CyberCode Academy episodes:

• November 14, 2025Course 6 - Network Traffic Analysis for Incident Response | Episode 7: Network Data Analysis Toolkit: Tools, Techniques and Threat Signature

  In this lesson, you’ll learn about: The complete toolkit and techniques for analyzing network traffic using Connection Analysis, Statistical Analysis, and Event-Based (signature-focused) Analysis. 1. Data Analysis Toolkit General-Purpose Tools These are foundational command-line utilities used to search, filter, and reshape data:

  • grep → pattern searching
  • awk → field extraction and manipulation
  • cut → selecting specific columns
    Used together, they form powerful pipelines for rapid, custom analysis.

  Scripting Languages Python

  • Most important language for packet analysis.
  • Scapy allows:
    • Parsing PCAPs
    • Inspecting packet structure
    • Accessing fields (IP, ports)
    • Filtering traffic (e.g., HTTP GET requests)
    • Deobfuscating malware traffic
      • Example: Extracting useful strings from compressed Ghostrat C2 payloads.

  R

  • Useful for statistical modeling and clustering of network data.

  Specialized Tools

  • Netstat → enumerates active connections
  • Silk → large-scale flow analysis (CERT tool)
  • Yara → rule-based threat matching (binary/text patterns)
  • Snort → signature-based intrusion detection

  2. The Three Core Data Analysis Techniques A. Connection Analysis Purpose: High-level visibility into which systems are connecting to which. Ideal for:

  • Detecting unauthorized servers or suspicious programs
  • Spotting lateral movement (e.g., odd SSH usage)
  • Identifying database misuse
  • Ensuring compliance across security zones

  Primary Tool: Netstat

  • Shows all active connections + states
    (LISTENING, ESTABLISHED, TIME_WAIT, etc.)

  Example Uses:

  • Spotting malware opening a hidden port
  • Identifying unauthorized remote access
  • Finding systems connecting to suspicious IPs

  B. Statistical Analysis A macro-level technique designed to spot deviations from normal behavior. Techniques: 1. Clustering Group similar traffic together to identify families or variants.

  • Demonstrated by clustering Ghostrat variants through similarities in their C2 protocol.

  2. Stack Counting Sort traffic by count of activity on:

  • Destination ports
  • Host connections
  • Packet types

  Used to find anomalies:

  • Single visits to rare ports (2266, 3333)
  • Unexpected FTP traffic (port 21)

  3. Wireshark Statistics Using built-in metrics:

  • Packet lengths (large packets → possible exfiltration or malware downloads)
  • Endpoints
  • Protocol hierarchy

  Specialized Tool: Silk

  • Designed for massive enterprise networks
  • Supports both command line & Python (Pysilk)
  • Ideal for flow-level analysis, anomaly detection, and trend discovery.

  C. Event-Based Analysis (Signature Focused) A micro-level technique used to identify known threats via rules and signatures. 1. Yara Signatures

  • Rules match known binary or text patterns.
  • Example uses:
    • Detecting Ghostrat via identifying strings like "lurk zero" or "v2010"
    • Multi-string matching to detect multi-stage malware
    • Matching malicious hostnames or indicators

  Used for:

  • Malware classification
  • Reverse-engineering support
  • Deep content inspection

  2. Snort Rules Snort provides concise detection logic for network traffic. Rule Structure Includes:

  • Action (alert, log)
  • Protocol (TCP/UDP)
  • Source/destination + ports
  • Options (content matches, flags, byte tests)

  Examples Provided:

  • Detecting Nmap Xmas scans (FIN + PUSH + URG flags)
  • Detecting SMTP credential leakage (plaintext “authentication succeeded” over port 25)

  Snort highlights:

  • Excellent for IDS/IPS
  • Simple to write and test
  • Widely used in enterprise SOCs

  3. Practical Demonstrations A. Scapy + Yara Workflow shown:

  1. Use Scapy to load and parse PCAP
  2. Extract payloads
  3. Feed payloads to Yara
  4. Detect Ghostrat, multi-stage malware, or other known threats

  This combination gives both:

  • PCAP-level filtering
  • Payload-level signature inspection

  B. Scapy + Snort Two key demonstrations: 1. Automatic Snort Rule Generation

  • Tools like packet_to_snort.py generate draft Snort rules from suspicious packets.

