The Hundred-Eyed Database Guardian

Know who connects. Control what they do. Protect what they see.

Argus is a protocol-aware database firewall and access proxy written in Go. It sits between applications and databases — inspecting every query, blocking SQL injection and dangerous operations, enforcing access policies in real time, masking sensitive data at the result level, and logging everything for audit and compliance.

┌──────────┐         ┌──────────────────────────────────────────────────┐         ┌──────────┐
│          │   TCP   │                     Argus                        │   TCP   │          │
│  Client  │────────>│  ┌─────────┐  ┌─────────┐  ┌────────────────┐   │────────>│ Database │
│  (App)   │<────────│  │Protocol │  │  WAF /  │  │   Masking /    │   │<────────│ Server   │
│          │         │  │ Handler │  │ Policy  │  │ PII Protection │   │         │          │
└──────────┘         │  └─────────┘  └─────────┘  └────────────────┘   │         └──────────┘
                     │  ┌─────────┐  ┌─────────┐  ┌────────────────┐   │
                     │  │Session  │  │ Audit / │  │ Connection     │   │
                     │  │Manager  │  │ SIEM    │  │ Pool + CB      │   │
                     │  └─────────┘  └─────────┘  └────────────────┘   │
                     └──────────────────────────────────────────────────┘

Traditional PAM tools manage credentials. They answer "who connected." They do not answer "what did they do" or "what did they see."

Argus answers all three — and blocks what shouldn't happen:

• SQL injection detection — tautology (OR 1=1), UNION-based, stacked queries, blind injection (SLEEP, BENCHMARK, WAITFOR DELAY), comment termination, encoding tricks (CHAR() obfuscation)
• Schema enumeration blocking — information_schema, pg_catalog, sys.*, mysql.user access detection
• System command blocking — xp_cmdshell, INTO OUTFILE, LOAD_FILE, pg_read_file, lo_export
• Privilege escalation detection — CREATE USER, GRANT, SET ROLE, SET SESSION AUTHORIZATION
• Query complexity limits — max query length, max tables, max JOINs, cost threshold
• Bulk operation protection — require_where enforces WHERE on UPDATE/DELETE
• Sensitive table lockdown — block non-DBA access to credential, audit, and secret tables
• Audit log tamper protection — prevent modification of audit/log tables

• 4 database protocols — PostgreSQL, MySQL, MSSQL TDS, and MongoDB wire protocols
• Protocol-native proxy — speaks each database's wire protocol natively, not JDBC/ODBC wrapping
• Zero external dependencies — standard library only, no CGO, single binary (~7.8MB)

Plus: role-based matching (!dba), command-type filtering, database/table wildcards, rate limiting per policy, row count limits, and masking rules.

• Column-level masking — per-column transformer rules with wildcard support
• PII auto-detection — 17 patterns, Luhn validation, TC Kimlik check
• 8 built-in transformers:

• Row count enforcement — configurable limits per policy
• Streaming — masking applied per-row, O(1) memory

• Structured JSON audit logs — every connection, command, and decision
• Three log levels — minimal, standard, verbose
• Async logging — buffered channel, never blocks the proxy pipeline
• SIEM webhook — batched HTTP POST to external systems
• Prometheus metrics — connections, commands, masking, pool stats, Go runtime
• Query fingerprinting — top query patterns, slow query logging
• Session replay — reconstruct full query timeline for any session
• Audit search & CSV export — filter by user, time, action, command type
• Log rotation + compaction — size-based rotation, age-based cleanup
• Health endpoints — /healthz, /ready, /livez with per-target backend health

• Auth passthrough — observes username without storing passwords
• LDAP/Active Directory — bind authentication with group resolution
• SSO/JWT — HMAC-SHA256 verification, claim extraction, expiry validation

