Leaderboard github.com
chr1shaefn3r/grow-up
build an eye-aligned face timelapse from photos of one person in an Immich library
AI provenance
100%
explicit
- Confidence
- 89%
- Coverage
- 100%
Estimated share of AI-generated code. Explicit attribution is a lower bound.
Code quality
77/100
adequate
- Confidence
- 90%
- Coverage
- 100%
Complexity, duplication, lint density, tests, CI, docs and review process.
Security
74/100
adequate
- Confidence
- 85%
- Coverage
- 100%
Secrets, static analysis, vulnerable dependencies, CI and supply-chain posture.
AI provenance
100% explicit
Explicit AI attribution on 100% of first-party code added; an estimated 100% including velocity signals.
How the score is built
- Explicitly attributed share100%
- Unattributed share in AI-pace bursts0%
- Estimated AI-generated share100%
- AI tool configuration files3
- Work sessions at AI pace3
- Releases at AI pace0
- Coding-style index (1.0+ means possible)0.24
Attributed AI tools
| Tool | Commits | Lines added | First seen | Last seen |
|---|---|---|---|---|
| Claude Code | 74 | 19,735 | 2026-08-08 | 2026-11-05 |
Lines added per month all AI-attributed share
- 2026-0813,693 · 100% AI
- 2026-10458 · 100% AI
- 2026-115,584 · 100% AI
Findings in AI-attributed lines vs the rest
From git blame: 8,331 lines trace to AI-attributed commits, 0 to others. Too few lines in one group for a fair comparison. Reported, not scored.
| Findings per 1,000 lines | AI-attributed | Other | Ratio |
|---|---|---|---|
| Code quality | 2.40 | — | — |
| Security | 1.56 | — | — |
Evidence by analyzer
Explicit AI attributionok26 items
- Claude Code: 74 attributed commits, 19,735 lines added
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- Claude Code: author email [email protected]
- attributed_commit_share
- 97.4%
- attributed_commits
- 74
- attributed_loc
- 19,735
- attributed_loc_share
- 100.0%
- commits
- 76
- effective_loc
- 19,735
- tools_detected
- 1
AI tool configurationok3 items
- .claude/hooks/session-start.sh (claude-code configuration)
- .claude/settings.json (claude-code configuration)
- CLAUDE.md (claude-code configuration)
- artifacts
- 3
- earliest_adoption
- 2026-08-10
- tools_configured
- 1
- workflow_agents
- 0
Commit velocityok3 items
- 1,036 lines of first-party code in ~1.4h (724 lines/hour, 2 commit session)
- 1,602 lines of first-party code in ~2.4h (658 lines/hour, 5 commit session)
- 3,277 lines of first-party code in ~5.2h (630 lines/hour, 10 commit session)
- excluded_import_loc
- 3,200
- flagged_loc
- 5,915
- flagged_loc_share
- 35.8%
- flagged_units
- 3
- max_loc_per_hour
- 723.77
- measured_loc
- 16,535
- median_loc_per_hour
- 153.25
- pr_timed_units
- 0
- pre_ai_era_burst_loc
- 0
- pre_ai_era_bursts
- 0
- pre_ai_era_measured_loc
- 0
- work_units
- 26
Release velocityok
- flagged_releases
- 0
- max_loc_per_day
- 28,323.40
- releases
- 10
Coding styleok2 items
- step-by-step narration comment: // first, and relabelling "the first button" turned it into a second reject.
- step-by-step narration comment: # first, and sizing it from only gaze_x, hid that it also decides gaze
- count:assistant_voice
- 0
- count:emoji_in_code
- 0
- count:narrated_steps
- 2
- count:placeholder
- 0
- files:assistant_voice
- 0
- files:emoji_in_code
- 0
- files:narrated_steps
- 1
- files:placeholder
- 0
- index
- 0.24
- lines_scanned
- 8,331
- per_kloc:assistant_voice
- 0
- per_kloc:emoji_in_code
- 0
- per_kloc:narrated_steps
- 0.24
- per_kloc:placeholder
- 0
Findings in AI-written linesok
- ai_lines
- 8,331
- blame_failures
- 0
- files_blamed
- 18
- other_lines
- 0
- quality:ai_findings
- 20
- quality:ai_per_kloc
- 2.40
- quality:other_findings
- 0
- security:ai_findings
- 13
- security:ai_per_kloc
- 1.56
- security:other_findings
- 0
Code quality
77 adequate
Code quality is adequate: test-to-source ratio 1.21, CI runs tests; 8% of function code in complex or long functions; 0% duplicated lines. Weakest area: type safety.
