Inspect SCTP traffic and M3UA payloads in minutes.
SCTP Lens is a desktop-first network analysis tool for engineers who need to quickly quantify SCTP traffic and inspect M3UA-related packets inside PCAP files. It helps telecom, signaling, and network operations teams move from raw captures to actionable findings without writing scripts or manually hunting through packet data.
Telecom NOC Engineer Amina, 34 - Amina investigates signaling issues on live incidents and receives PCAPs from field engineers. She needs a fast way to confirm whether SCTP and M3UA traffic are present before escalating to protocol specialists.
Network Analyst Bruno, 41 - Bruno supports enterprise backbones and often receives large PCAPs from packet brokers or SPAN ports. He prefers tools that are faster than scripting but more focused than a full packet suite for quick triage.
Solutions Architect Layla, 29 - Layla works with customer-facing escalations and needs repeatable analysis artifacts. She values a lightweight tool that can be shared across teams without teaching everyone Python or Scapy.
Amina receives a PCAP from a carrier incident and needs to know quickly whether signaling traffic is present. Instead of opening a notebook and running Python scripts with Scapy and PyShark, she drops the file into SCTP Lens and immediately sees total packets, SCTP counts, and whether M3UA packets exist.
She clicks the M3UA filter, inspects the first matching packet layers, and copies a compact report into the incident ticket. What used to take several minutes of setup and manual scripting now takes less than a minute, letting her escalate with confidence and keep the network team focused on resolution.
For the business, that speed translates into more repeat usage, faster incident triage, and less dependence on ad hoc scripts that vary by engineer. The tool becomes the default first stop for SCTP investigations and a shared workflow across operations, support, and solution teams.
Team & resourcing - Small team - 2 engineers, 1 designer, part-time PM, and QA shared across release.
Paste this into Cursor, Bolt, Lovable, or v0 to start building.
Build a desktop-first network analysis app called SCTP Lens for inspecting PCAP files, focused on fast SCTP and M3UA triage. Core product: Users import local .pcap and .pcapng files, the app streams through the capture, shows total packet count and SCTP packet count, lets users apply preset filters for SCTP and M3UA, and inspect packet layers for the first matching packet. The app should be local-first, fast, and safe for sensitive telecom/network data. Primary screens and flows: 1. Import screen with drag-and-drop, file picker, recent files, file validation, and privacy note. 2. Analysis dashboard with summary cards for total packets, SCTP packets, match count, progress state, and a simple protocol breakdown view. 3. Filter panel with preset filters plus a custom display-filter input with syntax validation. 4. Packet inspector showing layer hierarchy and key field values for the selected or first matching packet. 5. Export modal for CSV, JSON, and plain-text summary reports with optional anonymization. 6. Settings screen for local preferences, recent-files behavior, and anonymization defaults. Data model: CaptureFile id, name, path, sizeBytes, importedAt, fileType, status, errorMessage AnalysisResult id, captureFileId, totalPackets, sctpPackets, m3uaPackets, durationMs, createdAt FilterPreset id, name, expression, description, matchCount PacketSummary id, analysisResultId, index, timestamp, layers, src, dst, protocol, sizeBytes ExportJob id, analysisResultId, format, anonymize, createdAt, status, outputPath UserSetting key, value, updatedAt Technical approach: Use Electron + React + TypeScript for the UI, with a Node.js background worker or Rust sidecar for streaming parsing to keep the UI responsive. Use tshark or a well-tested packet parsing library for protocol decoding, and SQLite for local metadata caching and recent files. Add a small analytics layer for local event tracking only, with no packet payloads sent to the server. Requirements: Implement drag-and-drop import, streaming progress, counts, filter application, packet layer viewer, export generation, anonymization, error handling, and keyboard-accessible UI. Keep the first usable summary visible within 10 seconds for a 500 MB capture on a typical laptop. Include accessible colors, screen-reader labels, and responsive tables. Build with sensible defaults and mock fixture PCAP data for development.
python -m venv venv source venv/bin/activate # على ويندوز: venv\Scripts\activate pip install scapy pyshark from scapy.all import PcapReader, SCTP total = sctp_count = 0 with PcapReader("capture.pcap") as pcap: for pkt in pcap: total += 1 if SCTP in pkt: sctp_count += 1 print(f"إجمالي الحزم: {total}") print(f"حزم SCTP: {sctp_count}") import pyshark cap = pyshark.FileCapture("capture.pcap", display_filter="m3ua") for pkt in cap: print(pkt.layers) break cap.close()
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