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ryankiros/neural-storyteller
A recurrent neural network for generating little stories about images
AI provenance
0%
none-detected
- Confidence
- 46%
- Coverage
- 100%
Estimated share of AI-generated code. Explicit attribution is a lower bound.
Code quality
36/100
poor
- Confidence
- 90%
- Coverage
- 100%
Complexity, duplication, lint density, tests, CI, docs and review process.
Security
60/100
weak
- Confidence
- 85%
- Coverage
- 100%
Secrets, static analysis, vulnerable dependencies, CI and supply-chain posture.
- Repository: https://github.com/ryankiros/neural-storyteller
- Commit:
61e12a7a0453bdc62013c7c07b7f7c331059d360 - Generated: 2026-11-13T23:23:12+00:00
- Scorer 0.1.0, scoring prov-4+qual-2+sec-2, report schema v2
Scores
| Pillar | Score | Signal | Confidence | Coverage |
|---|---|---|---|---|
| AI provenance (estimated AI-generated share) | 0 | none-detected | 46% | 100% |
| Code quality | 36 | poor | 90% | 100% |
| Security | 60 | weak | 85% | 100% |
AI provenance
No AI attribution or AI-consistent velocity signals detected.
-
Explicitly attributed share (lower bound): 0.0%
-
Unattributed share in AI-consistent velocity bursts: 0.0%
-
Estimated AI-generated share: 0.0%
-
Stylometry index: 0.71 per 1,000 lines (narrated steps 1, placeholders 0, assistant phrasing 0, emoji 0). Reported as a signal, not scored.
| Month | Lines added | Attributed to AI |
|---|---|---|
| 2015-11 | 1,450 | 0% |
Evidence
- step-by-step narration comment: # first, do preprocessing (skipthoughts)
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 poor: test-to-source ratio 0.00, no CI test run detected; 15% of function code in complex or long functions; 38% duplicated lines. Weakest area: testing.
| Area | Score |
|---|---|
| Complexity (lizard) | 63 |
| Duplication | 10 |
| Code smells (Opengrep) | 84 |
| Tests and CI | 0 |
| Documentation | 40 |
| Type safety | 40 |
| Process (Scorecard review/maintenance) | n/a |
- Functions: 64; mean complexity 2.7, 90th percentile 5; 2 complex and 0 long functions
- Duplicated lines: 38.4% of 991 compared
- Tests: 0 test lines for 1,407 source lines (ratio 0.00); CI test commands: none detected; 0% of recent source commits also change tests
- Docs missing or thin: license, contributing, changelog
Most complex functions:
Security
Security posture is weak: no high-impact findings. Weakest area: posture.
| Area | Score |
|---|---|
| Secrets (gitleaks, tree + history) | 100 |
| Static analysis (Opengrep) | 39 |
| Vulnerable dependencies (OSV) | n/a |
| CI workflows (zizmor) | n/a |
| Posture (policy, updates, signing, lockfiles) | 0 |
| OpenSSF Scorecard | n/a |
- Posture checks passed: lockfiles; missing: security policy, dependency updates, signed commits
Top findings
| Severity | Finding | Location |
|---|---|---|
| medium | opengrep/python.lang.security.deserialization.avoid-cPickle: Avoid using cPickle, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format. [confidence low] |
decoder.py:21 |
| medium | opengrep/python.lang.security.deserialization.avoid-cPickle: Avoid using cPickle, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format. [confidence low] |
decoder.py:32 |
| medium | opengrep/python.lang.security.audit.eval-detected: Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources. [confidence low] |
decoder.py:115 |
| medium | opengrep/python.lang.security.audit.eval-detected: Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources. [confidence low] |
decoder.py:115 |
| medium | opengrep/python.lang.security.audit.eval-detected: Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources. [confidence low] |
decoder.py:234 |
| medium | opengrep/python.lang.security.deserialization.avoid-cPickle: Avoid using cPickle, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format. [confidence low] |
embedding.py:22 |
| medium | opengrep/python.lang.security.deserialization.avoid-cPickle: Avoid using cPickle, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format. [confidence low] |
embedding.py:33 |
| medium | opengrep/python.lang.security.audit.eval-detected: Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources. [confidence low] |
embedding.py:137 |
| medium | opengrep/python.lang.security.audit.eval-detected: Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources. [confidence low] |
embedding.py:137 |
| medium | opengrep/python.lang.security.audit.eval-detected: Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources. [confidence low] |
embedding.py:270 |
| medium | opengrep/python.lang.security.deserialization.avoid-cPickle: Avoid using cPickle, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format. [confidence low] |
generate.py:220 |
| medium | opengrep/python.lang.security.deserialization.avoid-cPickle: Avoid using cPickle, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format. [confidence low] |
skipthoughts.py:30 |
| medium | opengrep/python.lang.security.deserialization.avoid-cPickle: Avoid using cPickle, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format. [confidence low] |
skipthoughts.py:32 |
| medium | opengrep/python.lang.security.audit.eval-detected: Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources. [confidence low] |
skipthoughts.py:187 |
| medium | opengrep/python.lang.security.audit.eval-detected: Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources. [confidence low] |
skipthoughts.py:187 |
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.
Repository profile
- Source lines: 1,407; test lines: 0
| Language | Lines |
|---|---|
| Python | 1,407 |