NetAuditAI
A network configuration security auditor that refuses to guess.
Built for Smart India Hackathon 2026, problem statement SIH26155 (NTRO, Cybersecurity):
AI-Driven Multi-Vendor Network Security Compliance Auditor.
NetAuditAI reads router, switch, firewall and cloud firewall configurations, answers 24 security checks on
every one of them, and cites the exact configuration line behind every answer. When it cannot decide, it says so
instead of passing the check. It fixes what it is sure about, proves every fix by rescanning a copy, and never
runs a command on a device.
Upload or SSH-collect a config → cited PASS / FAIL / UNKNOWN per check → posture + coverage
→ verified fixes as device commands → PDF report, SARIF, signed audit ledger
Contents
Why it is different
Most config auditors either support a handful of vendors with hand-written rules, or put an LLM in front of the
file and trust what comes back. NetAuditAI does neither.
| Principle | What it means in practice |
|---|
| Undecided is an answer | UNKNOWN and NOT_CONFIGURED exist so missing evidence is never silently a PASS. Posture is computed from decided checks only, and coverage says how much could be decided. |
| Every verdict is traceable | Framework requirement → check → vendor-neutral fact → configuration line → verdict. No verdict without a cited line (or a documented vendor default). |
| AI proposes, code verifies, a human confirms | The AI only looks at checks the engine left undecided, its citations are verified deterministically, and its answers are never scored until an administrator confirms them. |
| Learning without training | An administrator confirms how an unfamiliar line reads; that becomes a typed, validated recognizer that answers decisively on every later scan, with no AI call. |
| Fixes are proven, not generated | Fixes come from fixed recipes or from the same recognizer that read the line. Each one is applied to a copy and rescanned; it only counts if the check now passes and nothing else regressed. |
| Read-only toward devices | Live collection opens one SSH session with read-only commands. Nothing NetAuditAI produces is ever executed on a device. |
Quickstart
Prerequisites: Python 3.10+, Node.js 18+. An AI key is optional; everything except AI explanations, chat and
AI proposals works without one.
# 1. Backend (http://localhost:8000, API docs at /docs)
cd backend
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
uvicorn app.main:app --reload --port 8000
# 2. Frontend, in a second terminal (http://localhost:5173)
cd frontend
npm install
npm run dev
Open http://localhost:5173, choose New scan, and upload demo-sih/cisco_oneclick.cfg.
No UI needed? Scan from the command line:
cd backend
python -m app.cli scan ../demo-sih/ --fail-on high
Optional settings live in backend/.env (copy backend/.env.example) and frontend/.env. See
Configuration.
Demo
Four demos in demo-sih/. Each goes from a bad first scan to posture 100 with 0
problems once the corrected file is rescanned. This is pinned by backend/tests/test_demo_fix_to_100.py.
| File | First scan | How it gets to 100 |
|---|
cisco_oneclick.cfg | posture 41, 15 problems | One click. Deterministic Cisco recipes, no input needed. |
paloalto_ai_human.cfg | posture 30, 10 problems | 5 fixed by seed write-back (no parser), 5 by an AI-drafted or typed command, each verified on a copy. |
unknown_vendor.cfg | no score, 3 suspected problems | Teach 3 lines in Adaptive learning, then 3 verified commands. |
fortigate/ (3 files, one upload) | fleet posture 80, 13 problems | One click; the download is a .zip of 3 corrected files. Also shows a cross-device NTP mismatch and a closed attack path. |
The two-minute judge path and the full walkthrough are in docs/demo.md. A browser test
(cd frontend && npm run e2e) walks the same path.
