CEH Practical: Information-Gathering Methodology

 

Information gathering can be broken into seven logical steps. Footprinting is performed during the first two steps of unearthing initial information and locating the network range.

Footprinting

Footprinting is defined as the process of establishing a scenario or creating a map of an organization's network and systems. Information gathering is also known as footprinting an organization. Footprinting is an important part of reconnaissance process which is typically used for collecting possible information about a targeted computer system or network. Active and Passive both could be Footprinting. The example of passive footprinting is assessment of a company's website, whereas attempting to gain access to sensitive information through social engineering is an example of active information gathering. Basically footprinting is the beginning step of hacker to get hacked someone because having information about targeted computer system is the main aspect of hacking. If you have an information about individual you wanna hack so you can easily hacked that individual. The basic purpose of information gathering is at least decide what type of attacks will be more suitable for the target. Here are some of the pieces of information to be gathered about a target
during footprinting:

• Domain name
• Network blocks
• Network services and applications
• System architecture
• Intrusion detection system
• Authentication mechanisms
• Specific IP addresses
• Access control mechanisms
• Phone numbers
• Contact addresses

Once this information is assemble, it can give a hacker better perception into the organization, where important information is stored, and how it can be accessed.

Footprinting Tools 

Footprinting can be done using hacking tools, either applications or websites, which allow the hacker to locate information passively. By using these footprinting tools, a hacker can gain some basic information on, or "footprint," the target. By first footprinting the target, a hacker can eliminate tools that will not work against the target systems or network. For example, if a graphics design firm uses all Macintosh computers, then all hacking software that targets Windows systems can be eliminated. Footprinting not only speeds up the hacking process by eliminating certain tool sets but also minimizes the chance of detection as fewer hacking attempts can be made by using the right tool for the job. Some of the common tools used for footprinting and information gathering are as follows:

• Domain name lookup
• Whois
• NSlookup
• Sam Spade

Before we discuss these tools, keep in mind that open source information can also yield a wealth of information about a target, such as phone numbers and addresses. Performing Whois requests, searching domain name system (DNS) tables, and using other lookup web tools are forms of open source footprinting. Most of this information is fairly easy to get and legal to obtain.

Footprinting a Target 

Footprinting is part of the preparatory pre-attack phase and involves accumulating data regarding a target's environment and architecture, usually for the purpose of finding ways to intrude into that environment. Footprinting can reveal system vulnerabilities and identify the ease with which they can be exploited. This is the easiest way for hackers to gather information about computer systems and the companies they belong to. The purpose of this preparatory phase is to learn as much as you can about a system, its remote access capabilities, its ports and services, and any specific aspects of its security.

DNS Enumeration

DNS enumeration is the process of locating all the DNS servers and their corresponding records for an organization. A company may have both internal and external DNS servers that can yield information such as usernames, computer names, and IP addresses of potential target systems.

NSlookup and DNSstuff

One powerful tool you should be familiar with is NSlookup (see Figure 2.2). This tool queries DNS servers for record information. It's included in Unix, Linux, and Windows operating systems. Hacking tools such as Sam Spade also include NSlookup tools. Building on the information gathered from Whois, you can use NSlookup to find additional IP addresses for servers and other hosts. Using the authoritative name server information from Whois ( AUTH1.NS.NYI.NET ), you can discover the IP address of the mail server.

Syntax

nslookup www.sitename.com

nslookup www.usociety4.com

Performing DNS Lookup

This search reveals all the alias records for www.google.com and the IP address of the web server. You can even discover all the name servers and associated IP addresses.

Understanding Whois and ARIN Lookups

Whois evolved from the Unix operating system, but it can now be found in many operating systems as well as in hacking toolkits and on the Internet. This tool identifies who has registered domain names used for email or websites. A uniform resource locator (URL), such as www.Microsoft.com , contains the domain name ( Microsoft.com ) and a hostname or alias ( www ).
The Internet Corporation for Assigned Names and Numbers (ICANN) requires registration of domain names to ensure that only a single company uses a specific domain name. The Whois tool queries the registration database to retrieve contact information about the individual or organization that holds a domain registration.

Using Whois

• Go to the DNSStuff.com website and scroll down to the free tools at the bottom of the page.
• Enter your target company URL in the WHOIS Lookup field and click the WHOIS button.
• Examine the results and determine the following:
  
  • Registered address
  • Technical and DNS contacts
  • Contact email
  • Contact phone number
  • Expiration date

• Visit the company website and see if the contact information from WHOIS matches up to any contact names, addresses, and email addresses listed on the website.

• If so, use Google to search on the employee names or email addresses. You can learn the email naming convention used by the organization, and whether there is any information that should not be publicly available.

Syntax

whois sitename.com
whois usociety4.com

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Why Receipt Notifications Increase Security In Signal

This blog post is aimed to express and explain my surprise about Signal being more secure than I thought (due to receipt acknowledgments). I hope you find it interesting, too.

Signal, and especially its state update protocol, the Double Ratchet algorithm, are widely known for significantly increasing security for instant messaging. While most users first see the end-to-end security induced by employing Signal in messaging apps, the properties achieved due to ratcheting go far beyond protecting communication against (active) attackers on the wire. Due to updating the local device secrets via the Double Ratchet algorithm, the protocol ensures that attackers, who temporarily obtain a device's local storage (on which Signal runs), only compromise confidentiality of parts of the communications with this device. Thus, the leakage of local secrets from a device only affects security of a short frame of communication. The exact duration of compromise depends on the messaging pattern among the communicating parties (i.e., who sends and receives when), as the state update is conducted during the sending and receiving of payload messages.

