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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 PRs Welcome

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, and every AI note is anchored to the captured traffic — any claim the scan did not observe is marked unverified rather than stated as fact (anti-hallucination).
  • Runs on your terms. Pluggable AI backends — Anthropic, OpenAI, DeepSeek, Ollama (fully offline), Claude Code, Codex, Bedrock — with secret redaction before send.
  • Knows what it's testing. Fingerprints the platform (24 profiles — WordPress/Drupal/ Joomla, Laravel/Django/Rails/Spring/Tomcat, Jenkins/GitLab/Grafana/Kibana, Elasticsearch/ Kubernetes, …) and tests it accordingly: its API shape, auth model, sensitive surfaces, and version-gated known CVEs (Nessus-plugin model). Detects the edge too — WAF/CDN (18 vendors: Cloudflare/Akamai/Fastly/Imperva/…), open ports/services, honeypot & IDS/IPS.
  • Broad coverage, one tool. Web · API (REST/GraphQL/WebSocket/gRPC) · headers/CORS/cookies · secrets · passive analysis (ZAP-style) · JS/SPA endpoint discovery (static + optional headless-browser crawl) · TLS/SSL · DNS/email · subdomain takeover · HTTP request smuggling (timing-only) · SMB/LDAP posture · LLM/AI systems (OWASP LLM Top 10) · containers/K8s · cloud (CSPM) · source (SAST) · API specs.
  • Shift-left in one command. python3 -m deluluscan.reposcan --path . scans a whole repo across SAST, secrets (incl. git history), dependencies, IaC (Terraform/CloudFormation, AWS/GCP/Azure), containers/Kubernetes + RBAC, CI/CD workflows, and SBOMs — one merged report.
  • Prioritized like modern ASPM. Every finding is ranked by real-world risk — EPSS exploit probability, CISA KEV (confirmed exploited), a combined 0–100 priority score, and MITRE ATT&CK technique tags — so you fix what matters first, not just what scores high.

Install

pip install deluluscan            # from PyPI
# optional extras: bedrock (AWS), web (FastAPI UI), xlsx (Excel export),
#   crawler (headless-browser dynamic crawl), or everything:
pip install "deluluscan[all]"
# the crawler extra also needs a browser binary:  playwright install chromium

