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Refresh Gemini validation-engine model defaults (v2.7.1) - #3

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azmolhaque merged 1 commit into
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claude/new-session-thsmic
Jul 21, 2026
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Refresh Gemini validation-engine model defaults (v2.7.1)#3
azmolhaque merged 1 commit into
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claude/new-session-thsmic

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Summary

Refreshes the two-tier Gemini AI-validation engine to track Google's current lineup. Default model IDs only — no change to engine logic. Both tiers remain fully env-overridable, and the legacy single-model GEMINI_MODEL override is still honoured.

Tier Before After Why
Tier-1 pre-filter (high volume) gemini-3.1-flash-lite gemini-3.5-flash-lite fastest / most cost-effective 3.5-class model — ideal for cheap noise rejection
Tier-2 deep validation (real / critical) gemini-3.5-flash gemini-3.6-flash stronger coding/reasoning workhorse for confirming genuine high-severity exposures

Both new IDs were verified callable against a live API key (via the v1beta/models list) before selection.

Also included:

  • Security-focused Tier-2 option documented in .env.example: point GEMINI_TIER2_MODEL at the security-specialised gemini-3.5-flash-cyber model (tuned to reason about software vulnerabilities) once a key can call it — a strong fit for the deep secret-validation tier. Left as a commented opt-in rather than a default, since it is not yet GA on all keys and a hardcoded unavailable model would 404 every scan.
  • Docs kept in sync: README architecture diagram + CHANGELOG entry updated to the new IDs.
  • New .env.example tip: the one-liner to list the exact model IDs a given key can call, so operators pick valid overrides instead of guessing.
  • Version single-sourced bump 2.7.0 → 2.7.1 (pyproject.toml; report.py fallback + frontend strings follow).

Type of change

  • Bug fix
  • New secret pattern / detector
  • New feature
  • Docs / tooling

Checklist

  • ruff check backend/ passes
  • pytest passes (added/updated tests for the change) — 270 passed, no logic change so no new tests required
  • New detectors include severity, cwe, and remediation — n/a (no new detectors)
  • No real credentials, live targets, or exploitation code introduced
  • Scanner remains passive (no use of discovered credentials, no writes to targets)

🤖 Generated with Claude Code

https://claude.ai/code/session_01V6XK23ZKmYtCovRte9a73E


Generated by Claude Code

Track Google's current Gemini lineup for the two-tier AI validation engine —
default model IDs only, no change to engine logic (all stay env-overridable).

- Tier-1 pre-filter default → gemini-3.5-flash-lite (was gemini-3.1-flash-lite):
  fastest / most cost-effective 3.5-class model for the high-volume noise-rejection tier.
- Tier-2 deep-validation default → gemini-3.6-flash (was gemini-3.5-flash):
  stronger reasoning workhorse for confirming genuine high-severity exposures.
- Document the security-specialised 3.5 Flash Cyber model as a Tier-2 override
  in .env.example for security-focused deployments.

Version bumped to 2.7.1 (single-sourced from pyproject; report + frontend strings
updated). Suite stays green (270 passed), ruff clean.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01V6XK23ZKmYtCovRte9a73E
@azmolhaque
azmolhaque merged commit ffd83ae into main Jul 21, 2026
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2 participants