New `mobile` engagement mode: `neurosploit mobile <app.apk|app.ipa|binary>`
reverse-engineers a local artifact with a dedicated `mobile` agent set, all
headless and provisioned on demand (Ghidra analyzeHeadless, MobSF REST/Docker,
Frida, apktool/jadx, radare2).
Twelve original, generic skills (agents_md/mobile/, English): static binary
triage, APK static analysis, IPA static analysis, RASP & anti-tamper mapping,
root/jailbreak detection + bypass, TLS pinning detection + bypass, anti-debug
detection + bypass, obfuscation analysis & deobfuscation, code-integrity /
tamper-check bypass, hardcoded-secrets extraction, insecure local storage, and
mobile network traffic analysis. Findings are proven from the artifact
(decompilation or Frida trace), non-destructively.
- agents.rs: new `mobile` Library category (loaded, counted).
- pipeline.rs: run_mobile() mirroring the host pipeline with a mobile recon and
headless tooling doctrine; exported from the crate.
- CLI: `Cmd::Mobile` + `Mode::Mobile`, wired in main and the TUI.
- README + TUTORIAL document the new test type; engagement-modes badge + table
updated; "New in v4.2.0" note. Version bumped to 4.2.0 across the workspace.
383 tests.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Version bumped to 4.1.0 across the workspace, binaries, web console and Typst
template.
README: new "New in v4.1.0" summary; trimmed the verbose highlight bullets and
the TypeSafe section; removed the anti-plagiarism/provenance section (provenance
stays in the code, just not front-and-centre in the README); TypeSafe promoted
to its own top-level section; agent count 446.
TUTORIAL: new section 17 "Assurance & authorization" covering the target gate,
--scope-file, evidence-graded CVSS, audit anchoring + assurance bundle, sandbox,
intercept proxy, PoC re-validation, compliance mapping, TypeSafe, and the
internal/AD graph + budget governor.
benchmarks/typesafe-2026-09-20/: the with/without TypeSafe measurement —
report.html, scorer, both runs' findings/assurance/meta/logs, and a README.
No secrets committed (env-only during the runs, verified clean).
381 tests.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Four pieces that together answer "may this action happen, under whose
authority, and can we prove afterwards what we did".
policy.rs — effective_risk per action, exactly as specified:
(action_risk + asset_criticality + protocol_risk + privilege_level
+ blast_radius) × environment_multiplier
Every term is named and kept on the result, so the number can be explained
rather than argued with. Three policies sit on it: SafetyPolicy (ceilings,
approval thresholds, hard prohibitions), ReasoningPolicy (baseline before
payload, bounded hypotheses, evidence before escalation, explicit stop
conditions) and ProofOfImpactPolicy (what a severity must carry before it may
be that severity).
OT/ICS/SCADA is treated as its own regime, not web testing on odd ports.
Industrial protocols authenticate nothing — a Modbus write is the protocol
working as intended, addressed to a device that may be holding a valve — and
scanners crash PLCs by sending unexpected data at line rate. So the OT profile
blocks writes, disruptive actions, fuzzing and exploit payloads outright, caps
the rate at ~1 req/s, and refuses the function codes that stop a CPU (Modbus
5/6/8/15/16/22/23/43, S7 start/stop, DNP3 restart/stop). Safety instrumented
systems are off limits in every profile.
A test caught a calibration error worth keeping: a plain READ of a critical PLC
scores 3.6 on this formula, so the obvious tight ceiling would have refused
exactly the observation OT findings come from. In an industrial environment it
is the KIND of action that is forbidden, not the arithmetic — the ceiling
catches extremes and the low approval threshold makes anything past trivial
observation a human's decision.
capability.rs — HMAC-signed grants: who authorized what, against which hosts,
in which environment, until when. The harness verifies the signature before
reading a single claim (a well-formed token from the wrong key must never get
to influence what the harness believes), refuses expired and not-yet-valid
tokens, and treats the grant as a CEILING: constrain() intersects it with local
configuration, so config can narrow authorization and never widen it. Tokens
carry no secrets — the payload is readable by anyone holding it.
audit.rs — one structured record per action, in the specified shape (timestamp,
agent, hypothesis, action, target, policy_decision, operator, tool, result,
evidence_hash, capability_token). Two things make it worth having: it is
hash-chained, so removing or editing an entry breaks every hash that follows
and verify() says which one; and it records REFUSALS, because a trail
containing only what happened cannot demonstrate restraint. Only the grant's
id is recorded, never the token — the trail gets shared.