  2. Packet Manipulation for Rule Testing

  • Scapy is used to modify packet captures (e.g., IP address changes)
  • Allows testing Snort signatures under different conditions
  • Helps ensure rules are stable and do not create false positives

  Summary: Combined Defense Strategy Effective network security requires all three techniques working together:TechniquePurposeCatchable ThreatsConnection AnalysisHigh-level visibilityUnauthorized access, lateral movementStatistical AnalysisDetect anomalies and unknown threatsData exfiltration, malware downloadsEvent-Based AnalysisDetect known, signature-based attacksRATs, worms, exploit kits
  
  A mature SOC or network defense operation relies on all three to defend against:

  • Known threats
  • Zero-days
  • Misconfigurations
  • Insider activity
  • Advanced malware campaigns

  
  
  You can listen and download our episodes for free on more than 10 different platforms:
  https://linktr.ee/cybercode_academy

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• November 14, 2025Course 6 - Network Traffic Analysis for Incident Response | Episode 6: Investigating RATs, Worms, Fileless, and Multi-Stage Malware Variants

  In this lesson, you’ll learn about: Advanced Malware Traffic Analysis — how to detect, decode, and investigate RATs, fileless exploits, worms, and multi-stage infections using real network captures. 1. Remote Access Trojans (RATs) WSH RAT

  • Uses plaintext beaconing for C2 → very easy to identify.
  • Key data exfiltrated in HTTP requests:
    • Unique device ID
    • Computer name
    • Username (“admin”)
    • RAT version (often hidden in the User-Agent field)

  NJRAT

  • Shows extensive data exfiltration:
    • Windows XP build info
    • CPU type (Intel Core i7)
    • Username (“Laura”)
  • Contains custom data blocks:
    • Likely a proprietary C2 format
    • Example: 4-byte value representing payload length (e.g., 16 bytes)

  2. Fileless Malware (Angler Exploit Kit) Detection

  • Traffic contains obfuscated script + random literature quotes
    → used to evade heuristic scanners.
  • Streams show signs of XOR encoding.

  Extraction & Deobfuscation Using Network Miner:

  • Extracted files include:
    • A Shockwave Flash file (.swf)
    • Three large application/octet-stream files
  • XOR decoding reveals:
    • Shellcode +
    • Windows executable (DLL)

  Purpose

  • Shellcode injects the malicious DLL into a running process (e.g., Internet Explorer).
  • Because nothing is written to disk → bypasses traditional antivirus, making network analysis essential.

  3. Network Worm Behavior WannaCry (SMB Worm)

  • Exploits SMB on port 445 using Eternal-family vulnerabilities.
  • Behavior includes:
    • High-volume IP scanning for vulnerable systems
    • SMB exploitation setup (NOP sled → shellcode → payload transfer)

  MyDoom (SMTP Mailer Worm)

  • Attempts spreading via SMTP (port 25).
  • Tries to send spoofed “delivery failed” emails with malicious attachments:
    • e.g., mail.zip → actually .exe hidden using spaces + triple dots.
  • In the demonstration, all spreading attempts were blocked, showing modern protections in action.

  4. Multi-Stage Malware Infection Tracking Stage 1 — Initial Compromise

  • Suspicious HTTP request containing Base64 ID.
    • Decodes to an email address (e.g., Reginald/Reggie Cage) → privacy red flag.
  • Download of a malicious Microsoft Word file.

  Stage 2 — Downloader Activity

  • Traffic to known malware-downloader domains (e.g., Pony botnet infrastructure).
  • Malware sends detailed victim metadata:
    • GUID
    • OS build number
    • IP address
    • Hardware info

  Stage 3 — Command & Control

  • Multiple C2 messages observed:
    • Some Base64-encoded
    • Many encrypted → indicating later-stage payloads
  • Strong evidence that:
    • Word file → downloader (Pony) → secondary malware → possible tertiary stage

  5. Key Techniques Demonstrated

  • Identifying IOCs in network captures
  • Detecting plaintext, encoded, and encrypted C2 protocols
  • Carving files and reconstructing injected payloads
  • Analyzing worm scanning patterns
  • Tracking infection chains across multiple malicious components

  
  
  You can listen and download our episodes for free on more than 10 different platforms:
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• November 14, 2025Course 6 - Network Traffic Analysis for Incident Response | Episode 5: Scanning, Covert Data Exfiltration, DDoS Attacks and IoT Exploitation

  In this lesson, you’ll learn about: Network Threat Analysis — understanding how common attacks and advanced malware appear in real traffic captures, and how to extract intelligence from them. Part 1 — Analysis of Common Network Threats 1. Network Scanning Techniques Attackers scan networks to discover targets, services, and vulnerabilities. Demonstrations cover several scanning styles: SYN / Half-Open Scan

  • Sends SYN packets without completing the handshake.
  • Target responses reveal open vs. closed ports.

  Full Connect Scan

  • Completes the full TCP three-way handshake.
  • More noticeable but highly accurate.

  Xmas Tree Scan

  • Uses abnormal TCP flags: FIN + PUSH + URG.
  • Leveraged to probe how systems respond to malformed packets.

