock—indirect
PyPImypy1.19.1indirect
PyPImypy-extensions1.1.0indirect
PyPInetworkx3.4.2indirect
PyPInumpy2.2.6indirect
PyPIobjection1.11.0indirect
PyPIopenai2.15.0indirect
PyPIpackaging26.0rc2indirect
PyPIparso0.8.5indirect
PyPIpathspec1.0.3indirect
PyPIpathvalidate3.2.3indirect
PyPIpexpect4.9.0indirect
PyPIpillow—indirect
PyPIpillow12.1.0indirect
PyPIpip26.1.2indirect
PyPIplatformdirs4.9.4indirect
PyPIplotly—indirect
PyPIplotly5.4.0indirect
PyPIpluggy1.6.0indirect
PyPIprettytable—indirect
PyPIprettytable2.4.0indirect
PyPIprompt-toolkit—indirect
PyPIprompt-toolkit3.0.36indirect
PyPIptyprocess0.7.0indirect
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PyPIpuremagic1.30indirect
PyPIpydantic2.12.5indirect
PyPIpydantic-core2.41.5indirect
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PyPIpygments2.20.0indirect
PyPIpyparsing3.3.1indirect
PyPIpytest9.0.3indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-ulid3.1.0indirect
PyPIpytokens0.4.1indirect
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PyPIr2pipe1.8.0indirect
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PyPIrecommonmark—indirect
PyPIrequests2.33.0indirect
PyPIrzpipe—indirect
PyPIrzpipe0.1.2indirect
PyPIsemver2.13.0indirect
PyPIsetuptools80.9.0indirect
PyPIsix1.17.0indirect
PyPIsniffio1.3.1indirect
PyPIsnowballstemmer3.0.1indirect
PyPIsphinx—indirect
PyPIsphinx8.1.3indirect
PyPIsphinx-rtd-theme—indirect
PyPIsphinx-rtd-theme3.1.0indirect
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
PyPIsqlite-fts41.0.3indirect
PyPIsqlite-migrate0.1b0indirect
PyPIsqlite-utils4.0a1indirect
PyPIsqlparse0.5.5indirect
PyPIstack-data0.6.3indirect
PyPItabulate0.9.0indirect
PyPItenacity9.1.2indirect
PyPItomli2.4.0indirect
PyPItqdm—indirect
PyPItqdm4.66.5indirect
PyPItraitlets5.14.3indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPIurllib32.6.3indirect
PyPIwcwidth0.2.14indirect
PyPIwerkzeug3.1.6indirect
Dependency advisories 0

Installing pypi:quark-engine@26.7.1 pulls in 44 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.

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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 v0.26.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.