How it works
flowchart TD
subgraph S1["1 . Ingest"]
UP["Upload a file"]
SSH["Collect over SSH<br/>Netmiko / NAPALM, read-only"]
MEM["Held in memory, max 2 MB<br/>never written to disk"]
UP --> MEM
SSH --> MEM
end
MEM --> DET{"Vendor detection<br/>+ grammar coverage"}
subgraph S2["2 . Read: configuration to SecurityFacts"]
PAR["Dedicated parser + vendor defaults<br/><i>decisive</i>"]
TOK["Generic tokenizer<br/>JSON and Terraform flattened first"]
REC["Recognizers from the store<br/>380 shipped + taught, <i>decisive</i>"]
HEU["Lexicon heuristics<br/><i>provisional</i>"]
TOK --> REC
TOK --> HEU
end
DET -->|"Cisco IOS or FortiGate,<br/>grammar confirmed"| PAR
DET -->|"any other vendor,<br/>or unverified"| TOK
FACTS[("SecurityFacts<br/>predicate, value, scope,<br/>cited lines, assurance")]
PAR --> FACTS
REC --> FACTS
HEU --> FACTS
subgraph S3["3 . Decide"]
CTL["24 checks on every configuration<br/>+ organisation policy"]
SCORE["Posture + coverage<br/>decisive evidence only"]
CTX["Attack paths, risk, drift,<br/>fleet checks, framework views"]
CTL --> SCORE
CTL --> CTX
end
FACTS --> CTL
subgraph S4["4 . Learn: unknown vendors"]
JUDGE["AI judge (optional)<br/>redacted, fenced, budgeted, cached"]
VER["Deterministic citation verifier<br/><i>ai_verified: shown, never scored</i>"]
HUM["Administrator confirms<br/>in Adaptive learning"]
DB[("Recognizer store<br/>feeds step 2 on every later scan:<br/>decisive, no AI call")]
JUDGE --> VER --> HUM
HUM -->|"saves a recognizer"| DB
end
CTL -->|"UNKNOWN /<br/>NOT_CONFIGURED"| JUDGE
CTL -->|"suspected FAIL"| HUM
subgraph S5["5 . Fix: decisive FAILs only"]
RCP["Confirmed vendor:<br/>deterministic recipe"]
WB["Unconfirmed vendor:<br/>seed write-back or candidate command"]
RESCAN["Apply to a copy and rescan:<br/>check passes, nothing regresses"]
OK["Administrator confirms<br/>never executed on a device"]
RCP --> RESCAN
WB --> RESCAN
RESCAN --> OK
end
CTL --> RCP
CTL --> WB
OUT["UI, PDF report, baseline JSON, SARIF<br/>+ signed, hash-chained audit ledger"]
SCORE --> OUT
CTX --> OUT
OK --> OUT
| Stage | What happens | Code |
|---|
| Ingest | Upload or SSH collection. Collection is restricted to private address space by default; credentials are used for one session and never stored. | app/collect/ |
| Detect | The vendor is confirmed only when the file follows its grammar (coverage threshold 0.7). Look-alikes (NX-OS, ASA, Arista, FortiSwitch, mixed files) are reported as unverified and take the generic path. | app/parsers/detector.py, coverage.py |
| Read | Parsers, recognizers and heuristics all produce the same vendor-neutral SecurityFacts. This is the Security Baseline Model, downloadable from GET /api/scan/{id}/baseline. | app/parsers/, app/structure/, app/facts/ |
| Decide | Every check runs on every configuration; the vendor only decides where facts come from. | app/controls/, app/analysis/ |
| Learn | AI proposals and suspected lines become recognizers only through an administrator. | app/ai/judge.py, app/adaptive/, app/db/ |
| Fix | Recipes (Cisco, FortiGate), seed write-back, vendor reference commands and candidate commands, each verified by rescanning a copy, then written as the device's own CLI in lockout-safe order. | app/remediation/ |
| Report | PDF per device, executive summary, SARIF, Ed25519-signed hash-chained ledger. | app/reporting/, app/ledger.py |
The full design, including the exact gates a recognizer must pass, is in docs/architecture.md.
Reading the results
Status per check
| Status | Meaning |
|---|
PASS | Evidence says the setting is secure, with a cited line or a documented vendor default. |
FAIL | Evidence says the setting is insecure. One FAIL per failing scope (interface, VTY range, policy). |
UNKNOWN | Something relevant exists but could not be decided (conflict, missing unit, unread syntax, AI proposal awaiting confirmation). |
NOT_CONFIGURED | Nothing relevant was found. Never counted as a PASS. |
N_A | Proven not to apply, for example no VPN on a device whose parser reads VPNs. Only a confirmed parser can prove this. |
Assurance per verdict
| Assurance | Source | Counts toward posture? |
|---|
parser | Dedicated Cisco IOS / FortiGate parser | Yes |
confirmed | Shipped seed recognizer or administrator-confirmed recognizer | Yes |
default | Documented default of a confirmed vendor | Yes |
heuristic | Lexicon reading of an unfamiliar line ("Suspected FAIL") | No |
ai_verified | AI proposal whose citations passed verification ("AI proposes ...") | No |
Scores
posture = weighted decisive PASS / weighted decisive (PASS + FAIL) x 100 "-" when nothing was decided
coverage = weighted decisive (PASS + FAIL) / weighted applicable checks
weights = critical 10, high 6, medium 3, low 1
Posture and coverage are always shown together, with the range posture would take if every undecided check
failed or passed, and a list of critical checks not assessed. The response still carries a deprecated
score field for old scripts; the UI ignores it.