Hard kill conditions end a run outright: target unresponsive after our traffic,
sustained 5xx, out-of-scope request, forbidden industrial function code, safety
system addressed, capability expired mid-run, repeated policy violations,
budget exhausted, operator stop. Failures BEFORE the target ever answered do
not count — nothing listening is not the same as knocked over. The OT switch
trips far sooner: a PLC missing two requests already warrants stopping.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
New web/ app (zero npm deps, Node http built-ins only):
- server.js reads agents_md/ to build a categorized lead board (435 agents
auto-classified into Business Logic / Broken Access Control / Injection /
LLM Application / Auth & Session / SSRF / API / Cloud & Infra / etc.),
reads runs/ for history, and spawns the compiled neurosploit CLI binary
for every exploitation job — structured findings/phase/progress are parsed
from its stdout (finding_json:/phase lines), same signal the TUI uses.
- REPL drawer spawns `neurosploit` with no subcommand (real interactive
session, Reader::Plain over the piped stdin) and streams stdin/stdout —
every /command works exactly as in a terminal, nothing reimplemented.
- SSE endpoints for both job and REPL streams; run/finding/report assets
served under /api/runs/:id/asset/*.
- public/{index,app.js,style.css}: lead board with category toggles + custom
leads + Start Exploitation, live run view (progress/findings/log), run
detail view, REPL drawer — screenshot-inspired layout.
- web/API.md: full endpoint reference. web/README.md: quick start.
Bump version 3.6.9 -> 4.0.0 (Cargo.toml, CLI banners, README/TUTORIAL).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0129WdYHccPsH27k5GGuwijd
Add two new model providers, both usable via API key or --subscription
(local CLI login, no key):
- opencode: OpenCode Zen gateway (OPENCODE_API_KEY, opencode.ai/zen/v1).
Subscription mode drives the `opencode` CLI (`opencode run --auto`).
Supports the Playwright MCP (--mcp): our .mcp.json is converted to
OpenCode's own config schema and injected via OPENCODE_CONFIG.
- nous: Nous Research / Hermes models (NOUS_API_KEY,
inference-api.nousresearch.com/v1). Subscription mode drives the
`hermes` CLI (NousResearch/hermes-agent) on the user's Nous Portal
OAuth login (`hermes setup --portal`), via `hermes chat -q`. No
CLI-level MCP hook — falls back to Hermes's own built-in toolsets
(web/terminal/computer-use).
Both wired into cli_binary_for, installed_cli_backends, cli_login_status
(prompt passed as argv, not stdin — neither CLI reads stdin for this).
Bump version 3.6.8 -> 3.6.9 across Cargo.toml, README, TUTORIAL, setup.sh,
install.ps1, and in-binary version strings. README/.env.example updated
with the new provider rows and subscription-login table.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HHFAVCHMvRkTy9Wgw7SayG
- models.rs: detect connection-refused and timeout on local providers
(ollama/litellm/llamacpp), show actionable error instead of raw reqwest
- pipeline.rs: findings with empty evidence skip adversarial vote (which
always rejects per 'default to rejected' prompt) and go straight to
needs-review for human triage
- pipeline.rs: warn when single-model panel + vote_n=1 (same model
validates its own findings = weaker validation)
- Bump version 3.6.7 → 3.6.8
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011739wMqPJJPttTLLX6YoQH
Version bump 3.6.5 -> 3.6.6.
Local & uncensored models
- New `llamacpp:` provider (llama-server, OpenAI-compatible, localhost:8080,
no API key, CPU-only or GPU-offloaded). Override via LLAMACPP_BASE_URL;
model name is the loaded gguf (pass-through). 15 -> 16 providers.
- README: local/uncensored highlight, provider table + key-less note, badges.
Quality
- clippy clean under `-D warnings`: clamp(), sort_by_key(Reverse), struct-literal
init, too_many_arguments allows, scoped await_holding_lock on the REPL blocking
fallback (guard intentionally held across run().await), plus clippy --fix set.
CI
- examples/github-actions/ci.yml: cargo build/test/clippy -D warnings for the
neurosploit-rs workspace (template, kept out of .github/workflows).
Claude-Session: https://claude.ai/code/session_01QDses7zTSa9YF7pPRjphvh
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
- 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.
The grounding gate ran in empirical mode for every engagement, demoting
white-box (and skills/n8n audit) findings that had passed the n-model vote
because a file:line code citation isn't raw tool output. Grounding is now
mode-aware:
- Symbolic (white-box SAST / skills): a file:line reference into the reviewed
source, or a quote of code present in it, is the receipt — no live target.
- Empirical (black-box / host / AI): evidence must resemble tool output (as before).
- Either (grey-box): a source citation OR a tool receipt grounds a finding.
The symbolic check runs against the reviewed source corpus (not the transcript)
and falls back to a structural file:line + quote check when the corpus is
unavailable. Adds unit tests incl. a regression test for #33.
- /continue (and /resume) now relaunch a recovered interrupted run on the same
target, carrying its findings forward and steering agents to widen coverage /
chain from them instead of re-reporting. Offer shown at launch; a fresh /run
supersedes it. Findings merge (dedup by title+endpoint) across both runs.
