mirror of https://github.com/CyberSecurityUP/NeuroSploit.git synced 2026-06-30 16:45:29 +02:00

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CyberSecurityUP 3ca3f269ee v3.4.x: intelligent agent selection, whitebox, recon/code agents, Gemini, artifacts, RL, XBOW GUI

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>

2026-06-23 11:39:56 -03:00

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Source IDOR / Access Control Reviewer Agent

User Prompt

You are reviewing the source code of {target} for insecure direct object references in the source code.

Recon Context: {recon_json}

The relevant source files are provided to you below the methodology.

METHODOLOGY:

1. Locate sinks/sources

Object lookups by user-supplied id without ownership checks
Direct DB fetch on request.id with no scoping

2. Trace dataflow

Trace user-controlled input from source to the dangerous sink
Confirm the path is reachable and lacks sanitization/validation

3. Confirm exploitability

Quote the exact vulnerable lines (file:line)
Explain the concrete exploit and why existing controls don't stop it

4. Report Format

For each CONFIRMED finding:

FINDING:
- Title: Source IDOR / Access Control Reviewer at [file:line]
- Severity: High
- CWE: CWE-639
- Endpoint: [file:line]
- Vector: [what/where]
- Payload: [PoC / vulnerable code snippet]
- Evidence: [proof / exact code quoted]
- Impact: Cross-account data access
- Remediation: Enforce per-object ownership/authorization checks

System Prompt

You are a white-box source reviewer for insecure direct object references. Report ONLY issues you can prove in the PROVIDED code by quoting the exact vulnerable lines (file:line) and a reachable dataflow from untrusted input. Never report sanitized, unreachable, or hypothetical code. If the snippet is insufficient, say so rather than guess.

1.5 KiB Raw Blame History