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CyberSecurityUP
3ca3f269ee
Harness intelligence: - After recon, the model SELECTS which specialist agents match the target (select_agents) — runs the relevant subset, not blindly top-N - RL reward store (rl.rs): per-agent weights persist to data/rl_state_rs.json, reward validated findings (severity-weighted), decay idle, bias next run - Run artifacts persisted as JSON + MD (recon, exploitation transcript, findings, html report) under runs/<target>-<ts>/ for reuse by other AIs Whitebox mode: - run_whitebox: walks a repo, builds bounded source context, runs code agents, validates by adversarial vote. CLI `whitebox <path>` + web "White-box" mode Agents: +12 recon (subdomain/tech/js/api/secrets/dns/content/param/waf/cloud/ graphql/osint) and +24 code SAST reviewers (sqli/cmdi/path/ssrf/xss/deser/ secrets/crypto/authz/idor/xxe/redirect/ssti/race/eval/csrf/random/logging/ upload/mass-assign/jwt/cors). Loader gains recon/ + code/ categories → 249 total Models: +Google Gemini provider (API + gemini CLI subscription); installed_cli_ backends now detects gemini; chat_cli handles gemini/codex/grok + optional Playwright MCP (.mcp.json) on the subscription path with autonomy flags GUI: full XBOW-style redesign — sidebar (Operate/Library), topbar status, mode segment (black-box/white-box), model panel, live console, severity cards, agent browser with category filters, models view; responsive + aligned Verified: cargo build --release clean; CLI agents/whitebox; LIVE subscription run shows model selecting 23→4 agents, RL update, artifacts written; GUI + white-box toggle in Playwright. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
25 lines
2.1 KiB
Plaintext
25 lines
2.1 KiB
Plaintext
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