How the score is built
- Complexity79
- Duplication98
- Lint and smells53
- Tests and CI90
- Documentation65
- Type safety40
- Review processnot measured
Evidence by analyzer
Complexity (lizard)ok4 items
- stage_encode in src/grow_up/pipeline.py: complexity 33, 86 lines
- write_rejects_gallery in src/grow_up/review.py: complexity 28, 103 lines
- render in src/grow_up/morph.py: complexity 18, 43 lines
- stage_align in src/grow_up/pipeline.py: complexity 16, 59 lines
- complex_functions
- 4
- function_nloc
- 3,789
- functions
- 312
- long_functions
- 1
- many_param_functions
- 6
- mean_ccn
- 3.68
- p90_ccn
- 8
- risky_nloc_share
- 7.7%
Duplication (jscpd)ok1 item
- compared_lines
- 6,466
- duplicated_lines
- 18
- duplicated_share
- 0.3%
- files
- 18
Lintok
- category:correctness
- 14
- category:maintainability
- 6
- findings
- 20
- scanned_lines
- 8,331
- weighted_findings
- 21.25
Tests and CIok2 items
- CI config: .github/workflows/tests.yml
.github/workflows/tests.yml - CI runs tests (pytest)
- check:ci_present
- yes
- check:ci_runs_lint
- no
- check:ci_runs_tests
- yes
- check:has_tests
- yes
- check:test_ratio
- yes
- check:tests_cochange
- yes
- ci_files
- 1
- cochange_commits
- 62
- cochange_share
- 83.9%
- source_lines
- 8,331
- test_lines
- 10,063
- test_ratio
- 1.21
Documentationok2 items
- README.md
README.md - LICENSE
LICENSE
- check:changelog
- no
- check:contributing
- no
- check:license
- yes
- check:readme
- yes
- readme_lines
- 686
Type safetyok
- check:low_escape_density
- yes
- check:strict_config
- no
- escapes
- 11
- escapes_per_kloc
- 1.33
Security
74 adequate
Security posture is adequate: 9 high-severity SAST findings; 2 high-severity workflow issues. Weakest area: posture.
How the score is built
- Secrets100
- Static analysis (SAST)72
- Vulnerable dependenciesnot measured
- CI workflows67
- Security posture20
- OpenSSF Scorecardnot measured
Evidence by analyzer
OpenSSF Scorecardskipped
no published OpenSSF Scorecard result for this repo
Package registriesok
- checked
- 7
- declared
- 7
- lookup_errors
- 0
- missing
- 0
- recent
- 0
Secrets (gitleaks)ok
- secrets_current
- 0
- secrets_history
- 0
- secrets_low_confidence
- 0
- secrets_nonprod
- 0
Static analysis (opengrep)ok
- findings
- 13
- findings_high
- 9
- findings_low
- 0
- findings_medium
- 4
- parse_errors
- 0
- scanned_lines
- 8,331
- weighted_findings
- 7.75
Dependencies (osv-scanner)skipped
CI workflows (zizmor)ok
- findings
- 3
- findings_high
- 2
- findings_low
- 1
- findings_medium
- 0
- penalty
- 24.30
- workflows
- 1
Security postureok
- check:dependency_updates
- no
- check:lockfiles
- yes
- check:security_policy
- no
- check:signed_commits
- yes
- signed_commit_share
- 98.7%
- unpinned_manifests
- 0
Release downloadsok1 item
- gives an archive password
README.md
- binary_assets
- 0
- signals
- 1
- suspicious
- 0
Findings
12 high22 medium2 low
36 findings
| Severity | Rule | Location | Message | Tool |
|---|---|---|---|---|
| high | opengrep/python.lang.correctness.return-in-init |
src/grow_up/progress.py:53 | `return` should never appear inside a class __init__ function. This will cause a runtime error. | Lint |
| high | zizmor/unpinned-uses |
.github/workflows/tests.yml:25 | unpinned action reference [confidence high] | CI workflows (zizmor) |
| high | zizmor/unpinned-uses |
.github/workflows/tests.yml:27 | unpinned action reference [confidence high] | CI workflows (zizmor) |
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query |
src/grow_up/cli.py:755 | Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used... | Static analysis (opengrep) |
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query |
src/grow_up/db.py:203 | Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used... | Static analysis (opengrep) |
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query |
src/grow_up/db.py:206 | Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used... | Static analysis (opengrep) |
| high | opengrep/python.lang.security.audit.dangerous-subprocess-use-audit |
