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Deluluscan

AI-augmented, evidence-first security auditor for authorized testing across web, API, application, container/Kubernetes, cloud, and LLM/AI-system targets.

PyPI License: AGPL v3 Python 3.11+ Tests Local AI

Deluluscan automates the mechanical phases of an assessment — discovery, fingerprinting, active/passive scanning, known-CVE checks, and evidence-based verification — and produces a triaged, reproducible report. It is built to augment a security engineer: it does the repeatable parts thoroughly with low false positives, verifies findings up to proof before asserting them, and can reason with a local, offline LLM so nothing leaves your host.

⚠️ Authorization & scope

Deluluscan enforces a scope gate: by default it only targets loopback / RFC1918 (private) hosts. Testing any other host requires explicitly asserting authorization (allow_remote in config, or --allow-remote on the domain tools). Only test systems you own or have written permission to assess. Unauthorized scanning is illegal in most jurisdictions (CFAA, Computer Misuse Act, …). Deluluscan confirms to proof but never weaponizes — no exfiltration, no persistence, no DoS.


Why Deluluscan

  • Evidence-first. Every finding is re-tested with a differential oracle before it's rated; a bare 200/400/500 is never treated as proof. Findings carry an honest verdict (confirmed / likely / conditional / inconclusive / false-positive), a reproducible CVSS v3.1 vector, and compliance mappings (PCI-DSS / SOC 2 / ISO 27001).
  • AI as a force multiplier, not a black box. The AI proposes; deterministic tools execute; the live verifier decides truth. It never overwrites a re-test result.
  • Runs on your terms. Pluggable AI backends — Anthropic, OpenAI, DeepSeek, Ollama (fully offline), Claude Code, Codex, Bedrock — with secret redaction before send.
  • Broad coverage, one tool. Web · API (REST/GraphQL/WebSocket/gRPC) · headers/CORS/cookies · secrets · LLM/AI systems (OWASP LLM Top 10) · containers/K8s · cloud (CSPM) · source (SAST) · API specs.

Install

pip install deluluscan            # from PyPI
# optional extras: bedrock (AWS), web (FastAPI UI), xlsx (Excel export), or everything:
pip install "deluluscan[all]"

Or from source:

git clone https://github.com/rsh1k/deluluscan && cd deluluscan
pip install -e . --break-system-packages

Quickstart

# unified assessment of an authorized target -> local report files (no publishing)
python3 -m deluluscan.assess --url http://127.0.0.1:8080/ \
    --sast-path ./src --spec openapi.json \
    --formats md,html,json,sarif --out-dir ./report

# full active scan with an OpenAPI spec
python3 -m deluluscan.cli --config config.yaml --openapi-file openapi.json --allow-state-changing

# reason with a local, offline model (no data leaves your host)
python3 -m deluluscan.cli --config config.yaml --ai ollama --ai-model qwen2.5:7b

Copy config.example.yamlconfig.yaml, set your target and identities, and leave the scan.scanners list commented out to run the full set. See docs/LOCAL_MODELS.md for running a model on a low-RAM / WSL / non-NVIDIA machine.

Capabilities

Domain Module What it does
Web / API scanning scanners/, verify/ 40+ checks across the OWASP API/Web Top 10, with a deep differential verification layer (identity matrix, filter-bypass, read-back sink classification, weaponizability grading).
Reconnaissance recon/ Tech/JS-library fingerprint (+ known-vulnerable versions), CT-log subdomain enumeration, content discovery.
HTTP hardening headers/ Security headers, CORS (wildcard / reflected-origin-with-credentials), cookie flags.
Secrets secrets/ Credential exposure in responses & JS (AWS/GitHub/Google/Slack/Stripe/… + entropy-gated generic), matched masked.
Deeper web/API webapi/ GraphQL introspection → surface map, WebSocket CSWSH, gRPC reflection.
API spec apispec/ OpenAPI/Swagger security lint (missing auth, secrets in query, http servers, mass-assignment).
Source (SAST) sast/ Dangerous patterns per language (eval/exec, deserialization, SQL concat, weak crypto, XSS sinks) + secrets, file:line.
LLM / AI systems llm/ Bring-your-own-target OWASP LLM Top 10 pentest — prompt injection, jailbreaks, multi-turn crescendo, system-prompt leakage.
Containers / K8s container/ Dockerfile / Kubernetes / compose misconfig (privileged, host ns, docker-socket escape, caps, secrets) + exposed control planes.
Cloud (CSPM) cloud/ AWS/GCP/Azure posture over a collected inventory + SSRF→IMDS→credentials (values redacted).
Agentic exploitation agentic/ Bounded observe→act→verify loop over an allowlist of safe capabilities; human-in-the-loop for state changes; deterministic proof.
Correlation correlate/ Combine findings into attack chains (SSRF+metadata→cloud creds, XSS+cookie→session hijack) and feed the agent objectives to prove.
AI layer ai/, kb/ Pluggable providers + an offline BM25 knowledge index (CVEs/advisories/Mantis) that grounds the AI.
Grey-box telemetry/ Tap the target container's logs/mem/CPU (--observe) and correlate server events to the exact probe.
Reporting assess/, reporting/ Merge findings → local Markdown / HTML / JSON / SARIF / CSV / XLSX / JUnit. No online publishing.

Each capability also has a standalone CLI, e.g. python3 -m deluluscan.recon --url …, python3 -m deluluscan.container --path ./deploy, python3 -m deluluscan.llm --provider ollama ….

Design principles

  • The report may only state what the scan observed. Untested surfaces read as untested; no synthesized evidence. Attack chains are hypotheses until the agent proves them.
  • Confirm to proof, never weaponize. Heavy exploitation is delegated to opt-in, host-allowlisted third-party tools (nuclei, sqlmap without --dump, interactsh).
  • The authorization boundary is a feature, not a limitation.

Extending

  • Signatures live in deluluscan/fingerprint.py; scanners in deluluscan/scanners/ (self-register via SCANNER_REGISTRY).
  • Out-of-tree plugins load from a directory (deluluscan/plugins.py); Nuclei-style YAML templates drop into templates/ (deluluscan/templates.py) with no code.
  • Run the tests: python3 -m tests.<suite> (e.g. test_verify, test_llm_pentest, test_recon).

License

GNU Affero General Public License v3.0 — see LICENSE. If you run a modified version as a network service, the AGPL requires you to offer that version's source to its users.

Provided for authorized security testing and educational use only. You are responsible for ensuring you have permission to test any target. The authors assume no liability for misuse.

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