  Zombie / Idle Scan

  • Uses an unwitting third-party host (“zombie”) to hide attacker identity.
  • Tracks incremental IP ID numbers to infer open ports.

  Network Worm Scanning (e.g., WannaCry)

  • Worms scan many IPs for a single vulnerable port, such as SMB 445.
  • High-volume, repetitive traffic is a key signature.

  2. Data Exfiltration (Covert Channels) Focus: understanding how attackers hide stolen data inside legitimate-appearing traffic. Covert SMB Channel

  • Data leaked one byte at a time inside SMB packets.
  • Requires:
    • Reviewing thousands of similar packets,
    • Extracting embedded data,
    • Base64 decoding,
    • Reversing the result,
    • Revealing hidden Morse code.

  ICMP Abuse

  • Attackers embed data into ICMP type fields, reconstructing files (e.g., a GIF).
  • Difficult to detect because ICMP is normally used for diagnostics, not data transfer.

  3. Distributed Denial of Service (DDoS) Attacks Explains why DDoS attacks remain common—cheap cloud resources, insecure IoT devices, accessible botnets. Volumetric SYN Flood

  • Floods a port (like HTTP 80) with incomplete handshakes.
  • Exhausts server connection capacity.

  HTTP Flood

  • Sends massive amounts of GET/POST requests.
  • Harder to distinguish from normal traffic.

  Amplification / Reflection Attacks

  • Small spoofed request → massive response to victim.
  • Examples:
    • Cargen protocol: 1-byte request → 748-byte response.
    • Memcache: tiny request → multi-megabyte responses from cached data.

  4. IoT Device Exploitation Demonstration focuses on how attackers compromise weak devices such as DVRs.

  • Many IoT devices use default credentials and insecure services like Telnet.
  • Attack flow typically involves:
    1. Logging in via Telnet.
    2. Attempting to download malware (e.g., Mirai ELF binary).
    3. When automated delivery (TFTP) fails → manually reconstructing binaries using echo.
    4. Device joins a botnet and starts scanning other victims.

  Part 2 — In-Depth Malware Case Studies 1. Remote Access Trojans (RATs)

  • Traffic begins with system information reporting from the infected host.
  • Followed by persistent command-and-control (C2) communication.

  2. Fileless Malware

  • Malware runs directly in memory, leaving minimal filesystem artifacts.
  • Often, network traffic is the only complete copy of the payload available.

  3. Network Worms

  • Automate scanning and propagation.
  • Look for specific open ports, then exploit and install themselves.

  4. Multi-Stage Malware

  • Downloader retrieves multiple malware families.
  • Identifying each stage helps determine full attack scope and remediation steps.
  • Network traffic often reveals multiple URLs, payloads, or C2 servers involved.

  
  
  You can listen and download our episodes for free on more than 10 different platforms:
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• November 14, 2025Course 6 - Network Traffic Analysis for Incident Response | Episode 4: Mapping, Decoding, and Decrypting Network Traffic Intelligence

  In this lesson, you’ll learn about: Intelligence Collection from Network Traffic Captures — focusing on anomalies, attacker behavior, and extracting actionable intelligence. 1. Network Mapping & Visualization

  • Humans struggle with long lists → visualizing traffic helps you feel the environment.
  • Tools like pcap viz generate maps at different OSI layers:

  Layer 3 (IP Addresses)

  • Shows which machines talk to each other.
  • Helps detect unusual communication paths.

  Layer 4 (TCP/UDP Ports)

  • Shows communication between applications.
  • Unusual ports (e.g., 900) may indicate custom or C2 protocols.

  2. Content Deobfuscation Attackers often hide traffic with simple encodings (not strong encryption).
  Goal → recover the original content, often a payload or second-stage executable. XOR Encoding

  • Common in malware traffic.
  • Repeated patterns in streams (especially when encoding zeros) reveal the key.
  • Example: fixed-length 4-byte key like MLVR.

  Base64 (B64)

  • Seen in C2 frameworks like Onion Duke.
  • Recognizable by:
    • A–Z, a–z, 0–9, “+”, “/”
    • Ends with “=” padding
  • Easy to decode using built-in libraries or online tools.

  3. Credential Capture from Insecure Protocols Focus: credentials leaking in plaintext protocols. Telnet & IMAP

  • Send usernames/passwords in clear text.
  • Easy to extract directly from the TCP stream.

  SMTP

  • Encodes credentials in Base64 → trivial to decode.
  • Python or online decoders reveal username + password.
  • Reinforces the need for TLS encryption.

  4. SSL/TLS Decryption in Wireshark Encrypted traffic looks like random “gibberish” unless you have the right keys. Using RSA Private Keys

  • If the RSA private key is available, Wireshark can decrypt sessions directly.