• Approval workflows — hold critical commands for manual approve/deny with timeout
• Anomaly detection — behavioral baseline learning, unusual command/table/hour/frequency spike alerts
• Query cost estimation — heuristic scoring (0-100) based on JOINs, subqueries, missing WHERE
• Query rewriting — auto-LIMIT injection, WHERE clause enforcement for multi-tenant isolation
• Rate limiting — per-policy token bucket (configurable rate/burst per role)
• Connection pool — dedicated + shared modes, circuit breaker, warmup, wait histogram
• Certificate rotation — TLS cert reload without restart
• Data classification — 5 sensitivity levels, 17 rules, confidence scoring
• Plugin system — custom transformers, audit writers, auth providers
• Web dashboard — embedded real-time UI at /ui with auto-refresh + interactive test runner at /ui/test

go build -o argus ./cmd/argus/
# Or with Makefile
make build

Create argus.json:

{
  "server": {
    "listeners": [
      {"address": ":15432", "protocol": "postgresql"}
    ]
  },
  "targets": [
    {
      "name": "my-postgres",
      "protocol": "postgresql",
      "host": "localhost",
      "port": 5432
    }
  ],
  "routing": {
    "default_target": "my-postgres"
  },
  "policy": {
    "files": ["policies/waf.json"],
    "reload_interval": "5s"
  },
  "audit": {
    "level": "verbose",
    "outputs": [{"type": "stdout"}],
    "pii_auto_detect": true
  },
  "metrics": {
    "enabled": true,
    "address": ":9091"
  }
}

./argus -config argus.json

Point your application to Argus instead of the database:

# Before: direct to database
psql -h localhost -p 5432 -U myuser mydb

# After: through Argus
psql -h localhost -p 15432 -U myuser mydb

No application code changes required. Same protocol, same tools.

# Start all services
make docker-up

# Services:
#   PostgreSQL direct → localhost:35432
#   MySQL direct      → localhost:33306
#   MSSQL direct      → localhost:31433
#   Argus PG proxy    → localhost:30100
#   Argus MySQL proxy → localhost:30101
#   Argus MSSQL proxy → localhost:30102
#   Admin/Metrics     → localhost:30200

# Connect via Argus proxy
psql -h localhost -p 30100 -U argus_test -d testdb
mysql -h 127.0.0.1 -P 30101 -u argus_test -pargus_pass testdb

# Run E2E tests
make e2e

# Dashboard
open http://localhost:30200/ui

{
  "name": "waf-sqli-detection",
  "match": {},
  "condition": { "sql_injection": true },
  "action": "block",
  "reason": "SQL injection pattern detected"
}

Detects: OR 1=1, UNION SELECT, ; DROP TABLE, SLEEP(5), xp_cmdshell, ' OR '--, CHAR(68,82,79,80), INTO OUTFILE, LOAD_FILE(), WAITFOR DELAY, BENCHMARK().

{
  "name": "waf-require-where",
  "match": { "commands": ["DELETE", "UPDATE"] },
  "condition": { "require_where": true },
  "action": "block",
  "reason": "WHERE clause required for write operations"
}

{
  "name": "waf-block-schema-scan",
  "match": { "roles": ["!dba"] },
  "condition": {
    "sql_regex": ["(?i)information_schema\\.", "(?i)pg_catalog\\.", "(?i)sys\\."]
  },
  "action": "block",
  "reason": "Schema metadata access restricted to DBA"
}

{
  "name": "waf-max-query-length",
  "match": { "roles": ["!dba"] },
  "condition": { "max_query_length": 8192 },
  "action": "block",
  "reason": "Query exceeds 8KB — possible injection payload"
}

{
  "name": "waf-max-joins",
  "match": { "roles": ["!dba"] },
  "condition": { "max_joins": 8 },
  "action": "block",
  "reason": "Too many JOINs — possible resource exhaustion"
}

{
  "name": "waf-protect-credentials",
  "match": {
    "roles": ["!dba"],
    "tables": ["credentials", "passwords", "secrets", "api_keys"]
  },
  "action": "block",
  "reason": "Access to credential tables requires DBA role"
}

{
  "name": "waf-block-system-commands",
  "match": { "roles": ["!dba"] },
  "condition": {
    "sql_regex": [
      "(?i)xp_cmdshell", "(?i)INTO\\s+OUTFILE", "(?i)LOAD_FILE\\s*\\(",
      "(?i)LOAD\\s+DATA\\s+INFILE", "(?i)pg_read_file", "(?i)lo_export"
    ]
  },
  "action": "block",
  "reason": "System-level operations are prohibited"
}