src/grow_up/encode.py:371 | Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external... | Static analysis (opengrep) |
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query |
src/grow_up/pipeline.py:249 | Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used... | Static analysis (opengrep) |
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query |
src/grow_up/pipeline.py:315 | Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used... | Static analysis (opengrep) |
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query |
src/grow_up/pipeline.py:425 | Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used... | Static analysis (opengrep) |
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query |
src/grow_up/pipeline.py:488 | Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used... | Static analysis (opengrep) |
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query |
src/grow_up/pipeline.py:551 | Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used... | Static analysis (opengrep) |
| medium | opengrep/python.lang.maintainability.is-function-without-parentheses |
src/grow_up/cli.py:247 | Is "is_full" a function or an attribute? If it is a function, you may have meant watermark.is_full() because watermark.is_full is always true. | Lint |
| medium | opengrep/python.lang.correctness.common-mistakes.string-concat-in-list |
src/grow_up/db.py:381 | Detected strings that are implicitly concatenated inside a list. Python will implicitly concatenate strings when not explicitly delimited. Was this supposed to be individual elements of the list? | Lint |
| medium | opengrep/python.lang.correctness.common-mistakes.string-concat-in-list |
src/grow_up/encode.py:271 | Detected strings that are implicitly concatenated inside a list. Python will implicitly concatenate strings when not explicitly delimited. Was this supposed to be individual elements of the list? | Lint |
| medium | opengrep/python.lang.correctness.common-mistakes.string-concat-in-list |
src/grow_up/encode.py:281 | Detected strings that are implicitly concatenated inside a list. Python will implicitly concatenate strings when not explicitly delimited. Was this supposed to be individual elements of the list? | Lint |
| medium | opengrep/python.lang.correctness.common-mistakes.string-concat-in-list |
src/grow_up/encode.py:308 | Detected strings that are implicitly concatenated inside a list. Python will implicitly concatenate strings when not explicitly delimited. Was this supposed to be individual elements of the list? | Lint |
| medium | opengrep/python.lang.maintainability.is-function-without-parentheses |
src/grow_up/immich.py:219 | Is "is_success" a function or an attribute? If it is a function, you may have meant response.is_success() because response.is_success is always true. | Lint |
| medium | opengrep/python.lang.maintainability.is-function-without-parentheses |
src/grow_up/immich.py:291 | Is "is_success" a function or an attribute? If it is a function, you may have meant response.is_success() because response.is_success is always true. | Lint |
| medium | opengrep/python.lang.maintainability.is-function-without-parentheses |
src/grow_up/immich.py:295 | Is "is_success" a function or an attribute? If it is a function, you may have meant response.is_success() because response.is_success is always true. | Lint |
| medium | opengrep/python.lang.maintainability.is-function-without-parentheses |
src/grow_up/immich.py:434 | Is "is_success" a function or an attribute? If it is a function, you may have meant response.is_success() because response.is_success is always true. | Lint |
| medium | opengrep/python.lang.maintainability.is-function-without-parentheses |
src/grow_up/pipeline.py:144 | Is "is_full" a function or an attribute? If it is a function, you may have meant watermark.is_full() because watermark.is_full is always true. | Lint |
| medium | opengrep/python.lang.correctness.common-mistakes.string-concat-in-list |
