Automating Attack Surface Reconnaissance: Async Python & Streaming LLM Synthesis
SentinelScan couples non-blocking Python asyncio and aiohttp probes with Server-Sent Events to aggregate 120+ DNS, TLS, and port telemetry vectors in under 18 seconds. Real-time streaming LLM synthesis maps raw network responses to OWASP Top 10 vulnerabilities, persisting finalized security audits into Supabase PostgreSQL.
Traditional perimeter reconnaissance tools suffer from a fundamental bottleneck: synchronous network probes crawl through targets sequentially, leaving security analysts buried under mountains of fragmented raw port dumps, certificate logs, and HTTP header output.
When engineering SentinelScan, our goal was to bridge high-throughput asynchronous networking with real-time generative data synthesis. We built a custom Python reconnaissance backend leveraging asyncio and aiohttp to fire over a hundred concurrent DNS checks, non-blocking TCP socket validations, and heuristic sensitive endpoint probes simultaneously.
Rather than forcing users to wait for a monolithic scan report, the backend streams synthesized findings to a Next.js 14 frontend using Server-Sent Events (SSE). The raw network telemetry is contextualized on the fly against OWASP Top 10 classifications, delivering an executive-ready risk report in under 20 seconds.
All telemetry and finalized audits are persisted in Supabase PostgreSQL, creating permanent, shareable incident audit links without requiring intensive re-scans.
Connection pooling and DNS resolution throttling prevent edge firewalls from identifying the scan probe as an aggressive distributed denial-of-service attempt. As asynchronous workers receive socket responses, telemetry vectors are queued in memory and fed into a streaming LLM parsing prompt, generating prioritized remediation guides before network sockets are even closed.
| Audit Phase | Core Technology | Execution Time | Probe Concurrency | Primary Output |
|---|---|---|---|---|
| DNS & Subdomain Enumeration | Python aiodns & asyncio | 2.4 seconds | 100 concurrent lookups | CNAME chains, SPF/DMARC records, wildcard resolution |
| TLS & Certificate Auditing | OpenSSL & asyncio TLS socket | 1.8 seconds | 40 endpoint handshakes | Cipher suite strength, expiry dates, SAN discovery |
| Heuristic HTTP Probing | aiohttp with connection pooling | 6.2 seconds | 120 asynchronous requests | Security headers (CSP, HSTS), exposed endpoints, tech stack |
| OWASP Risk Synthesis | Streaming Server-Sent Events (SSE) | 7.5 seconds | Real-time token streaming | Executive risk matrix, CVSS scoring, remediation steps |
Q1:How does SentinelScan achieve comprehensive domain reconnaissance in under 20 seconds?
By utilizing Python asyncio event loop and aiohttp non-blocking connection pools, SentinelScan initiates over a hundred DNS, port, certificate, and HTTP header inspections concurrently rather than sequentially, eliminating network I/O blocking.
Q2:How are raw port and header outputs converted into OWASP vulnerability reports?
As probes resolve, telemetry vectors are normalized and streamed into an LLM analysis pipeline. The model cross-references exposed headers, outdated cipher suites, and misconfigured DNS records against OWASP Top 10 classifications, streaming markdown recommendations via Server-Sent Events.
Q3:Are scan findings and historical audits stored securely?
Yes. All audit outputs are persisted in Supabase PostgreSQL protected by Row Level Security. Audit URLs can be shared as immutable report snapshots, eliminating the need to re-scan targets and risk triggering target rate limiters.