RepoTrust

amontlabs/lcu

Codex computer use, decoupled from the app, for usage inside any harness.

https://github.com/amontlabs/lcu · commit c8e5693d7141 · scored 2026-11-14 · scoring prov-4+qual-2+sec-2

unusual-traction

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Scores

Unusual traction: many stars in a few days on a newly created account, which is consistent with purchased or automated stars. Star count is not a reliable signal for this repository.

Pillar Score Signal Confidence Coverage
AI provenance (estimated AI-generated share) 32 explicit 95% 100%
Code quality 73 adequate 90% 100%
Security 59 weak 85% 100%

AI provenance

Explicit AI attribution on 33% of first-party code added; an estimated 33% including velocity signals.

AI tool Attributed commits Lines added
Claude Code 69 27,909

Current source lines last changed by AI-attributed commits: 11,592 of 20,200.

Findings per 1,000 lines AI-attributed Other Ratio
Quality 3.106 3.717 0.84x
Security 0.69 2.091 0.33x
Month Lines added Attributed to AI
2026-09 31,923 4%
2026-10 53,217 50%
2026-11 608 24%

Evidence

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 1.70, CI runs tests; 24% of function code in complex or long functions; 1% duplicated lines. Weakest area: type safety.

Area Score
Complexity (lizard) 49
Duplication 95
Code smells (Opengrep) 66
Tests and CI 100
Documentation 65
Type safety 0
Process (Scorecard review/maintenance) n/a

Most complex functions:

Security

Security posture is weak: 23 known vulnerabilities in 8 dependencies; 8 high-severity SAST findings; 20 high-severity workflow issues. Weakest area: ci actions.

Area Score
Secrets (gitleaks, tree + history) 94
Static analysis (Opengrep) 83
Vulnerable dependencies (OSV) 52
CI workflows (zizmor) 2
Posture (policy, updates, signing, lockfiles) 20
OpenSSF Scorecard n/a

Top findings

Severity Finding Location
high opengrep/python.lang.security.audit.dangerous-subprocess-use-audit: Detected subprocess function 'Popen' 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] adapters/hermes/init.py:76
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] scripts/build_bundle.py:100
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] scripts/build_bundle.py:172
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] scripts/check_windows_host_layout.py:63
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] scripts/check_windows_host_layout.py:81
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] scripts/provision_agent_tools.py:81
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] scripts/provision_agent_tools.py:91
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] scripts/provision_agent_tools.py:109
high osv/GHSA-22jm-h49p-29qw: @modelcontextprotocol/[email protected] (npm) is affected by GHSA-22jm-h49p-29qw adapters/package-lock.json
high osv/GHSA-46jr-4wx8-v453: @modelcontextprotocol/[email protected] (npm) is affected by GHSA-46jr-4wx8-v453 adapters/package-lock.json
high osv/GHSA-6qxp-vccf-f47h: @modelcontextprotocol/[email protected] (npm) is affected by GHSA-6qxp-vccf-f47h adapters/package-lock.json
high osv/GHSA-f897-62hf-6gxq: @modelcontextprotocol/[email protected] (npm) is affected by GHSA-f897-62hf-6gxq adapters/package-lock.json
high osv/GHSA-27r3-jxmh-p828: [email protected] (npm) is affected by GHSA-27r3-jxmh-p828 adapters/package-lock.json
high osv/GHSA-mrhx-c7xc-m3w5: [email protected] (npm) is affected by GHSA-mrhx-c7xc-m3w5 adapters/package-lock.json
high zizmor/unpinned-uses: unpinned action reference [confidence high] .github/workflows/ci.yml:29
high zizmor/unpinned-uses: unpinned action reference [confidence high] .github/workflows/ci.yml:30
high zizmor/unpinned-uses: unpinned action reference [confidence high] .github/workflows/ci.yml:47
high zizmor/unpinned-uses: unpinned action reference [confidence high] .github/workflows/ci.yml:48
high zizmor/unpinned-uses: unpinned action reference [confidence high] .github/workflows/ci.yml:51
high zizmor/unpinned-uses: unpinned action reference [confidence high] .github/workflows/ci.yml:63
high zizmor/unpinned-uses: unpinned action reference [confidence high] .github/workflows/ci.yml:64
high zizmor/unpinned-uses: unpinned action reference [confidence high] .github/workflows/ci.yml:67
high zizmor/unpinned-uses: unpinned action reference [confidence high] .github/workflows/ci.yml:85
high zizmor/unpinned-uses: unpinned action reference [confidence high] .github/workflows/ci.yml:88
high zizmor/unpinned-uses: unpinned action reference [confidence high] .github/workflows/ci.yml:91

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

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

Language Lines
JavaScript 37,276
Python 13,739
TypeScript 2,419
Shell 995
Swift 103
PowerShell 61

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