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Jignesh160/icaur-chatbot-s3vec

https://github.com/Jignesh160/icaur-chatbot-s3vec · scanned 2026-06-16 04:29 UTC (2 months ago)

8 raw signals (0 security + 8 graph)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 months ago · v1 · 8 actionable findings from 1 signal source. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

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66.7% cov · 8 findings

Severity distribution — click a segment to filter

Active filters: excluding tests × Reset all

Severity: Critical 0 High 0 Medium 6 Low 2 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 8 Crowd 0 Layer: Security 3 Quality 5

Exclude dismissed / FP Exclude test files

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Scan summary Repository scanned at 79.5/100 with 66.7% coverage. It contains 33 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 8 findings — concentrated in quality (5), security (3). Risk profile is low: 0 critical, 0 high, 6 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 8 of 8 actionable findings. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

medium System graph quality Agent instructions conf 1.00 Agent authority lacks a verifier contract: CLAUDE.md

This agent instruction grants code or shell authority but does not state the verification gate that decides promotion. The recurring safe pattern is: LLM proposes; deterministic tests/build/security checks verify; only verified code promotes.

CLAUDE.md VerificationClaude instruction

medium System graph quality Agent instructions conf 1.00 Agent authority lacks a verifier contract: docker-compose.cloudwatch.yml

docker-compose.cloudwatch.yml VerificationCloud instruction

medium System graph quality Agent instructions conf 1.00 Agent instructions exist but release-hardening basics are missing

AI-coder instruction files were found, but the repo is missing license, ci. Treat this as a contract gap: the agent is guided, but the generated output is not yet guarded by the controls that make it repeatable.

Repo hardeningGenerated repo pattern

medium System graph security security conf 1.00 Insecure pattern 'direct_innerhtml_assignment' in chat.html:391

Found a known-risky pattern (direct_innerhtml_assignment). Review and replace if possible.

chat.html:391 Direct innerhtml assignment

medium System graph security security conf 1.00 Insecure pattern 'direct_innerhtml_assignment' in eval_dashboard.html:203

Found a known-risky pattern (direct_innerhtml_assignment). Review and replace if possible.

eval_dashboard.html:203 Direct innerhtml assignment

medium System graph security Coverage conf 1.00 No auth library detected

The scanner did not find any standard auth library (JWT, OAuth, NextAuth, Auth0, etc.). The repo has auth/admin/session surface indicators, so auth may live in custom code, in a separate service, or be missing.

auth

low System graph quality Production readiness conf 1.00 Composite production-readiness gap

Multiple low-cost hardening controls are missing together: license, ci. Opus verification showed these co-occurring gaps are a better readiness signal than reading each flag in isolation.

Repo hardeningGenerated repo pattern

low System graph quality License conf 1.00 No license file detected

No LICENSE/COPYING/NOTICE file was found. Generated repositories often omit licensing, which blocks reuse and automated intake.

Repo hardeningGenerated repo pattern

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