Framework views regroup the same results under NIST SP 800-53 Rev. 5, the DISA Network Device Management
SRG, ISO/IEC 27001:2022 Annex A and, for confirmed vendors, verified CIS Benchmark items. They are evidence, not a
compliance certification. PCI DSS and CIS Controls v8 are deliberately not mapped.
Vendor support
| Configuration | How it is read | Decisive? | Remediation |
|---|
| Cisco IOS / IOS-XE | Dedicated parser, confirmed by grammar coverage | Yes | Deterministic recipes, verified |
Fortinet FortiGate (with a config firewall / config vpn section) | Dedicated parser, confirmed by grammar coverage | Yes (password storage and AAA are not read: UNKNOWN) | Deterministic recipes, verified |
| Juniper Junos, Palo Alto PAN-OS, Arista EOS, Huawei VRP, Aruba AOS-CX, Check Point Gaia, Extreme EXOS, MikroTik RouterOS, Cisco NX-OS / ASA / IOS-XR, SONiC, Cumulus NVUE, Dell OS10, VyOS, FortiSwitchOS | Generic tokenizer + shipped recognizers + heuristics | Where a recognizer reads the line; otherwise provisional | Seed write-back, or candidate commands verified on a copy |
| Terraform (AWS, Azure, GCP) and cloud exports (AWS security groups, Azure NSG, GCP firewall JSON) | Flattened to one statement per rule, read by shipped recognizers; device-only checks are N_A | Yes for an open rule; an unresolved var.x stays undecided | None generated |
| Anything else | Generic tokenizer + heuristics + optional AI judge | Provisional until an administrator teaches it | Candidate commands once a finding is decisive |
The vendor is always decided by code. An AI vendor guess is shown as evidence only and never selects a parser,
defaults or remediation. Device identity (hostname, OS version, FortiGate model and firmware) is reported only
when the file states it; serial numbers and chassis details are never invented.
Serial number and hardware. A configuration rarely states them, so upload the device's show version,
show inventory, show chassis hardware, get system status or show system info output in the same upload
(core-01.cfg with core-01-version.txt). It is recognised as command output, attached to its configuration by
the hostname it states or by file name, and never scanned as a device of its own; an output that matches no
single configuration is reported, never guessed onto one. Live collection runs the same read-only command for
you. The report names the file the serial number came from.
The 396 shipped recognizers live in backend/data/seed_recognizers.json,
load into an empty database on first start, and are marked source=seed so shipped knowledge can be audited
separately from what a deployment was taught. See docs/seed-knowledge.md.
The 24 checks
| ID | Severity | Check |
|---|
| MGMT-001 | Critical | Insecure management protocol (Telnet) enabled |
| MGMT-002 | High | Insecure HTTP management enabled |
| MGMT-003 | Critical | Unrestricted management access |
| MGMT-004 | Critical | Weak or default SNMP community strings |
| MGMT-005 | Critical | Plaintext or weakly encrypted passwords |
| MGMT-006 | Medium | Missing or disabled session timeout |
| MGMT-007 | High | SSH version 1 or weak SSH configuration |
| MGMT-008 | High | AAA not configured |
| MGMT-009 | Low | Missing login banner |
| MGMT-010 | Critical | Management reachable from an untrusted interface |
| MGMT-011 | High | SNMPv1/v2c in use |
| AUTH-001 | High | No login brute-force protection |
| AUTH-002 | Medium | Weak password policy |
| AUTH-003 | Medium | Default administrator account in use |
| AUTH-004 | High | Direct root login over SSH allowed |
| BOUNDARY-001 | Critical | Overly permissive firewall / ACL rules |
| BOUNDARY-002 | Medium | IP source routing enabled |
| BOUNDARY-003 | Medium | CDP / LLDP enabled on an external interface |
| BOUNDARY-004 | Medium | Interface hardening (redirects, proxy-ARP, directed broadcast) |
| LOG-001 | High | No remote syslog server |
| LOG-002 | Medium | NTP not configured or unauthenticated |
| LOG-003 | Medium | Traffic rules that do not log |
| CRYPTO-001 | High | Weak VPN / IPsec algorithms |
| CRYPTO-002 | High | Weak management cryptography (SSH / HTTPS) |
Per-vendor facts and remediation: docs/detection-rules.md.
