Packet Capture About
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Implementing Cisco Cyber Security Operations
2019 CLUS Implementing Cisco Cyber Security Operations Paul Ostrowski / Patrick Lao / James Risler Cisco Security Content Development Engineers LTRCRT-2222 2019 CLUS Cisco Webex Teams Questions? Use Cisco Webex Teams to chat with the speaker after the session How 1 Find this session in the Cisco Live Mobile App 2 Click “Join the Discussion” 3 Install Webex Teams or go directly to the team space 4 Enter messages/questions in the team space Webex Teams will be moderated cs.co/ciscolivebot#LTRCRT-2222 by the speaker until June 16, 2019. 2019 CLUS © 2019 Cisco and/or its affiliates. All rights reserved. Cisco Public 3 Agenda • Goals and Objectives • Prerequisite Knowledge & Skills (PKS) • Introduction to Security Onion • SECOPS Labs and Topologies • Access SECFND / SECOPS eLearning Lab Training Environment • Lab Evaluation • Cisco Cybersecurity Certification and Education Offerings 2019 CLUS LTRCRT-2222 © 2019 Cisco and/or its affiliates. All rights reserved. Cisco Public 4 Goals and Objectives: • Today's organizations are challenged with rapidly detecting cybersecurity breaches in order to effectively respond to security incidents. Cybersecurity provides the critical foundation organizations require to protect themselves, enable trust, move faster, add greater value and grow. • Teams of cybersecurity analysts within Security Operations Centers (SOC) keep a vigilant eye on network security monitoring systems designed to protect their organizations by detecting and responding to cybersecurity threats. • The goal of Cisco’s CCNA Cyber OPS (SECFND / SECOPS) courses is to teach the fundamental skills required to begin a career working as an associate/entry-level cybersecurity analyst within a threat centric security operations center. • This session will provide the student with an understanding of Security Onion as an open source network security monitoring tool (NSM). -
Virtualization of the RIOT Operating System
Computer Systems and Telematics — Distributed, Embedded Systems Diploma Thesis Virtualization of the RIOT Operating System Ludwig Ortmann Matr. 3914103 Supervisor: Dr. Emmanuel Baccelli Assisting Supervisor: Prof. Dr.-Ing. Jochen Schiller Institute of Computer Science, Freie Universität Berlin, Germany March 2, 2015 iii I hereby declare to have written this thesis on my own. I have used no other literature and resources than the ones referenced. All text passages that are literal or logical copies from other publications have been marked accordingly. All figures and pictures have been created by me or their sources are referenced accordingly. This thesis has not been submitted in the same or a similar version to any other examination board. Berlin, March 2, 2015 (Ludwig Ortmann) Abstract Abstract Software developers in the growing field of the Internet of Things face many hurdles which arise from the limitations of embedded systems and wireless networking. The employment of hardware and network virtualization promises to allow developers to test and debug hard- ware independent code without being affected by these limitations. This thesis presents RIOT native, a hardware and network emulation implementation for the RIOT operating system, which enables developers to compile and run RIOT as a process in their host operat- ing system. Running the operating system as a process allows for the use of debugging tools and techniques only available on desktop computers otherwise, the integration of common network analysis tools, and the emulation of arbitrary network topologies. By enabling the use of these tools and techniques for the development of software for distributed embedded systems, the hurdles they impose on the development process are significantly reduced. -
TCPDUMP Caution
TCPDUMP q Refer to book ”Open Source Network Administration” m Online sample chapter: http://www.phptr.com/articles/article.asp?p=170902&seqNum=4 q Some tools are not based directly on the data being transmitted on a network, but information related to that data. m For example, network bandwidth values m System logs on network equipment q Sometimes needs to examine the packets themselves. m Diagnose some particularly tricky network problems q Widely used open source tool for directly analyzing packets: tcpdump m http://www.tcpdump.org/ Network Analyzer 1-1 Caution q Before you use tcpdump or other analyzer: m Will be able to see some private data m Consult/research Legal implication first m Respect the privacy of other users Network Analyzer 1-2 1 What Tcpdump can do for you q View the entire data portion of an Ethernet frame or other link layer protocol m An IP packet m An ARP packet m Or any protocol at a higher layer than Ethernet. q Very useful m Tcpdump is to a network administrator like a microscope to a biologist. m Give a very clear picture of a specific part of your network m Can be used when the problem is simply that something is not working properly. Network Analyzer 1-3 What tcpdump can do for you? q Case1 : Web browser can not load pages from a server – it hangs. m Problem with client? Server? Or between? m Run tcpdump while loading • Watch every stage to see the following – DNS query – HTTP request to server – Server respond q Case 2: help debug denial of service attacks. -