{
  "name": "mask-pii-for-support",
  "match": { "roles": ["support"], "commands": ["SELECT"] },
  "masking": [
    {"column": "email", "transformer": "partial_email"},
    {"column": "phone", "transformer": "partial_phone"},
    {"column": "tc_kimlik", "transformer": "redact"},
    {"column": "card_number", "transformer": "partial_card"},
    {"column": "salary", "transformer": "redact"},
    {"column": "password_hash", "transformer": "redact"},
    {"column": "date_of_birth", "transformer": "redact"}
  ]
}

{
  "name": "contractor-rate-limit",
  "match": { "roles": ["contractor"] },
  "rate_limit": { "rate": 5, "burst": 10 }
}

{
  "name": "contractor-office-hours",
  "match": { "roles": ["contractor"] },
  "condition": {
    "work_hours": "08:00-19:00",
    "work_days": ["monday", "tuesday", "wednesday", "thursday", "friday"]
  },
  "action": "block",
  "reason": "Contractor access outside business hours"
}

{
  "name": "production-ip-restriction",
  "match": { "databases": ["production", "prod_*"] },
  "condition": {
    "source_ip_not_in": ["10.0.0.0/8", "172.16.0.0/12", "192.168.0.0/16"]
  },
  "action": "block",
  "reason": "Production access restricted to internal network"
}

A comprehensive WAF policy with 30+ rules is included at configs/policies/waf.json. It covers all the above plus audit log tamper protection, privilege escalation blocking, data exfiltration limits, and role-specific masking for 8 predefined roles.

All config values can be overridden via ARGUS_ prefixed environment variables:

ARGUS_AUDIT_LEVEL=verbose
ARGUS_METRICS_ADDRESS=:8080
ARGUS_POOL_MAX_CONNECTIONS_PER_TARGET=200
ARGUS_SESSION_IDLE_TIMEOUT=1h
ARGUS_TARGETS_0_HOST=db-prod.internal

Use $ENV{VAR} syntax in config for secrets:

{
  "host": "$ENV{DB_HOST}",
  "port": 5432
}

Three built-in policy profiles:

argus/
├── cmd/argus/              # Binary entry point, signal handling
├── internal/
│   ├── core/               # Listener, TLS, router, pipeline, approval workflow
│   ├── protocol/
│   │   ├── handler.go      # ProtocolHandler interface
│   │   ├── pg/             # PostgreSQL (Simple + Extended + COPY + SSL)
│   │   ├── mysql/          # MySQL (COM_QUERY, prepared statements, masking)
│   │   ├── mssql/          # MSSQL TDS (Pre-Login, Login7, SQL Batch, masking)
│   │   └── mongodb/        # MongoDB (OP_MSG, BSON command extraction)
│   ├── inspection/         # Tokenizer, classifier, fingerprint, anomaly, cost, splitter
│   ├── policy/             # Engine, matcher (15 conditions), WAF rules, decision cache
│   ├── masking/            # Streaming pipeline, 8 transformers, PII auto-detection
│   ├── ratelimit/          # Token bucket rate limiter
│   ├── session/            # Lifecycle, identity, timeout, tagging, concurrency
│   ├── pool/               # Dedicated + shared pool, circuit breaker, histogram, health
│   ├── audit/              # Logger, rotation, webhook, recorder, search, replay, compaction
│   ├── admin/              # 26 REST endpoints + WebSocket, auth middleware, dashboard UI
│   ├── auth/               # LDAP (BER encoding, group resolution) + SSO (JWT/HMAC-SHA256)
│   ├── classify/           # Data classification engine (5 levels, 17 rules)
│   ├── cluster/            # Multi-instance shared session store
│   ├── config/             # Loading, validation, env overrides
│   ├── metrics/            # Counters, query latency histogram
│   ├── plugin/             # Plugin registry (transformer, audit writer, auth provider)
│   └── gateway/            # SQL Gateway HTTP API, query executor, allowlist, approval
├── configs/
│   ├── argus-multidb.json  # Multi-database Docker config
│   └── policies/
│       ├── default.json    # Minimal policy (8 rules)
│       ├── production.json # Production policy (13 rules)
│       └── waf.json        # Full WAF policy (30+ rules)
└── scripts/                # E2E test scripts