  Ephemeral Keys (ECDHE)

  • Cannot be decrypted using the server’s private key.
  • Must capture the session keys using a pre-master secret log file:
    • Often done by setting an SSL key log file environment variable in browsers.
  • Without that log, the sessions are not recoverable.

  5. Web Proxy Interception (Deep Packet Inspection) Enterprise method for inspecting encrypted HTTPS traffic. How it works

  • A corporate proxy (e.g., Burp Suite) intercepts connections:
    • Breaks the client → server TLS session.
    • Decrypts → inspects → re-encrypts all traffic.

  Requirements

  • Clients must install the proxy’s self-signed root certificate.
  • Needed to bypass controls like HSTS.

  Risks

  • Proxy becomes a single high-value target for attackers.
  • Raises privacy concerns, especially when employees do personal browsing (banking, etc.).

  
  
  You can listen and download our episodes for free on more than 10 different platforms:
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• November 14, 2025Course 6 - Network Traffic Analysis for Incident Response | Episode 3: Wireshark Alternatives: Network Miner, Terminal Shark, and CloudShark

  In this lesson, you’ll learn about:

  • Three powerful alternatives to Wireshark that expand your capabilities in network traffic analysis.
  • How to use Network Miner for passive intelligence, T-shark for automation, and CloudShark for collaborative, web-based analysis.
  • When and why each tool is more effective than Wireshark in specific scenarios.

  Network Miner — Passive Data Collection & File Extraction

  • Purpose: A passive network forensics tool excellent for extracting intelligence without actively interfering with traffic.

  Key Capabilities

  • Host Intelligence (Auto-Recon):
    • Automatically breaks traffic down by host.
    • Extracts IP/MAC, hostnames, OS fingerprints (e.g., Red Hat Linux), NIC vendor, open TCP ports, and even web server banners (e.g., Apache 2.0.40).
    • Provides a detailed, Nmap-like overview without performing any active scans.
  • Data Extraction (File Carving):
    • Automatically pulls files transmitted during the capture (images, documents, etc.).
    • Makes recovery of transferred files extremely easy.
  • Credential Extraction:
    • Effective at pulling credentials from clear-text protocols like:
      • SMTP (usernames and passwords when TLS is not used)
      • HTTP cookies (considered credentials because they allow authentication)
  • Traffic Review Tools:
    • Lists DNS queries for browsing activity.
    • Breaks HTTP and SMTP header fields into searchable tables for instant lookup (e.g., search by user agent).

  Terminal Shark (T-shark) — Command-Line Automation

  • Purpose: A command-line version of Wireshark designed for automation, scripting, and large-scale analysis.

  Key Capabilities

  • Same Power as Wireshark, but CLI-Based:
    • Uses the same filtering language as Wireshark (e.g., http.request, tcp.port == 80).
    • Ideal for environments without a GUI or for remote analysis over SSH.
  • Automation & Integration:
    • Perfect for batch processing, cron jobs, or running inside scripts.
    • Output can be piped into other tools for threat intel or blacklist checks.
  • Custom Output:
    • Extract specific fields only (e.g., HTTP hostnames, source IPs).
    • Reduces noise and makes threat hunting more efficient.
  • Simple Threat Detection:
    • Analysts can filter important fields and check them against malicious blocklists.
    • Enables lightweight, fast, automated detection workflows.

  CloudShark — Web-Based Visualization & Collaboration

  • Purpose: A browser-based network analysis platform similar to Wireshark, designed for team collaboration.

  Key Capabilities

  • Collaborative Interface:
    • Apply filters just like in Wireshark.
    • Add comments/annotations directly to packets for team-based investigations.
  • Advanced Visualization Tools:
    • Traffic-over-time graph: Helps analysts zoom into sudden spikes or suspicious bursts.
    • Ladder diagrams: Show packet flow between hosts — extremely useful for understanding sequences like handshakes or attack chains.
    • Bytes-over-time visualization: Helps detect anomalies such as large outbound data spikes (e.g., from SQL injection exfiltration).
  • Interoperability:
    • Upload PCAPs to CloudShark for analysis.
    • Download them again (with or without comments) to continue work in Wireshark.
    • Works as a complementary tool rather than a replacement.

  Key Takeaways

  • Network Miner excels at passive forensics, credential discovery, and file extraction.
  • T-shark is ideal for automation, scripting, and environments without a GUI.
  • CloudShark shines in collaboration, visual analysis, and team-based investigations.

  Together, these tools form a specialized toolkit—like having precise surgical instruments instead of relying solely on Wireshark’s general-purpose capabilities.
  