- Opening /results, /finding or /report while a run streams no longer corrupts
the terminal: live background output is paused for the picker (still captured
in /logs) and restored on exit, so Ctrl-C in a picker can't take the process
down mid-run.
- Drive `codex exec --json` and parse its JSONL event stream into the same
categorized live feed as Claude Code (exec/edit/tool/net/tokens), so recon and
exploitation are visible as each command runs instead of a silent black box.
- Fix the activity feed to keep per-agent tool events (commands, network, files,
findings) and only filter model reasoning + token telemetry, so /logs shows the
real command trail and /status 'last:' is a true sign-of-life.
- Surface failed internal commands as 'exec: (exit N)'; keep Codex auth/rate
detection from stderr.
Added the OpenAI GPT-5.6 line to the provider pool: gpt-5.6-sol (frontier/default),
gpt-5.6-terra (balanced), gpt-5.6-luna (fast/affordable). Version 3.6.0 -> 3.6.1.
New harness module `integrations` (+ app commands) wiring NeuroSploit into the
SDLC. Config persists per-project to .neurosploit/integrations.json; secrets are
NEVER stored — only the env-var name is saved, values read from the environment.
GitHub:
- private-repo clone (token injected into the clone URL for whitebox/greybox/tui)
- `neurosploit pr <owner/repo> <n>`: clone the PR head (refs/pull/N/head),
white-box review, optional `--comment` (PR summary) and `--jira` (cards)
- `neurosploit watch <owner/repo> --branch --interval`: re-review on each new commit
GitLab:
- private-repo clone (oauth2 token) for whitebox/greybox (gitlab.com or self-hosted)
Jira:
- `--jira` on any engagement opens one card per finding (REST /issue, basic auth)
Control:
- `/integrations` (REPL): show · enable/disable · setup jira|gitlab|github
- `neurosploit integrations [show|enable|disable] [github|gitlab|jira]` (CLI)
Docs: README "Integrations" section + new TUTORIAL-INTEGRATION.md (per-tool setup,
scopes, recipes, troubleshooting). Version bumped 3.5.2 → 3.5.3.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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>
Partial observability is now first-class:
- belief.rs — property-graph world model; nodes (host/service/vuln/exploit/cred)
carry a probability, not a boolean. Bayesian observation updates; per-node
Shannon entropy; mean-uncertainty + recon-frontier. Black-box = diffuse priors
that sharpen with observation; white-box collapses toward deterministic (MDP).
- pomdp.rs — value_of_information(), decide() (recon vs exploit falls out of
belief entropy), and may_assert() — the mathematical anti-hallucination gate:
no exploitability claim while the belief is diffuse (high entropy) → observe first.
- grounding.rs — verification engine, hard rule "no claim without a tool receipt":
empirical grounding for black-box (raw HTTP/OOB/error markers), symbolic for
white-box (file:line into reviewed source). Ungrounded claims demoted + flagged
receipt_missing (feeds future reward shaping).
- pipeline.finish(): grounding gate before reporting + belief-uncertainty readout.
- bump 3.5.0 → 3.5.1; README documents the v3.5.1 belief/grounding architecture
and the infra/bandit/reward roadmap.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Harness:
- Exploit-chaining round: after validation, chain confirmed findings into deeper
impact (SSRF→metadata, SQLi→dump→reuse, IDOR→ATO, file-read→secrets→RCE),
validate the new findings, merge. Wired into black-box and greybox.
- Latest top models surfaced: claude-opus-4-8, gpt-5.1/gpt-5.1-codex, gemini-3-pro.
REPL:
- Real line editing via rustyline: ↑/↓ command-history recall, Ctrl-A/E/K, paste;
Ctrl-C cancels the line, Ctrl-D exits. Command history persists to
data/repl_history.txt. Graceful plain-stdin fallback when not a TTY.
- /model with no arg → arrow-key multi-select (dialoguer); with arg accepts any
provider:model names.
- /key is model-aware: lists the providers your selected models need (set/missing)
and prompts for the missing keys; /key <prov> <key> still works.
- Run history persists to data/repl_runs.json and reloads across sessions
(/runs lists past + current; /results /report /status by run number).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- New persistent interactive session (app/src/repl.rs), launched when run with no args:
banner, model selection, API-key config (/key) or subscription (/sub), then a live
session to set /target, /repo, /auth, and free-text /focus instructions (or just type
them) that STEER which agents run and how.
- Slash-commands: /model /providers /key /sub /target /repo /auth /focus /mcp /votes
/agents /show /run /quit (+ bare text = focus).
- RunConfig gains `instructions` and `auth`:
* instructions bias both LLM agent-selection and the heuristic (focus keywords →
injection/access-control/etc. agents get a strong boost)
* operator directives (focus + auth) injected into recon and exploit prompts so agents
test as an authenticated user and prioritise the requested vuln classes
- bump 3.4.1 → 3.5.0 (CLI, harness, reports, credits)
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