The Double Ratchet

The Double Ratchet algorithm consists of two different update mechanisms: the symmetric ratchet and the asymmetric ratchet. The former updates symmetric key material by hashing and then overwriting it with the hash output (i.e.,  k:=H(k)). Thus, an attacker, obtaining key material can only predict future versions of the state but, due to the one-wayness of the hash function, cannot recover past states. The asymmetric ratchet consists of Diffie-Hellman key exchanges (DHKE). If, during the communication, party A receives a new DH share g^b as part of a message from the communication partner B, then A samples a new DH exponent a and responds with the respective DH share g^a in the next sent message. On receipt of this DH share, B will again sample a new DH exponent b' and attach the DH share g^b' to the next message to A. With every new DH share, a new DHKE g^ab is computed among A and B and mixed into the key material (i.e., k:=H(k,g^ab)). For clarity, I leave out a lot of details and accuracy. As new DH shares g^a and g^b are generated from randomly sampled DH exponents a and b, and the computation of g^ab is hard if neither a nor b are known, the key material recovers from an exposure of the local secrets to an attacker after a new value g^ab was freshly established and mixed into it. Summing up this mechanism, if an attacker obtains the local state of a Signal client, then this attacker cannot recover any previously received message (if the message itself was not contained in the local state), nor can it read messages that are sent after a new g^ab was established and mixed into the state. The latter case happens with every full round-trip among A and B (i.e., A receives from B, A sends to B, and A receives again from B).

Conceptual depiction of Double Ratchet in Signal two years ago (acknowledgments were only protected between client and server). The asymmetric ratchet fully updates the local secrets after one round-trip of payload messages.

Research on Ratcheting

During the last two years, the Signal protocol inspired the academic research community: First, a formal security proof of Signal was conducted [1] and then ratcheting was formalized as a generic primitive (independent of Signal) [2,3,4]. This formalization includes security definitions that are derived via 1. defining an attacker, 2. requiring security unless it is obvious that security cannot be reached. Protocols, meeting this optimal notion of security, were less performant than the Double Ratchet algorithm [3,4]. However, it became evident that the Double Ratchet algorithm is not as secure as it could be (e.g., recovery from exposure could be achieved quicker than after a full round-trip; see, e.g., Appendix G of our paper [3]). Afterwards, protocols (for slightly weakened security notions) were proposed that are similarly performant as Signal but also a bit more secure [5,6,7].

Protecting Acknowledgments ...

In our analysis of instant messaging group chats [8] two years ago (blog posts: [9,10]), we found out that none of the group chat protocols (Signal, WhatsApp, Threema) actually achieves real recovery from an exposure (thus the asymmetric ratchet is not really effective in groups; a good motivation for the MLS project) and that receipt acknowledgments were not integrity protected in Signal nor WhatsApp. The latter issue allowed an attacker to drop payload messages in transmission and forge receipt acknowledgments to the sender such that the sender falsely thinks the message was received. Signal quickly reacted on our report by treating acknowledgments as normal payload messages: they are now authenticated(-encrypted) using the Double Ratchet algorithm.

... Supports Asymmetric Ratchet

Two years after our analysis, I recently looked into the Signal code again. For a training on ratcheting I wanted to create an exercise for which the lines in the code should be found that execute the symmetric and the asymmetric ratchet respectively. Somehow I observed that the pure symmetric ratchet (only updates via hash functions) was nearly never executed (especially not when I expected it) when lively debugging the app but almost always new DH shares were sent or received. I realized that, due to encrypting the receipt acknowledgments now, the app always conducts full round-trips with every payload message. In order to observe the symmetric ratchet, I needed to temporarily turn on the flight mode on my phone such that acknowledgments are not immediately returned.

Conceptual depiction of Double Ratchet in Signal now (acknowledgments encrypted). The asymmetric ratchet fully updates the local secrets after an acknowledgment for a message is received.

Consequently, Signal conducts a full DHKE on every sent payload message (in case the receiving device is not offline) and mixes the result into the state. However, a new DH exponent is always already sampled on the previous receipt (see sketch of protocol above). Thus, the exponent for computing a DHKE maybe remained in the local device state for a while. In order to fully update the state's key material, two round-trips must be initiated by sending two payload messages and receiving the resulting two acknowledgments. Please note that not only the mandatory receipt acknowledgments are encrypted but also notifications on typing and reading a message.

If you didn't understand exactly what that means, here a tl;dr: If an attacker obtains your local device state, then with Signal all previous messages stay secure and (if the attacker does not immediately use these secrets to actively manipulate future conversations) all future messages are secure after you wrote two messages (and received receipt acknowledgments) in all of your conversations. Even though this is very (in practice certainly sufficiently) secure, recent protocols provide stronger security (as mentioned above) and it remains an interesting research goal to increase their performance.

[1] https://eprint.iacr.org/2016/1013.pdf
[2] https://eprint.iacr.org/2016/1028.pdf
[3] https://eprint.iacr.org/2018/296.pdf
[4] https://eprint.iacr.org/2018/553.pdf
[5] https://eprint.iacr.org/2018/889.pdf
[6] https://eprint.iacr.org/2018/954.pdf
[7] https://eprint.iacr.org/2018/1037.pdf
[8] https://eprint.iacr.org/2017/713.pdf
[9] https://web-in-security.blogspot.com/2017/07/insecurities-of-whatsapps-signals-and.html
[10] https://web-in-security.blogspot.com/2018/01/group-instant-messaging-why-baming.html

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