  You can listen and download our episodes for free on more than 10 different platforms:
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• November 14, 2025Course 6 - Network Traffic Analysis for Incident Response | Episode 2: Wireshark Features and Comprehensive Protocol Dissection

  In this lesson, you’ll learn about:

  • Transitioning from theoretical networking concepts to hands-on traffic analysis.
  • Using Wireshark to capture, dissect, filter, and understand live network traffic.
  • Identifying how common protocols appear in real packet captures, including their structure and behavior.
  • Recognizing how different protocols handle communication, reliability, and security.

  Wireshark: Introduction & Core Features

  • What Wireshark Is:
    • A free, GUI-based network traffic analyzer (formerly Ethereal).
    • Supports live packet capture and loading .cap / .pcap files.
  • Key Features Covered:
    • Capture Management:
      • Start live captures with options like promiscuous mode.
      • Load and inspect previously saved capture files.
    • File Handling & Exporting:
      • Merge capture files (if timestamps align).
      • Import packets from hex dumps.
      • Export selected packets or full dissections in text, CSV, JSON, XML.
      • Export TLS session keys for decrypting certain encrypted traffic.
    • UI Navigation:
      • Color-coded packet list (e.g., green = TCP/HTTP, red = errors/retransmissions).
      • Three-pane layout: Packet list → Protocol dissection → Raw hex/ASCII.
    • Analysis Tools:
      • Display filters for precise inspection (e.g., tcp.port == 80).
      • Follow TCP/HTTP Stream to trace entire conversations.
      • Decode As to reinterpret traffic running on uncommon ports.

  Protocol Dissection: What You’ll See in Wireshark 1. IP (IPv4/IPv6)

  • View IP headers, including TTL (Time To Live) as hop count.
  • Look at IPv6 structures and tunneling protocols such as:
    • 6to4
    • 6in4
  • Learn how IPv6 packets travel across IPv4 networks.

  2. TCP (Transmission Control Protocol)

  • Understand reliability and session management.
  • Observe:
    • The 3-way handshake: SYN → SYN-ACK → ACK
    • Connection teardown: FIN/FIN-ACK or RST
    • Flags, sequence numbers, acknowledgments, and retransmissions.

  3. UDP (User Datagram Protocol)

  • Minimal, fast, connectionless protocol.
  • No handshake, no retransmission.
  • Used in scenarios requiring speed over reliability.

  4. ICMP (Internet Control Message Protocol)

  • Used for error reporting and diagnostic tools like:
    • Ping (Echo Request/Reply – Type 8/Type 0)
    • Traceroute
  • Note: While essential, ICMP must be carefully controlled on networks.

  5. ARP (Address Resolution Protocol)

  • Maps IP → MAC inside local networks.
  • Stateless nature allows ARP poisoning, a common man-in-the-middle technique.

  Higher-Level / Application Protocols in Wireshark 1. DNS (Domain Name System)

  • Seen mostly over UDP.
  • Analyze queries, recursion, multiple responses (A, MX, etc.).

  2. HTTP (Hypertext Transfer Protocol)

  • Review request lines, headers (User-Agent, Host, URI) and response codes.
  • HTTP is common in analysis due to high traffic volume.
  • Also widely monitored because attackers often misuse it for hidden communications.

  3. FTP (File Transfer Protocol)

  • A clear-text protocol:
    • Credentials and transfers visible in packet captures.
  • Highlights the need for secure alternatives (FTPS / SFTP).

  4. IRC (Internet Relay Chat)

  • Simple text-based protocol.
  • Multi-user channels make it useful for automation and remote coordination tools.

  5. SMTP (Simple Mail Transfer Protocol)

  • Clear-text protocol for sending emails.
  • Username/password often appear in Base64, easily decoded.
  • Typically secured using TLS.

  6. SSH (Secure Shell)

  • Encrypted remote terminal access.
  • Only early handshake is readable; session content is encrypted by design.
  • Demonstrates why encrypted protocols prevent content inspection.

  7. TFTP (Trivial File Transfer Protocol)

  • Runs over UDP.
  • Very simple; no authentication.
  • Traffic, including files, appears in clear text.

  Key Takeaways

  • You’ll gain practical experience by capturing, filtering, and interpreting traffic directly in Wireshark.
  • Observing how protocols appear “on the wire” builds intuition for normal vs. abnormal behavior.
  • This hands-on section prepares you for real-world network forensics, troubleshooting, and security analysis in an ethical academic environment.

  
  
  You can listen and download our episodes for free on more than 10 different platforms:
  https://linktr.ee/cybercode_academy

  ...more

  

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• November 14, 2025Course 6 - Network Traffic Analysis for Incident Response | Episode 1: Fundamentals of Networking: The OSI Model and Essential Protocols

  In this lesson, you’ll learn about:

  • The core networking concepts required before beginning any network traffic analysis.
  • The relationship between the OSI model, low-level protocols, and application-level protocols, and how they shape the behaviour of traffic you’ll examine in a tool like Wireshark.
  • How to recognize common protocol behaviours at a high level so you can later understand patterns, anomalies, and security-related findings during analysis.

