- New agent account_registration_and_forms (+1 → 430): analyzes the app's forms
and self-registers a benign test account (curl or Playwright) to reach the
authenticated surface when no creds are given.
- Probe extracts form details (action/method/fields/kind/CSRF) so form analysis is
grounded; shown in the probe summary and recon JSON.
- Hard anti-flood guardrail in SAFETY_DOCTRINE + the agent: at most 2 accounts per
engagement, never loop/script/batch the register endpoint or flood the DB; reuse
the account made; a test needing many sign-ups is a lead, not mass-creation.
- Credential vault: engagement_ops directive tells agents to append created
accounts to <run-dir>/vault.jsonl; finish() consolidates to vault.json, masks
secrets in the report, and adds a 'Test accounts created (DELETE after)' cleanup
finding listing each account and how it was created.
- Finding tagging: new auth_context (authenticated/unauthenticated) and account
fields, rendered per-finding in the HTML report.
- Opt-in disposable email (off by default): /tempmail on + RunConfig.temp_email;
agents may use the free mail.tm API to read a registration confirmation code.
- Tests: parse_forms unit tests; docs updated (README/TUTORIAL/RELEASE), counts 430.
- Add 12 technique/scenario LLM red-team agents (AI category 18 → 30, total 429):
jailbreaks — AdvPrefix, PAIR, TAP, Crescendo, many-shot, persona/DAN,
encoding/obfuscation, refusal-suppression; prompt-injection scenarios — direct,
indirect (RAG/web/email/tool output), goal hijacking, tool/function-call abuse,
system-prompt/secret exfiltration. Each runs an attacker→LLM-judge loop
(baseline refusal → technique across variants → verdict), proving the bypass
with a benign, redacted receipt. Generated by scripts/build_llm_redteam_v365.py.
- Add REDTEAM_DOCTRINE and inject it into run_ai so every AI test follows the
baseline→technique→judge method across scenarios.
- Models: add Claude Opus 5 and Sonnet 5 (Anthropic) and a new Moonshot AI (Kimi)
provider with Kimi K3/K2 (moonshot:kimi-k3, MOONSHOT_API_KEY) — 15 providers.
- Docs: README/TUTORIAL/RELEASE — new AI/LLM red-team engagement mode + section,
model/env-key tables, agent-library counts (429), badges.
Also includes the v3.6.4 grounding fix (#33) landing on main.
- DECISION_DOCTRINE injected into exploit/grey/chain prompts: analyse responses to
pick the technique; map & connect routes (endpoint output → next endpoint input);
hunt sensitive flows; mine parameters (incl. hidden from JS/source maps) and test
per-param; mock realistic (non-PII) data to reach deeper logic; exploit the
authenticated surface after login and compare roles; build PoCs when a proof
needs an artifact; bypass 401/403/redirect controls.
- REPL /auth now supports multiple named identities (/auth admin <hdr>, /auth user
<hdr>; bare token → Bearer). With >=2 roles the run gets the access-control
directive (IDOR/BOLA/BFLA/privesc, authorized-vs-unauthorized) and tests both.
- +6 decision agents (library 389): param_miner, endpoint_flow_linker,
authenticated_surface_exploit, clickjacking_poc (HTML PoC), csrf_poc (HTML PoC),
access_control_bypass.
- Docs: counts 383->389, RELEASE + /auth help updated.
- tool_doctrine: agents now actively DRIVE the browser on JS/SPA targets — use
the Playwright MCP (render, read live DOM, click client-side routes, watch the
network to find the real API, screenshot proof); when no MCP, use the Playwright
CLI (write+run a small script / npx playwright screenshot) to render and capture
XHR/fetch traffic — complementing curl (which only sees the empty shell).
- probe: detect SPAs (<app-root>, ng-version, near-empty body + linked scripts →
Angular/React/Vue/SPA) and note in recon that the browser is required, so the
SPA agents get selected.
- +8 SPA/API agents (library 383): spa_api_discovery, spa_hidden_admin,
login_sqli_bypass, dom_xss_spa, api_bola_numeric_ids,
register_privilege_mass_assign, jwt_forgery_spa, spa_business_logic.
- Docs: README/RELEASE/TUTORIAL counts + notes.
Distilled from reviewing real AI-pentest output that kept stopping at "exposed"
instead of "exploited". Pure-additive, back-compatible.
Behavior (injected into black/grey/chain exploit prompts via DEPTH_DOCTRINE):
- Exposed → exploited: any info-disclosure / exposed service/WSDL / leaked
credential|token / reachable dev host MUST be used before it's a finding;
otherwise it's a lead, not a confirmed High/Critical.
- Chain across modules: reuse obtained session/JWT/cookie/credential and pivot
to IDOR/privesc/exfil; report the chain, not isolated parts.
- Decode & fingerprint → CVE; audit tokens (alg-confusion/none/kid/JWKS, weak
HS256 secret cracking, lifecycle).
Deterministic post-pass (new crates/harness/src/hygiene.rs, wired into finish()):
- calibrate severity to PROVEN impact — unproven High/Critical (hedged, no
payload, thin evidence) capped to Medium and re-titled "(potential)";
- depth_audit — flag exposures on a host with no real exploit;
- hygiene_summary — advise consolidating hygiene classes repeated across assets.
Unit tests cover calibration + depth audit.
5 new doctrine meta-agents (scripts/build_methodology_v352.py → agents_md/meta/):
exploit_depth_doctrine, finding_chainer, artifact_decoder, token_auditor,
report_calibrator (meta 17→22, total 343→348).
Version bumped 3.5.1 → 3.5.2 across crates/app/installers/docs; RELEASE/README
updated.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Chaining:
- agents_md/chains/ (12 multi-stage exploitation playbooks): SQLi→RCE→LPE,
SSRF→AWS-creds, SSRF→RCE, upload→RCE, upload→LFI→RCE→LPE, XSS→ATO, IDOR→ATO,
SSTI→RCE→cloud, default-creds→domain, deserialization→RCE, exposed-git→RCE,
subdomain-takeover→trusted-abuse. Each stage proven by a tool receipt before
advancing; reports chains_from edges.
- Loaded as a `chains` category (→ 329 agents). chain_round now injects the chain
recipes as a menu so the LLM applies proven multi-stage paths.
Persistence (no DB — structured state):
- Per-project `<cwd>/.neurosploit/` holding session.json (config), runs.json
(history), history.txt (readline). REPL resumes target/repo/auth/focus/models
on reopen; saves on /run and /quit.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- Task-based model ROUTER (recon/select prefer a fast model; exploit prefers primary; validate uses a different model than the finder)
- ReAct doctrine injected into exploit prompts (Thought→Action→Observation, token-efficient)
- Dedup: unique agents per run + findings deduped by CWE/endpoint/title (highest confidence kept)
- Token economy: recon blob capped for selector + per-agent context
- Configurable MCP: merge user mcp.servers.json into the pipeline's .mcp.json
- +54 white-box/code-analysis agents (NoSQLi, LDAP/XPath, JWT-none, Java/.NET/PHP/Go/Node/Python
specifics, SSTI, ReDoS, deserialization, etc.) → 303 agents total (78 code)
- Credits: Joas A Santos & Red Team Leaders (CLI banner, interactive header, HTML+Typst report)
- README: GitHub stars/forks badges, 60-second quick start, full API config steps, intuitive layout
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