Hands-On Network Forensics, FIRST 2015
2015-04-30 WWW.FORSVARSMAKTEN.SE Hands-on Network Forensics Workshop Preparations: 1. Unzip the virtual machine from NetworkForensics_ VirtualBox.zip on your EXTENSIVE USE OF USB thumb drive to your local hard drive COMMAND LINE 2. Start VirtualBox and run the Security Onion VM IN THIS WORKSHOP 3. Log in with: user/password 1 FM CERT 2015-04-30 WWW.FORSVARSMAKTEN.SE Hands-on Network Forensics Erik Hjelmvik, Swedish Armed Forces CERT FIRST 2015, Berlin 2 FM CERT 2015-04-30 WWW.FORSVARSMAKTEN.SE Hands-on Network Forensics Workshop Preparations: 1. Unzip the virtual machine from NetworkForensics_ VirtualBox.zip on your EXTENSIVE USE OF USB thumb drive to your local hard drive COMMAND LINE 2. Start VirtualBox and run the Security Onion VM IN THIS WORKSHOP 3. Log in with: user/password 3 FM CERT 2015-04-30 WWW.FORSVARSMAKTEN.SE ”Password” Ned 4 FM CERT 2015-04-30 WWW.FORSVARSMAKTEN.SE SysAdmin: Homer 5 FM CERT 2015-04-30 WWW.FORSVARSMAKTEN.SE PR /Marketing: Krusty the Clown 6 FM CERT 2015-04-30 WWW.FORSVARSMAKTEN.SE Password Ned AB = pwned.se 7 FM CERT 2015-04-30 WWW.FORSVARSMAKTEN.SE pwned.se Network [INTERNET] | Default Gateway 192.168.0.1 PASSWORD-NED-XP www.pwned.se | 192.168.0.53 192.168.0.2 [TAP]--->Security- | | | Onion -----+------+---------+---------+----------------+------- | | Homer-xubuntu Krustys-PC 192.168.0.51 192.168.0.54 8 FM CERT 2015-04-30 WWW.FORSVARSMAKTEN.SE Security Onion 9 FM CERT 2015-04-30 WWW.FORSVARSMAKTEN.SE Paths (also on Cheat Sheet) • PCAP files: /nsm/sensor_data/securityonion_eth1/dailylogs/ • Argus files: -
Network Intell: Enabling the Non-Expert Analysis of Large Volumes of Intercepted Network Traffic
Chapter 1 NETWORK INTELL: ENABLING THE NON- EXPERT ANALYSIS OF LARGE VOLUMES OF INTERCEPTED NETWORK TRAFFIC Erwin van de Wiel, Mark Scanlon and Nhien-An Le-Khac Abstract In criminal investigations, telecommunication wiretaps have become a common technique used by law enforcement. While phone-based wire- tapping is well documented and the procedure for their execution are well known, the same cannot be said for Internet taps. Lawfully inter- cepted network traffic often contains a lot of encrypted traffic making it increasingly difficult to find useful information inside the traffic cap- tured. The advent of Internet-of-Things further complicates the pro- cess for non-technical investigators. The current level of complexity of intercepted network traffic is close to a point where data cannot be analysed without supervision of a digital investigator with advanced network knowledge. Current investigations focus on analysing all traffic in a chronological manner and are predominately conducted on the data contents of the intercepted traffic. This approach often becomes overly arduous when the amount of data to be analysed becomes very large. In this paper, we propose a novel approach to analyse large amounts of intercepted network traffic based on network metadata. Our approach significantly reduces the duration of the analysis and also produces an arXiv:1712.05727v2 [cs.CR] 27 Jan 2018 insight view of analysing results for the non-technical investigator. We also test our approach with a large sample of network traffic data. Keywords: Network Investigation, Big Data Forensics, Intercepted Network Traffic, Internet tap, Network Metadata Analysis, Non-Technical Investigator. 1. Introduction Lawful interception is a method that is used by the police force in some countries in almost all middle-to high-level criminal investigations. -
CIT 485: Network Forensics
CIT 485/585 Network Forensics The primary objective of this assignment is to learn a process for investigating security incidents and to give students practice analyzing such an incident using captured network data. 1S TUDENT LEARNING OUTCOMES 1. Describe digital evidence and how the type of legal dispute affects evidence used to resolve it. 2. Describe the steps of the OSCAR network forensics methodology. 3. Identify and decode protocols used on non-standard ports. 4. Investigate suspicious network data for malicious activity. 2D IGITAL EVIDENCE Digital evidence refers to any data collected in digital form from any computer, whether that computer is a desktop, mobile device, game console, printer, or IoT device. A primary goal of digital forensics is ensuring evidence integrity, the preservation of evidence in its original form. Evidence integrity is supported by a chain of custody, a set of documentation that describes the acquisition, copying, and analysis of digital evidence. As analysis of digital data often changes that data (reading a file will not modify the file itself but will change the last accessed time on the file), cryptographic checksums such as SHA-256 are often used to ensure that copies of digital evidence match the original evidence. Details of digital evidence handling are discussed in CIT 430: Computer Forensics. Digital evidence in a criminal case is returned through an inventory of items take through a search warrant. Any devices that may contain an embedded computer can contain digital evidence. Defense attorneys can request an invetory of items and obtain forensic copies of the data from those devices. -