  1. The OSI Model and the Network Stack (high-level foundation)

  • The OSI model divides networking functionality into structured layers.
  • Hardware-oriented layers:
    • Physical → bits on the wire
    • Data Link → frames within a local network
  • Software-oriented layers relevant for analysis:
    • Network (Layer 3) → packets, routing
    • Transport (Layer 4) → reliability, ports
    • Session / Presentation / Application (Layers 5–7) → how applications encode, manage, and interpret network data
  • Students should understand the distinctions between bits → frames → packets, because these appear in captures.

  2. Base Network Protocols (the building blocks)

  • IP (Internet Protocol – Layer 3):
    • Core packet-forwarding protocol for IPv4/IPv6.
    • Manages routing across networks.
  • TCP (Transmission Control Protocol):
    • Ensures reliable delivery: sequencing, acknowledgments, error checking, retransmission.
    • Manages connections using ports and a handshake mechanism.
  • UDP (User Datagram Protocol):
    • Connectionless and faster but offers no delivery guarantees.
    • Used when speed and low latency matter more than reliability.
  • ICMP (Internet Control Message Protocol):
    • Sends diagnostic and control messages.
    • Used by tools like ping and traceroute.

  3. Common Higher-Level Protocols & Security Wrappers (conceptual behaviour)ProtocolPurpose (High-Level)Security-Relevant Behaviours (Conceptual Only)ARPResolves IP → MAC within a LAN.Can be abused conceptually for redirecting traffic.DNSTranslates domain names to IP addresses.Commonly targeted for redirection or misdirection attacks.FTPTransfers files using ports 20/21.Weak configurations may allow unauthorized file movement.HTTP / HTTPSWeb communication.Frequently analysed due to large volume of traffic and vulnerabilities.IRCText-based group chat channels.Historically used in automation and remote coordination systems.SMTPSends email.High-volume traffic channel; relevant for filtering and monitoring.SNMPNetwork device management.Misconfigurations can lead to information disclosure.SSHSecure, encrypted remote terminal access.Important for secure administration.TFTPLightweight file transfer on port 69.Seen in simple or automated device configurations.TLSProvides authentication and encryption for other protocols.Masks traffic contents in both legitimate and illegitimate uses.
  
  Key Takeaways

  • Understanding how protocols behave at each OSI layer is essential for interpreting traffic captures.
  • Familiarity with the normal patterns of protocols (IP, TCP/UDP, DNS, TLS, etc.) helps analysts later identify unusual or suspicious activity.
  • This theoretical module prepares students for the practical phase using tools like Wireshark, where they will analyse real traffic captures in a controlled, educational setting.

  
  
  You can listen and download our episodes for free on more than 10 different platforms:
  https://linktr.ee/cybercode_academy

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• November 13, 2025Course 5 - Full Mobile Hacking | Episode 8: Technical Check for Mobile Indicators of Compromise using ADB and Command Line

  In this lesson, you’ll learn about:
  

  • Goal — verifying if an Android device is compromised (conceptual):
    • How investigators look for Indicators of Compromise (IoCs) on a device by inspecting network activity and running processes; emphasis on performing all checks only with explicit authorization and on isolated lab devices.
  • Network‑level indicators:
    • Look for unexpected outbound or long‑lived connections to remote IPs or uncommon ports (examples of suspicious patterns, not how‑to).
    • High‑risk signals include connections to unknown foreign IPs, repeated reconnect attempts, or traffic to ports commonly associated with remote shells/listeners.
    • Correlate network findings with timing (when the connection started) and with other telemetry (battery spikes, data usage) to prioritize investigation.
  • Process & runtime indicators:
    • Unusual processes or services running on the device (unexpected shells, daemons, or package names) are strong red flags.
    • Signs include processes that appear to be interactive shells, packages with strange or obfuscated names, or processes that persist after reboots.
    • Correlate process names with installed package lists and binary locations to determine provenance (signed store app vs. side‑loaded package).
  • Behavioral symptoms to watch for:
    • Sudden battery drain, unexplained data usage, spikes in CPU, or device sluggishness.
    • Unexpected prompts for permissions, new apps appearing without user consent, or developer options/USB debugging enabled unexpectedly.
  • Forensic collection & triage (high level):
    • Capture volatile telemetry (network connections, running processes, recent logs) and preserve evidence with careful documentation (timestamps, commands run, who authorized the collection).
    • Preserve a copy/snapshot of the device state (emulator/VM snapshot or filesystem image) before further analysis to avoid contaminating evidence.
    • Export logs and network captures to an isolated analyst workstation for deeper correlation and timeline building.
  • Correlation & investigation workflow (conceptual):
    • Cross‑reference suspicious outbound connections with running processes and installed packages to identify likely malicious artifacts.
    • Use process metadata (package name, signing certificate, install time) and network metadata (destination domain, ASN, geolocation) to assess intent and scope.
    • Prioritize containment (isolate device/network) if active exfiltration or ongoing C2 is suspected.
  • Containment & remediation guidance:
    • Isolate the device from networks (airplane mode / disconnect) and, where appropriate, block suspicious destinations at the network perimeter.
    • Preserve evidence, then follow a remediation plan: revoke credentials, wipe/restore from a known‑good image, reinstall OS from trusted media, and rotate any secrets that may have been exposed.
    • Report incidents per organizational policy and involve legal/compliance if sensitive data was involved.
  • Safe lab & teaching suggestions:
    • Demonstrate IoCs using emulators or instructor‑controlled devices in an isolated lab network; never create or deploy real malicious payloads.
    • Provide students with sanitized capture files and pre‑built scenarios so they can practice correlation and investigation without touching live systems.
  • Key takeaway:
    • Detecting device compromise relies on correlating suspicious network activity with anomalous processes and device behavior. Always investigate within legal/ethical bounds, preserve evidence, and prioritize containment before remediation.