The checks are data. All 24 live in backend/data/controls.json: question,
severity, the facts each reads, its judge, its fix phase, its framework mappings and per-vendor reference
commands. Adding a check, a framework mapping or a whole framework is an edit to that file, not to code. A check
can even bring its own boolean fact and decide it with a rule written in the file ({"forbid": true},
{"max": 15}), read by recognizers taught or shipped for it. The file is validated when the backend starts: a
check naming an unknown fact, judge or phase stops it instead of silently deciding nothing.
Measured accuracy
Every labelled configuration run through the real pipeline with shipped knowledge only and no AI. Reproduce
with python backend/scripts/benchmark.py; full table in benchmark/RESULTS.md, labels in
benchmark/labels.json.
| Set | Insecure settings caught (decided FAIL) | Missed | False alarms on secure settings |
|---|
| 20 vulnerabilities planted in the demo files (Cisco IOS, PAN-OS) | 19/20 (the other 1 flagged as suspected) | 0 | 0 of 4 |
| 31 labelled fixtures: 8 vendors without a parser, SONiC, Cumulus, Terraform, Azure / GCP exports | 92/112 (1 more flagged as suspected, 19 left undecided) | 0 | 0 of 84 |
| Held-out: 9 real configurations never seen during development (pybatfish example networks), labels committed before the first run. Not in the repository: needs the download step below | 21/21 (first run 20/21; the miss was a parser bug, since fixed) | 0 | 0 of 13 |
"Undecided" is not a miss: the engine shows the line and what it would need, and never calls an insecure setting
secure. tests/test_benchmark.py fails if detection drops or a single miss or false alarm appears. The held-out
files are not committed (they are pybatfish's); backend/scripts/benchmark.py prints the command that fetches
them at the pinned commit, and the same test then holds them to zero misses and zero false alarms.
Reproducing from a clone: the planted and fixtures sets reproduce as shown (their files, including the
teach/*_5_configs dialect sets, are committed). The held-out row does not until you fetch the pybatfish files into
datasets/pybatfish/ with the command backend/scripts/benchmark.py prints; without them it is skipped, not failed.
See testing.md.
A separate live probe of 6 prompt-injection attacks against the AI judge succeeded 0 times
(backend/scripts/probe_injection.py), and a fully hijacked model is tested to change no verdict.
More than a checklist
| Feature | What it does |
|---|
| Attack paths | Chains decided FAILs into how an attacker gets in (reach the login → capture the password → log in as admin), each step citing its line, plus the one fix that breaks the path. Each path is validated against a positive and a negative configuration. |
| Contextual risk | Worst problem, internet exposure, attack paths and the asset importance you set, by a formula shown on screen and in the report. |
| Fix order | Remediation sorted by risk removed per unit of effort, with the reason for each position. |
| Device commands | Every verified fix is also written as the commands that make it, in the device's own dialect (IOS / EOS configure terminal blocks, FortiOS config / edit, Junos and PAN-OS set / delete, Huawei undo, RouterOS sections). They are ordered by phase, not severity: secure access first, then hardening, then switching off what it replaced, and management restrictions last, so entering them top to bottom never cuts your own session. Where nothing could be verified, the vendor's reference commands are shown and labelled as not checked against your file. |
| Changes since last audit | Rescan a device and see what was fixed, what newly broke and which attack paths closed. Losing evidence is never counted as a fix. |
| Fleet checks | Problems only visible across devices: the same SNMP community on several devices (compared by hash, never shown) and inconsistent NTP / syslog servers. |
| Organisation policy | Your own stricter baseline (idle timeout, login attempts, password length, approved NTP / syslog servers). It can only tighten, never loosen. See docs/policy.md. |
| Known CVEs | CVEs for the OS version the file states, from a committed NVD cache. Labelled as context, not an assessment. No live call. |
| Audit ledger | Scans, taught recognizers, fix decisions and reports are hash-chained, and every entry is signed with the deployment's Ed25519 key. Rewriting an entry and recomputing the chain after it is still caught, because the signature needs the private key. Anyone can check an export offline with only the public key: . A report PDF can be checked byte for byte. |
Configuration
Every setting is optional. Backend settings go in backend/.env, frontend settings in frontend/.env.
