antirez/neural-redis
Neural networks module for Redis
- Repository: https://github.com/antirez/neural-redis
- Commit:
fef3d1be51df90ae249c1a8a32bbc87ead4bfe1d - Generated: 2026-11-13T23:31:49+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 | 62% | 100% |
| Code quality | 55 | weak | 90% | 100% |
| Security | 74 | adequate | 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%
| Month | Lines added | Attributed to AI |
|---|---|---|
| 2016-09 | 2,806 | 0% |
| 2016-10 | 1,195 | 0% |
| 2016-12 | 41 | 0% |
| 2018-06 | 133 | 0% |
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 weak: test-to-source ratio 0.05, no CI test run detected; 32% of function code in complex or long functions; 3% duplicated lines. Weakest area: testing.
| Area | Score |
|---|---|
| Complexity (lizard) | 38 |
| Duplication | 81 |
| Code smells (Opengrep) | 100 |
| Tests and CI | 23 |
| Documentation | 65 |
| Type safety | n/a |
| Process (Scorecard review/maintenance) | n/a |
- Functions: 82; mean complexity 5.2, 90th percentile 12; 6 complex and 2 long functions
- Duplicated lines: 3.5% of 2,553 compared
- Tests: 161 test lines for 3,282 source lines (ratio 0.05); CI test commands: none detected; 1% of recent source commits also change tests
- Docs missing or thin: contributing, changelog
Most complex functions:
- NRTrainingThreadMain in neuralredis.c: complexity 54, 151 lines
- AnnPrint in nn.c: complexity 22, 71 lines
- NRCreate_RedisCommand in neuralredis.c: complexity 19, 78 lines
- AnnInitLayer in nn.c: complexity 17, 46 lines
- NRObserve_RedisCommand in neuralredis.c: complexity 16, 69 lines
Security
Security posture is adequate: no high-impact findings. Weakest area: posture.
| Area | Score |
|---|---|
| Secrets (gitleaks, tree + history) | 100 |
| Static analysis (Opengrep) | 79 |
| 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/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] |
neuralredis.c:871 |
| medium | opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] |
nn.c:229 |
| medium | opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] |
nn.c:230 |
| medium | opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] |
nn.c:232 |
| medium | opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] |
nn.c:234 |
| medium | opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] |
nn.c:236 |
| medium | opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] |
nn.c:238 |
| medium | opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] |
nn.c:240 |
| medium | opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] |
nn.c:700 |
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: 3,282; test lines: 161
| Language | Lines |
|---|---|
| C | 2,920 |
| Ruby | 523 |