src/grow_up/progress.py:126 | Detected strings that are implicitly concatenated inside a list. Python will implicitly concatenate strings when not explicitly delimited. Was this supposed to be individual elements of the list? | Lint |
| medium | opengrep/python.lang.correctness.common-mistakes.string-concat-in-list |
src/grow_up/review.py:1203 | Detected strings that are implicitly concatenated inside a list. Python will implicitly concatenate strings when not explicitly delimited. Was this supposed to be individual elements of the list? | Lint |
| medium | opengrep/python.lang.correctness.common-mistakes.string-concat-in-list |
src/grow_up/review.py:1439 | Detected strings that are implicitly concatenated inside a list. Python will implicitly concatenate strings when not explicitly delimited. Was this supposed to be individual elements of the list? | Lint |
| medium | opengrep/python.lang.correctness.common-mistakes.string-concat-in-list |
src/grow_up/timing.py:113 | Detected strings that are implicitly concatenated inside a list. Python will implicitly concatenate strings when not explicitly delimited. Was this supposed to be individual elements of the list? | Lint |
| medium | opengrep/python.lang.correctness.common-mistakes.string-concat-in-list |
src/grow_up/timing.py:115 | Detected strings that are implicitly concatenated inside a list. Python will implicitly concatenate strings when not explicitly delimited. Was this supposed to be individual elements of the list? | Lint |
| medium | opengrep/python.lang.correctness.common-mistakes.string-concat-in-list |
src/grow_up/timing.py:117 | Detected strings that are implicitly concatenated inside a list. Python will implicitly concatenate strings when not explicitly delimited. Was this supposed to be individual elements of the list? | Lint |
| medium | opengrep/python.lang.correctness.common-mistakes.string-concat-in-list |
src/grow_up/timing.py:120 | Detected strings that are implicitly concatenated inside a list. Python will implicitly concatenate strings when not explicitly delimited. Was this supposed to be individual elements of the list? | Lint |
| medium | opengrep/python.lang.correctness.common-mistakes.string-concat-in-list |
src/grow_up/timing.py:122 | Detected strings that are implicitly concatenated inside a list. Python will implicitly concatenate strings when not explicitly delimited. Was this supposed to be individual elements of the list? | Lint |
| medium | opengrep/python.lang.security.audit.dynamic-urllib-use-detected |
src/grow_up/cli.py:188 | Detected a dynamic value being used with urllib. urllib supports 'file://' schemes, so a dynamic value controlled by a malicious actor may allow them to read arbitrary files. Audit uses of urllib calls to ensure user data cannot control... | Static analysis (opengrep) |
| medium | opengrep/python.lang.security.audit.formatted-sql-query |
src/grow_up/cli.py:755 | Detected possible formatted SQL query. Use parameterized queries instead. [confidence low] | Static analysis (opengrep) |
| medium | opengrep/python.lang.security.audit.formatted-sql-query |
src/grow_up/db.py:203 | Detected possible formatted SQL query. Use parameterized queries instead. [confidence low] | Static analysis (opengrep) |
| medium | opengrep/python.lang.security.audit.formatted-sql-query |
src/grow_up/db.py:206 | Detected possible formatted SQL query. Use parameterized queries instead. [confidence low] | Static analysis (opengrep) |
| low | opengrep/bash.lang.correctness.unquoted-variable-expansion-in-command |
.claude/hooks/session-start.sh:28 | Variable expansions must be double-quoted so as to prevent being split into multiple pieces according to whitespace or whichever separator is specified by the IFS variable. If you really wish to split the variable's contents, you may... | Lint |
| low | zizmor/artipacked |
.github/workflows/tests.yml:25 | credential persistence through GitHub Actions artifacts [confidence low] | CI workflows (zizmor) |
Tools and coverage
Every analyzer that ran on this commit. A failed or skipped tool is a coverage gap: its share of the score is left out and the coverage figure drops.