| Variable | Default | Purpose |
|---|
GROQ_API_KEY, GROQ_API_KEY_1 to _4 | empty | AI judge, explanations and chat. Tried in order; the next key is used on 429 / 401 / 403 / 404. Keys from one Groq organization share one daily quota. |
LOCAL_AI_URL, LOCAL_AI_MODEL, LOCAL_AI_TIMEOUT | empty, llama3.1:8b, 120 | Use a local OpenAI-compatible model instead of Groq. When set, the Groq keys are ignored. |
AI_JUDGE_MAX_CALLS_PER_SCAN | 2 | AI judge requests per scan. Cache hits are free. |
API_KEY | empty | When set, every /api request needs an X-API-Key header. The bundled frontend does not send it yet, so only set it for API-only use or behind a proxy that adds it. |
CORS_ORIGINS | * | Comma-separated list of allowed origins. |
ADAPTIVE_DB_PATH | backend/data/adaptive.db | SQLite file for recognizers, rejected lines, the AI cache, the scan archive and the audit ledger. |
DATABASE_URL | empty | Postgres URI (e.g. Supabase session pooler) instead of SQLite, for hosts that wipe their disk on restart. |
LEDGER_SIGNING_KEY | empty | Base64 of a 32-byte Ed25519 private key that signs the ledger. Empty: a key file is created in backend/data/ on first use (owner-only, git-ignored). Set it on a host that wipes its disk, or each restart starts a new key. |
LEDGER_TRUSTED_KEYS | empty | Comma-separated public keys (hex) of earlier signing keys whose entries should still verify after a rotation. |
VENDOR_PARSE_COVERAGE_THRESHOLD | 0.7 | Share of lines that must follow a vendor's grammar before its parser is trusted. |
LIVE_COLLECTION_ENABLED | true | SSH collection from devices. Set false on any backend others can reach. |
LIVE_COLLECTION_NETWORKS |
Live collection with NAPALM (preferred where it has a driver) needs pip install -r requirements-live.txt.
Netmiko is already included and covers all 12 supported platforms: Cisco IOS / IOS-XE, NX-OS and IOS-XR, Arista EOS,
Juniper Junos, FortiGate, Palo Alto PAN-OS, HPE Aruba AOS-CX, Huawei VRP, Check Point Gaia, Extreme EXOS and MikroTik
RouterOS.
Command line and CI
The same engine without a server, built for pipelines:
cd backend
python -m app.cli scan ../configs/ --fail-on high --sarif netaudit.sarif
- Deterministic: AI is always off, and a throwaway database holds only shipped knowledge, so the same files
give the same result.
- Only decided FAILs fail the build. Suspected problems are reported but never block.
- Exit codes:
0 passed, 1 a decided problem at or above --fail-on, 2 bad input.
- SARIF 2.1.0 output shows each problem on its line in a pull request (GitHub code scanning).
- Offline ledger check:
python -m app.cli ledger-verify export.json --public-key <hex> checks every hash and
signature of GET /api/ledger/export on any machine. Exit 0 intact, 1 not.
Options, --policy, --framework and a ready GitHub Actions workflow: docs/cli.md.
What is stored
| Data | Where | Survives a restart? |
|---|
| Uploaded or collected configurations | Backend memory only | No. Never written to disk. |
| Active scans (needed to teach and fix) | Backend memory | No. After a restart an archived scan reopens read-only; teaching or fixing asks for the file again. |
| Scan archive: redacted results and remediation plans | scans table | Yes |
| Recognizers and learned mappings (shipped and taught) | learned_mappings | Yes |
| Lines an administrator rejected | rejected_lines, redacted | Yes |
| Verified AI judge answers | ai_judge_cache, keyed by a hash of the redacted prompt | Yes |
| Audit ledger: hashes of scans, recognizers, fix decisions, reports, each signed | ledger | Yes |
| Ledger signing key | backend/data/ledger_signing_key.pem (or LEDGER_SIGNING_KEY) | Yes, unless the disk is wiped |
| History list in the UI | Browser localStorage, summaries only | Browser only |
Tables live in SQLite by default or in Postgres when DATABASE_URL is set; the same SQL runs on both. A line
holding a password, key or community string is refused as a recognizer, and every AI prompt, archived scan and
report is redacted.
Deploying safely
This is a prototype built to run on a laptop for a demo. If you expose it anyway:
- Set
LIVE_COLLECTION_ENABLED=false. Otherwise the backend will open SSH sessions to hosts it is given.
- Never set
LIVE_COLLECTION_NETWORKS=any on a public host.