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.yaml → config.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/ 43 checks across the OWASP API/Web Top 10, with a deep differential verification layer (identity matrix, filter-bypass, read-back sink classification, weaponizability grading). Burp-style Intruder (sniper/battering-ram/pitchfork/cluster-bomb).
Reconnaissance recon/ Tech/JS-library fingerprint (+ known-vulnerable versions), CT-log subdomain enumeration, content discovery, and static JS endpoint extraction (fetch/axios/XHR → shadow API surface).
Platform intelligence platforms/ Fingerprints 24 platforms (WordPress/Drupal/Joomla/Quilzo, Laravel/Django/Rails/Spring/Tomcat, Jenkins/GitLab/Grafana/Kibana, Elasticsearch/Kubernetes, …) → API shape, auth model, sensitive surfaces, user-enum & version disclosure, plus version-gated known CVEs (Nessus-plugin model).
Edge / network recon netscan/ WAF/CDN/proxy detection (18 vendors, wafw00f-style passive+active), TCP port/service scan + banner grab, TLS/SSL config (deprecated protocols, weak/expired/mismatched certs, no-PFS), honeypot heuristics, IDS/IPS inference, SMB/LDAP posture (signing, SMBv1, anonymous bind).
OSINT & takeover recon/ DNS/email intel (SPF/DMARC/AXFR + email harvest), subdomain-takeover — live provider fingerprints (14 providers, CNAME-corroborated) and dangling-CNAME (NXDOMAIN-target) takeover inferred from DNS alone.
Shadow environments shadowenv.py Derive staging/sandbox/dev host-variants of a target and diff their security posture vs production (auth dropped, security headers missing) — the staging-weaker-than-prod root cause; scope-respecting (out-of-scope hosts stay unprobed leads).
Prioritization epss/,kev/,priority/,attack/ Ranks findings by real-world risk: EPSS exploit probability, CISA KEV (confirmed exploited), a combined 0–100 priority score, and MITRE ATT&CK technique tagging.
Rules of Engagement roe/ Parse a RoE doc (YAML/JSON/text) and enforce it: in-scope/out-of-scope (host/domain/CIDR), prohibited tests, and testing window — wired into assess --roe to refuse out-of-scope/out-of-window runs before anything starts.
Repo DevSecOps scan reposcan/ One command over a whole repo: SAST + secrets, git-history secrets, IaC, containers/K8s+RBAC, CI/CD, SBOM — merged, deduped, ATT&CK/priority-enriched → md/html/json/SARIF.
Supply chain depconfusion/,githistory/,subresource/,sbom/ Dependency confusion, secrets in git history, missing Subresource Integrity, and SBOM analysis (CycloneDX/SPDX → known-vulnerable components like Log4Shell + integrity gaps).
Cloud IaC & CI/CD iac/,cicd/,k8srbac/ Terraform + CloudFormation misconfigs (AWS/GCP/Azure), GitHub Actions security (script injection, pwn requests, unpinned actions), Kubernetes RBAC (wildcard roles, escalation verbs, anonymous bindings).
AI / MCP / agentic llm/,mcp/,agentaudit/ OWASP LLM Top 10 pentest, MCP tool-poisoning analysis, and OWASP Agentic Top 10 (2026) agent-config audit (excessive agency, memory poisoning, privilege abuse).
Client-side & crypto csp.py,protopollution/,jwtaudit/ CSP bypass analysis (Google-CSP-Evaluator-style), client-side prototype pollution (live-DOM proof), offline JWT audit with HS256 weak-secret cracking.
Passive analysis passive/ ZAP-style, no extra requests — stack traces / SQL errors, debug consoles (Werkzeug/Whoops/Django), directory listing, internal-IP & cloud internal-resource identifiers (service accounts / buckets / ARNs), secrets-in-URL, HTML-comment leaks. Runs over every collected response.
Dynamic crawl crawler/ Optional headless-browser (Playwright) AJAX-spider: renders JS-heavy apps and captures the API calls the client actually makes — the dynamic surface a static parse can't resolve.
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, shadow-env-auth-drop+data→cross-env access, subdomain-takeover+cookie→session/OAuth abuse, cloud-identifier-leak+SSRF→targeted SSRF), visualize them as an Attack Chains graph in the dashboard, 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, plus evidence anchoring — every AI note is checked against the captured traffic and any claim the scan did not observe is marked unverified (anti-hallucination).
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.platforms --url …, python3 -m deluluscan.netscan --url …, python3 -m deluluscan.passive --url …, python3 -m deluluscan.crawler --url …, python3 -m deluluscan.container --path ./deploy, python3 -m deluluscan.llm --provider ollama …. See docs/PLATFORM_INTELLIGENCE.md for the platform/edge detection design and a Nessus/Burp/ZAP capability map.

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).

Contributing

Contributions are very welcome — Deluluscan gets better every time someone adds a platform signature, a detection rule, a known CVE, or a scanner. Many additions are just data (no engine code): a platform profile, a WAF/CDN signature, a CVE, a passive rule, a Nuclei-style YAML template. See CONTRIBUTING.md for the extension points, dev setup, and how to run the tests.

  • New here? Look for good first issue and help wanted.
  • Found a bug or have an idea? Open an issue.
  • Every contribution must keep Deluluscan defensive and authorized-testing only — the authorization boundary stays, and we confirm to proof, never weaponize.
  • Found a security issue in Deluluscan itself? Please report it privately — see SECURITY.md.
  • Participation is governed by our Code of Conduct.

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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