  
  
  
  
  
  
  
  
  
  
  
  
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• November 13, 2025Course 5 - Full Mobile Hacking | Episode 7: Remote Windows Management and Android Geolocation Security Tutorials

  In this lesson, you’ll learn about:

  • Remote desktop from Android to Windows — legitimate use & risks (conceptual):
    • What remote desktop access enables: control a Windows desktop from an Android device for administration, support, or productivity (launch apps, browse files).
    • Legitimate configuration concerns: who should be allowed remote access, least‑privilege user selection, and the importance of strong authentication for remote sessions.
    • Security risks from exposed RDP‑like services: brute‑force, credential stuffing, and lateral movement if an attacker obtains access.
  • Secure deployment & hardening of remote desktop services:
    • Prefer VPN / zero‑trust tunnels rather than exposing remote desktop ports to the Internet.
    • Enforce multi‑factor authentication, strong passwords, account whitelisting, and limited session times.
    • Keep host OS patched, limit which users are permitted remote login, and log/monitor remote sessions for anomalies.
  • Social‑engineering data‑harvesting techniques — high‑level awareness (non‑actionable):
    • Why attackers use phishing/cloned sites: to trick users into granting permissions (OAuth consent, file access) or revealing device/browser metadata.
    • Types of data commonly exposed if a user is tricked: browser/user‑agent info, OS details, and location metadata (when permitted by the user).
    • Emphasize: these are high‑level attack categories to defend against, not to implement. No operational steps are provided.
  • Detection signals & forensic indicators for defenders:
    • Unexpected OAuth consent grants or newly‑authorized third‑party apps in user accounts.
    • Unusual outbound connections after a user clicks a link, sudden telemetry reporting (new IPs, device fingerprints), and spikes in geolocation requests.
    • Alerts for new remote sessions from unknown devices, unusual login times, or new client software installs.
    • Retain logs: authorization events, web server access logs, and device telemetry to reconstruct incidents.
  • Mitigations & user education:
    • Train users to verify OAuth consent screens and only grant permissions to known, trusted apps.
    • Disable or tightly control third‑party app authorizations in enterprise accounts; enforce allow‑lists.
    • Use device/endpoint protection (mobile/desktop EDR), network filters, and DNS/TLS inspection to block known phishing/C2 domains.
    • Apply principle of least privilege for remote access and require MFA for all remote desktop logins.
  • Legal, ethical & operational guidance for teaching:
    • Never test phishing or live social‑engineering techniques on real users without explicit, documented consent and institutional approval.
    • Use simulated or injected telemetry in closed lab environments for demonstrations.
    • Follow institutional policies and applicable laws when discussing or demonstrating attacks.
  • Safe classroom exercises & demos:
    • Controlled remote‑access demo: show a remote desktop session using an instructor‑controlled device on an isolated lab network; focus on configuration and logs.
    • OAuth consent analysis: students review benign consent screens and identify risky permission requests.
    • Detection lab: simulate benign telemetry in an isolated environment and have students create detection rules (alerts on new consent grants, unusual geolocation requests).
    • Tabletop IR: run a scenario where a user reports a suspicious consent prompt; students draft containment, evidence collection, and notification steps.
  • Further reading & resources:
    • Enterprise remote‑access hardening guides, OAuth security best practices, phishing awareness curricula, and incident‑response playbooks for handling compromised accounts/devices.