| Analyzer | Pillar | Status | Version | Findings | Note |
|---|---|---|---|---|---|
| AI tool configuration | AI provenance | ok | signatures-v1 | 0 | |
| Explicit AI attribution | AI provenance | ok | signatures-v1 | 0 | |
| Release velocity | AI provenance | ok | prov-4 | 0 | |
| Coding style | AI provenance | ok | — | 0 | |
| Commit velocity | AI provenance | ok | prov-4 | 0 | |
| Findings in AI-written lines | AI provenance | ok | git-blame | 0 | |
| Complexity (lizard) | Code quality | ok | lizard 1.25.1 | 0 | |
| Documentation | Code quality | ok | — | 0 | |
| Duplication (jscpd) | Code quality | ok | repotrust-dup-w6 | 0 | |
| Lint | Code quality | ok | opengrep 1.33.1; rules f1d2b562b414 | 20 | |
| Tests and CI | Code quality | ok | — | 0 | |
| Type safety | Code quality | ok | — | 0 | |
| CI workflows (zizmor) | Security | ok | zizmor 1.32.0 | 3 | |
| Dependencies (osv-scanner) | Security | skipped | — | 0 | |
| Release downloads | Security | ok | — | 0 | |
| Security posture | Security | ok | — | 0 | |
| Package registries | Security | ok | — | 0 | |
| Static analysis (opengrep) | Security | ok | opengrep 1.33.1; rules f1d2b562b414 | 13 | |
| OpenSSF Scorecard | Security | skipped | — | 0 | no published OpenSSF Scorecard result for this repo |
| Secrets (gitleaks) | Security | ok | gitleaks 8.30.1 | 0 |
Score history
Scores from different scoring versions aren't directly comparable.
| Scored | Commit | Scoring | AI provenance | Quality | Security |
|---|---|---|---|---|---|
| 2026-11-14 | 2e2d40c88dc8 | prov-5+qual-2+sec-2 | 100% | 77 | 74 |
| 2026-11-14 | 2e2d40c88dc8 | prov-4+qual-2+sec-2 | 100% | 77 | 74 |
Full text report
- Repository: https://github.com/chr1shaefn3r/grow-up
- Commit:
2e2d40c88dc8dfee0b2ed294184c9f10c95d5d99 - Generated: 2026-11-14T14:52:03+00:00
- Scorer 0.1.0, scoring prov-5+qual-2+sec-2, report schema v2
Scores
| Pillar | Score | Signal | Confidence | Coverage |
|---|---|---|---|---|
| AI provenance (estimated AI-generated share) | 100 | explicit | 89% | 100% |
| Code quality | 77 | adequate | 90% | 100% |
| Security | 74 | adequate | 85% | 100% |
AI provenance
Explicit AI attribution on 100% of first-party code added; an estimated 100% including velocity signals.
- Explicitly attributed share (lower bound): 100.0%
- Unattributed share in AI-consistent velocity bursts: 0.0%
- Estimated AI-generated share: 100.0%
| AI tool | Attributed commits | Lines added |
|---|---|---|
| Claude Code | 74 | 19,735 |
- AI tooling configured in repo: claude-code
Current source lines last changed by AI-attributed commits: 8,331 of 8,331.
Too few lines in one group to compare finding densities.
- Stylometry index: 0.24 per 1,000 lines (narrated steps 2, placeholders 0, assistant phrasing 0, emoji 0). Reported as a signal, not scored.
| Month | Lines added | Attributed to AI |
|---|---|---|
| 2026-08 | 13,693 | 100% |
| 2026-10 | 458 | 100% |
| 2026-11 | 5,584 | 100% |
Evidence
- Claude Code: author email [email protected] (2e2d40c88dc8)
- Claude Code: author email [email protected] (af86092a9b77)
- Claude Code: author email [email protected] (15d4bb3c7e32)
- Claude Code: author email [email protected] (c9acd43fb1c6)
- Claude Code: author email [email protected] (6b5b2cd4bef3)
- Claude Code: author email [email protected] (c5e31e2e4482)
- Claude Code: author email [email protected] (c5c7c565e2c5)
- Claude Code: author email [email protected] (a9aabe8d6798)
- Claude Code: author email [email protected] (796e5554aa4f)
- Claude Code: author email [email protected] (8dd0bcb157c0)
- Claude Code: author email [email protected] (b9956df8f8ea)
- Claude Code: author email [email protected] (dd2d55d81818)
- Claude Code: author email [email protected] (b5edaebefdc5)
- Claude Code: author email [email protected] (7ec3c39e9a0f)
- Claude Code: author email [email protected] (5b54689e4c97)
AI provenance describes how code was produced; it is not a quality judgment. Unless attribution is explicit, these are signals consistent with AI generation, not proof. Squash/rebase workflows, imported code, and rewritten history reduce accuracy.