Passive Asset Discovery and Operating System Fingerprinting in Industrial Control System Networks
Eindhoven University of Technology MASTER Passive asset discovery and operating system fingerprinting in industrial control system networks Mavrakis, C. Award date: 2015 Link to publication Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain Department of Mathematics and Computer Science Passive Asset Discovery and Operating System Fingerprinting in Industrial Control System Networks Master Thesis Chris Mavrakis Supervisors: prof.dr. S. Etalle dr. T. Oz¸celebi¨ dr. E. Costante Eindhoven, October 2015 Abstract Maintaining situational awareness in networks of industrial control systems is challenging due to the sheer number of devices involved, complex connections between subnetworks and the delicate nature of industrial processes. While current solutions for automatic discovery of devices and their operating system are lacking, plant operators need to have accurate information about the systems to be able to manage them effectively and detect, prevent and mitigate security and safety incidents. -
I3: Maximizing Packet Capture Performance
I3: Maximizing Packet Capture Performance Andrew Brown Agenda • Why do captures drop packets, how can you tell? • Software considerations • Hardware considerations • Potential hardware improvements • Test configurations/parameters • Performance results Sharkfest 2014 What is a drop? • Failure to capture a packet that is part of the traffic in which you’re interested • Dropped packets tend to be the most important • Capture filter will not necessarily help Sharkfest 2014 Why do drops occur? • Applications don’t know that their data is being captured • Result: Only one chance to capture a packet • What can go wrong? Let’s look at the life of a packet Sharkfest 2014 Internal packet flow • Path of a packet from NIC to application (Linux) • Switch output queue drops • Interface drops • Kernel drops Sharkfest 2014 Identifying drops • Software reports drops • L4 indicators (TCP ACKed lost segment) • L7 indicators (app-level sequence numbers revealed by dissector) Sharkfest 2014 When is (and isn’t) it necessary to take steps to maximize capture performance? • Not typically necessary when capturing traffic of <= 1G end device • More commonly necessary when capturing uplink traffic from a TAP or SPAN port • Some sort of action is almost always necessary at 10G • Methods described aren’t always necessary • Methods focus on free solutions Sharkfest 2014 Software considerations - Windows • Quit unnecessary programs • Avoid Wireshark for capturing ˗ Saves to TEMP ˗ Additional processing for packet statistics • Uses CPU • Uses memory over time, can lead -
PROGRAMMING ESSENTIALS in PYTHON | PCAP Certification
PROGRAMMING ESSENTIALS IN PYTHON | PCAP Certification Programming Essentials in Python course covers all the basics of programming in Python, as well as general computer programming concepts and techniques. The course also familiarizes the student with the object-oriented approach. The course will prepare the student for jobs/careers connected with widely understood software development, which includes not only creating the code itself as a junior developer, but also computer system design and software testing. It could be a stepping-stone to learning any other programming language, and to explore technologies using Python as a foundation (e.g., Django, SciPy). This course is distinguished by its affordability, friendliness, and openness to the student. It starts from the absolute basics, guiding the student step by step to complex problems, making her/him a responsible software creator able to take on different challenges in many positions in the IT industry. TARGET AUDIENCE Programming Essentials in Python curriculum is designed for students with little or no prior knowledge of programming. TARGET CERTIFICATION Programming Essentials in Python curriculum helps students prepare for the PCAP | Python Certified Associate Programmer certification exam. PCAP is a professional certification that measures the student’s ability to accomplish coding tasks related to the basics of programming in the Python language, and the fundamental notions and techniques used in object-oriented programming. PCAP – COURSE MODULES & OBJECTIVES Module 1: Familiarize the student with the basic methods offered by Python of formatting and outputting data, together with the primary kinds of data and numerical operators, their mutual relations and bindings. Introduce the concept of variables and variable naming conventions. -