Client Request
  → Protocol Decode (PG/MySQL/MSSQL/MongoDB)
  → SQL Inspection (tokenize, classify, risk score, fingerprint)
  → Cost Estimation (0-100 heuristic)
  → Policy Evaluation (15 conditions, role/command/table match, cache)
    → SQLi Detection (tautology, UNION, stacked, blind, encoding)
    → Rate Limit Check (token bucket per policy)
    → Anomaly Detection (baseline + frequency spike)
  → Decision:
    ├── BLOCK → return error to client, audit log
    ├── ALLOW → forward to backend
    │   → Query Rewrite (auto-LIMIT, WHERE injection)
    │   → Forward Results (streaming)
    │     → Masking Pipeline (explicit rules + PII auto-detect)
    │     → Row Limit Enforcement
    │   → Latency Measurement → Slow Query Check
    │   → Audit Log + Metrics + Live Broadcast
    └── APPROVAL → hold for manual approve/deny

1. Invisible to applications — same protocol, same tools, only connection target changes
2. Streaming-first — results processed per-row, never buffered entirely
3. Policy-driven — every decision comes from the policy engine, no hardcoded rules
4. Defense in depth — SQLi detection + risk scoring + cost limits + rate limiting + anomaly detection
5. Observable — every connection, command, and decision is logged and measurable

• PostgreSQL Simple Query + Extended Query + COPY + SSL
• MySQL wire protocol (handshake, COM_QUERY, prepared statements)
• Auth passthrough mode
• SQL inspection (tokenizer, classifier, risk scoring)
• Policy engine (role, command, time, IP rules)
• Streaming result masking (8 transformers)
• Async audit logging (JSON, file/stdout)
• Connection pooling with health checks
• TLS support (client + backend)
• Prometheus metrics & health endpoints
• Configuration with env overrides

• Admin REST API (26 endpoints + WebSocket)
• SQL literal sanitization in audit logs
• SIEM webhook export (batched HTTP POST)
• Audit log file rotation + compaction
• PII auto-detection (17 patterns, Luhn, TC Kimlik)
• Graceful shutdown with connection draining
• GitHub Actions CI/CD
• Kubernetes readiness/liveness probes

• MSSQL TDS protocol (codec, Login7, SQL Batch, COLMETADATA masking)
• Approval workflows (hold/approve/deny/timeout)
• Live session monitoring (WebSocket)
• Rate limiting per user/role (token bucket)
• Anomaly detection (baseline + frequency spike)
• Query fingerprinting + cost estimation
• Audit search, session replay, top fingerprints
• Policy dry-run, inheritance, validator
• Connection pool circuit breaker + warmup
• Certificate rotation without restart
• LDAP authentication with group resolution
• SSO/JWT authentication (HMAC-SHA256)

• MongoDB wire protocol (OP_MSG, BSON command extraction)
• Web dashboard UI + interactive test runner
• Plugin system (custom transformers, audit writers)
• Data classification engine (5 sensitivity levels, 17 rules)
• SQL injection detection (tautology, UNION, stacked, blind, encoding, system commands)
• Schema enumeration blocking
• System command blocking (xp_cmdshell, OUTFILE, LOAD_FILE)
• Privilege escalation detection
• Query complexity limits (length, tables, JOINs, cost)
• WHERE clause enforcement
• Sensitive table lockdown
• Comprehensive WAF policy (30+ rules, 8 roles)
• Oracle TNS protocol support

go test ./... -count=1          # Run all tests
go test ./... -v                # Verbose output
make test-cover                 # HTML coverage report
bash scripts/e2e-realworld.sh   # Real-world E2E (45 tests)
bash scripts/e2e-extra-scenarios.sh  # Extra scenarios (63 tests)

Current: 1718 unit tests, 99.4% coverage (22 packages).

Argus Panoptes (Argos Panoptes) — the all-seeing giant of Greek mythology. He had a hundred eyes and never slept. He sees everything.

MIT

ECOSTACK TECHNOLOGY OU