- Set
API_KEY and put a proxy in front that adds the header for the UI.
- Set
CORS_ORIGINS to your frontend origin.
- Set
DATABASE_URL if the host loses its disk on restart, or everything administrators taught is lost.
- On such a host also set
LEDGER_SIGNING_KEY, and keep a copy of GET /api/ledger/public-key somewhere else:
an offline check is only as good as a public key kept apart from the server.
Trust boundaries and guarantees: docs/security-model.md.
Known limitations
- Access control is one optional shared key: no users, no roles, no per-tenant isolation.
- Parsers exist for Cisco IOS / IOS-XE and FortiGate only. The IOS grammar is a curated list of command roots,
so an unusual but valid IOS file can come out unverified.
- Shipped recognizers answer part of each dialect, not all of it. Anything they do not cover has to be taught.
- Heuristics can misread an unfamiliar dialect until an administrator confirms or rejects the line. They never
affect posture.
- Redaction is pattern-based; a secret behind an unlisted keyword could reach the AI.
- The AI judge runs only for unknown or unverified vendors. Undecided checks on Cisco / FortiGate are not
escalated.
- Candidate commands for unconfirmed vendors are verified only when they remove or switch off the cited lines,
or when a reviewed recognizer reads every line. A verified candidate means the finding is gone from this file,
not that the command is safe to run on the device.
- Adding a missing setting on an unconfirmed vendor is limited to syslog and the login banner.
/api/assistant/status reports AI as available whenever a key is set, even when the quota is used up.
The full list of open items is in docs/roadmap.md.
Repository layout
backend/
app/
collect/ SSH collection (Netmiko, optional NAPALM)
parsers/ vendor detection, grammar coverage, Cisco IOS and FortiGate parsers
structure/ generic tokenizer, JSON and Terraform flattening
facts/ predicates, parser facts, defaults, lexicon, heuristics, recognizers, seed loader
controls/ catalog loader, judges, evaluator, framework views, policy
analysis/ scoring, attack paths, risk, drift, fleet checks, CVE lookup
ai/ model client, redaction, prompt fence, AI judge, remediation drafts
adaptive/ teaching flow: capture, relevance, matching, review service
remediation/ recipes, verifying engine, seed write-back, candidate commands, device CLI
reporting/ PDF reports
db/ SQLite / Postgres, recognizer store, scan archive
api/routes/ scan, collect, remediation, adaptive, assistant, report, ledger
cli.py command line for CI
ledger.py signed, hash-chained audit ledger
data/ the 24 checks (controls.json), shipped recognizers, factory defaults, CVE cache,
attack-path validation
scripts/ benchmark, CVE cache builder, injection probe, architecture PDF
tests/ pytest suite and labelled fixtures
frontend/src/ React 19 + Vite app (hand-written CSS, no component library)
benchmark/ ground-truth labels and generated results
demo-sih/ the three demo configurations
sample/ extra sample configurations
docs/ design and reference documentation
Testing
# backend: every AI call is mocked, every test gets its own SQLite database
cd backend
python -m pytest tests -q -n auto
NETAUDIT_LIVE_AI=1 python -m pytest tests -q # also runs the 2 live-AI tests (needs a Groq key)
# frontend
cd frontend
npm test
npm run build
npm run e2e # Playwright demo walkthrough
Details: docs/testing.md.
Documentation
Start at the documentation index, which has reading paths for judges, operators, developers and
security reviewers.
| Document | Contents |
|---|
| project-overview.md | System context, repository map, module dependencies, frontend pages |
| architecture.md | The full pipeline, facts, checks, scoring, AI, recognizers, persistence, remediation |
| architecture-brief.pdf | Two-page architecture brief (evaluation deliverable) |
| security-model.md | Trust boundaries and safety guarantees |
| ai-design.md | AI judge, verification, cache, remediation drafts |
| seed-knowledge.md | Shipped recognizers and how to add one |
| detection-rules.md | The 24 checks: how each is decided, per-vendor sources, fixes, every framework requirement |
| parser-design.md | Vendor detection, grammar coverage, the two parsers |
| api.md | Endpoints and response fields (interactive docs at /docs when the backend runs) |
| cli.md | Command line, exit codes, SARIF, GitHub Actions |
License
All rights reserved. See LICENSE. No copying, use, modification or redistribution without written
permission from the author. Organisers, evaluators and judges of Smart India Hackathon 2026 may view, download and
run it to evaluate this submission.