Network Forensics
Network Forensics Michael Sonntag Institute of Networks and Security What is it? Evidence taken from the “network” In practice this means today the Internet (or LAN) In special cases: Telecommunication networks (as long as they are not yet changed to VoIP!) Typically not available “after the fact” Requires suspicions and preparation in advance Copying the communication content At the source (=within the suspects computer): “Online search” This could also be a webserver, e.g. if it contains illegal content “Source” does NOT mean that this is the client/initiator of communication/… At the destination: See some part of the traffic Only if unavoidable or the only interesting part Somewhere on the way of the (all?) traffic: ISP, physically tapping the wires, home routers etc. Network Forensics 2 Problems of network forensics “So you have copied some Internet traffic – but how is it linked to the suspect?” The IP addresses involved must be tied to individual persons This might be easy (location of copying) or very hard “When did it take place?” Packet captures typically have only relative timestamps But there may be lots of timestamps in the actual traffic! As supporting evidence to some external documentation “Is it unchanged?” These are merely packets; their content can be changed Although it is possible to check e.g. checksums, this is a lot of work and normally not done Treat as any other digital evidence Hash value + Chain of Custody; work on copies only Network Forensics 3 Scenario Suspect: Mallory Malison; released -
Guide to Computer Forensics and Investigations Fourth Edition
Guide to Computer Forensics and Investigations Fourth Edition Chapter 11 Virtual Machines, Network Forensics, and Live Acquisitions Objectives • Describe primary concerns in conducting forensic examinations of virtual machines • Describe the importance of network forensics • Explain standard procedures for performing a live acquisition • Explain standard procedures for network forensics • Describe the use of network tools Guide to Computer Forensics and Investigations 2 Virtual Machines Overview • Virtual machines are important in today’s networks. • Investigators must know how to detect a virtual machine installed on a host, acquire an image of a virtual machine, and use virtual machines to examine malware. Virtual Machines Overview (cont.) • Check whether virtual machines are loaded on a host computer. • Check Registry for clues that virtual machines have been installed or uninstalled. Network Forensics Overview • Network forensics – Systematic tracking of incoming and outgoing traffic • To ascertain how an attack was carried out or how an event occurred on a network • Intruders leave trail behind • Determine the cause of the abnormal traffic – Internal bug – Attackers Guide to Computer Forensics and Investigations 5 Securing a Network • Layered network defense strategy – Sets up layers of protection to hide the most valuable data at the innermost part of the network • Defense in depth (DiD) – Similar approach developed by the NSA – Modes of protection • People • Technology • Operations Guide to Computer Forensics and Investigations -
Of Mobile Devices: a Survey on Network Traffic Analysis
1 The Dark Side(-Channel) of Mobile Devices: A Survey on Network Traffic Analysis Mauro Conti, Senior Member, IEEE, QianQian Li, Alberto Maragno, and Riccardo Spolaor*, Member, IEEE. Abstract—In recent years, mobile devices (e.g., smartphones elements enable both smartphones and tablets to have the and tablets) have met an increasing commercial success and same functionalities typically offered by laptops and desktop have become a fundamental element of the everyday life for computers. billions of people all around the world. Mobile devices are used not only for traditional communication activities (e.g., voice According to the statistics reported in [1], smartphone calls and messages) but also for more advanced tasks made users were 25:3% of the global population in 2015, and this possible by an enormous amount of multi-purpose applications percentage is expected to grow till 37% in 2020. Similarly, the (e.g., finance, gaming, and shopping). As a result, those devices statistics about tablets reported in [2] indicate a global penetra- generate a significant network traffic (a consistent part of the overall Internet traffic). For this reason, the research community tion of 13:8% in 2015, expected to reach 19:2% in 2020. The has been investigating security and privacy issues that are related driving forces of this tremendous success are the ubiquitous to the network traffic generated by mobile devices, which could Internet connectivity, thanks to the worldwide deployment of be analyzed to obtain information useful for a variety of goals cellular and Wi-Fi networks, and a large number of apps (ranging from fine-grained user profiling to device security and available in the official (and unofficial) marketplaces.