  
  
  You can listen and download our episodes for free on more than 10 different platforms:
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• November 13, 2025Course 5 - Full Mobile Hacking | Episode 6: Ghost Framework: Exploiting Android Devices via Debug Bridge (ADB) and Shodan Reconnaissance

  In this lesson, you’ll learn about:

  • Threat overview — device command‑and‑control via debug interfaces (conceptual):
    • What attacker frameworks that target device debug services aim to achieve (remote control, data exfiltration, persistence).
    • Why debugging interfaces (like Android’s debug bridge) are attractive: powerful access surface, rich device APIs, and potential for high impact if misused.
  • High‑level framework lifecycle (non‑actionable):
    • General stages attackers use conceptually: discovery, access, establish control, maintain access, and post‑compromise actions — explained as theory only, not how‑to.
    • Differences between legitimate management tools (MDM, device management consoles) and malicious C2 frameworks (abuse of management channels).
  • Discovery & reconnaissance (defender mindset):
    • Why exposed management/debug ports on the Internet increase risk and how defenders should treat any externally accessible debug interfaces as critical vulnerabilities.
    • Risk of internet‑facing debug endpoints: automated scanners and crawlers can find exposed services; businesses must not expose debug interfaces publicly.
  • Common post‑compromise capabilities (conceptual):
    • Inventory collection (device metadata), remote process management, filesystem access, sensor/media capture, credential/access checks, and file exfiltration — discussed as categories of impact, not recipes.
    • Emphasize real harms (privacy invasion, surveillance, lateral movement, persistent access).
  • Indicators of compromise (IoCs) & telemetry to monitor:
    • Unexpected remote connections originating from devices to unknown domains or unusual destinations.
    • New or unsigned apps installed, unusual app package names, or apps requesting broad permissions suddenly.
    • Sudden battery drain, spikes in data usage, or unusual CPU load correlated with network activity.
    • Presence of unknown services or long‑running processes, unexpected open ports, and unusual log entries in system logs/logcat.
    • Changes to device configuration (developer mode enabled, USB debugging toggled) without authorized admin action.
  • Forensic artifacts & evidence collection (safe practices):
    • What to collect in an investigation: device inventory, installed package lists and manifests, network connection logs, app data directory listings, and system logs — always under legal authority.
    • Prefer read‑only evidence collection; document chain‑of‑custody; snapshot/emulator capture for lab analysis.
    • Use vendor and platform logging (MDM/Audit logs) to correlate events.
  • Defensive controls & hardening (practical guidance):
    • Disable debug/management interfaces on production devices; permit them only in controlled labs.
    • Block or firewall management ports at network edge — never expose device debug ports to the public Internet.
    • Enforce device enrollment and use MDM to control app installation, restrict sideloading, and enforce app signing policies.
    • Monitor device telemetry and set alerts on anomalous network or power usage patterns.
    • Enforce strong device access controls: screen locks, disk encryption, secure boot where supported, and per‑app permission audits.
    • Keep devices patched and apply vendor security updates promptly.
  • Operational policies & governance:
    • Mandate least privilege for admin keys and rotate management credentials/keys.
    • Use network segmentation for device management systems and require VPN/zero‑trust access to management consoles.
    • Maintain an incident response plan specific to mobile device compromise — include isolation, forensic capture, remediation, and notification steps.
  • Safe lab & teaching recommendations:
    • Teach using emulators and isolated networks only; never scan or connect to internet hosts you don’t own or have explicit permission to test.
    • Provide students with sanitized, instructor‑controlled sample devices/APKs for demonstrations.
    • Use logging/proxy capture in closed labs so students can observe telemetry and detection without causing harm.
    • Require signed authorization for any hands‑on exercises; include ethics and legal briefings before labs.
  • Ethics, legality & disclosure:
    • Unauthorized access is illegal and unethical. Academic settings must enforce rules, require consent, and document authorization for any live testing.
    • Encourage responsible disclosure when vulnerabilities are found in real systems and provide students with resources and templates for reporting.
  • Suggested defensive classroom activities (safe & practical):
    • Manifest and permission review: students analyze benign APK manifests to spot overly broad permissions and propose mitigations.
    • Telemetry detection lab: simulate benign suspicious behavior on an emulator (local-only) and have students build detection rules.
    • Incident response table‑top: walk through a suspected compromised device scenario and practice containment and forensics planning.
    • Policy design exercise: students design an enterprise policy to prevent management interface exposure and outline monitoring/alerting.
  • Further reading & resources:
    • OWASP Mobile Top 10, OWASP MASVS, vendor mobile security guides, MDM best practices, and mobile incident response literature.

  
  
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