Code quality
Code quality is adequate: test-to-source ratio 1.21, CI runs tests; 8% of function code in complex or long functions; 0% duplicated lines. Weakest area: type safety.
| Area | Score |
|---|---|
| Complexity (lizard) | 79 |
| Duplication | 98 |
| Code smells (Opengrep) | 53 |
| Tests and CI | 90 |
| Documentation | 65 |
| Type safety | 40 |
| Process (Scorecard review/maintenance) | n/a |
- Functions: 312; mean complexity 3.7, 90th percentile 8; 4 complex and 1 long functions
- Duplicated lines: 0.3% of 6,466 compared
- Tests: 10,063 test lines for 8,331 source lines (ratio 1.21); CI test commands: pytest; 84% of recent source commits also change tests
- Docs missing or thin: contributing, changelog
Most complex functions:
- stage_encode in src/grow_up/pipeline.py: complexity 33, 86 lines
- write_rejects_gallery in src/grow_up/review.py: complexity 28, 103 lines
- render in src/grow_up/morph.py: complexity 18, 43 lines
- stage_align in src/grow_up/pipeline.py: complexity 16, 59 lines
Security
Security posture is adequate: 9 high-severity SAST findings; 2 high-severity workflow issues. Weakest area: posture.
| Area | Score |
|---|---|
| Secrets (gitleaks, tree + history) | 100 |
| Static analysis (Opengrep) | 72 |
| Vulnerable dependencies (OSV) | n/a |
| CI workflows (zizmor) | 67 |
| Posture (policy, updates, signing, lockfiles) | 20 |
| OpenSSF Scorecard | n/a |
- Posture checks passed: signed commits, lockfiles; missing: security policy, dependency updates
Top findings
| Severity | Finding | Location |
|---|---|---|
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query: Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition [confidence low] |
src/grow_up/cli.py:755 |
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query: Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition [confidence low] |
src/grow_up/db.py:203 |
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query: Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition [confidence low] |
src/grow_up/db.py:206 |
| high | opengrep/python.lang.security.audit.dangerous-subprocess-use-audit: Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'. [confidence low] |
src/grow_up/encode.py:371 |
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query: Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition [confidence low] |
src/grow_up/pipeline.py:249 |
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query: Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition [confidence low] |
src/grow_up/pipeline.py:315 |
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query: Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition [confidence low] |
src/grow_up/pipeline.py:425 |
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query: Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition [confidence low] |
src/grow_up/pipeline.py:488 |
| high | opengrep/python.sqlalchemy.security.sqlalchemy-execute-raw-query: Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition [confidence low] |
src/grow_up/pipeline.py:551 |
| high | zizmor/unpinned-uses: unpinned action reference [confidence high] |
.github/workflows/tests.yml:25 |
| high | zizmor/unpinned-uses: unpinned action reference [confidence high] |
.github/workflows/tests.yml:27 |
| medium | opengrep/python.lang.security.audit.dynamic-urllib-use-detected: Detected a dynamic value being used with urllib. urllib supports 'file://' schemes, so a dynamic value controlled by a malicious actor may allow them to read arbitrary files. Audit uses of urllib calls to ensure user data cannot control the URLs, or consider using the 'requests' library instead. [confidence low] |
src/grow_up/cli.py:188 |
| medium | opengrep/python.lang.security.audit.formatted-sql-query: Detected possible formatted SQL query. Use parameterized queries instead. [confidence low] |
src/grow_up/cli.py:755 |
| medium | opengrep/python.lang.security.audit.formatted-sql-query: Detected possible formatted SQL query. Use parameterized queries instead. [confidence low] |
src/grow_up/db.py:203 |
| medium | opengrep/python.lang.security.audit.formatted-sql-query: Detected possible formatted SQL query. Use parameterized queries instead. [confidence low] |
src/grow_up/db.py:206 |
| low | zizmor/artipacked: credential persistence through GitHub Actions artifacts [confidence low] |
.github/workflows/tests.yml:25 |
Static signals only: the scorer never runs the project's code. Secret findings are pattern matches that were not verified, and secret values are never stored.
Distribution signals
- readme-download-lure: gives an archive password
Signals consistent with a repository that exists to distribute a download. They are heuristics, not a verdict; release files were not downloaded or inspected.
Repository profile
- Source lines: 8,331; test lines: 10,063
| Language | Lines |
|---|---|
| Python | 18,359 |
| Shell | 35 |