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In computer security, pass the hash is a hacking technique that allows an attacker to authenticate to a remote server or service by using the underlying NTLM or LanMan hash of a user's password, instead of requiring the associated plaintext password as is normally the case. It replaces the need for stealing the plaintext password to gain access with stealing the hash.
Native Windows applications ask users for the cleartext password, then call APIs like LsaLogonUser that convert that password to one or two hash values (the LM or NT hashes) and then send that to the remote server during NTLM authentication.[Notes 1]
If an attacker has the hashes of a user's password, they do not need the cleartext password; they can simply use the hash to authenticate with a server and impersonate that user. In other words, from an attacker's perspective, hashes are functionally equivalent to the original passwords that they were generated from.
The pass the hash technique was originally published by Paul Ashton in 1997 and consisted of a modified Samba SMB client that accepted user password hashes instead of cleartext passwords. Later versions of Samba and other third-party implementations of the SMB and NTLM protocols also included the functionality.
This implementation of the technique was based on an SMB stack created by a third-party (e.g., Samba and others), and for this reason suffered from a series of limitations from a hacker's perspective, including limited or partial functionality: The SMB protocol has continued to evolve over the years, this means that third parties creating their own implementation of the SMB protocol need to implement changes and additions to the protocol after they are introduced by newer versions of Windows and SMB (historically by reverse engineering, which is very complex and time-consuming). This means that even after performing NTLM authentication successfully using the pass the hash technique, tools like Samba's SMB client might not have implemented the functionality the attacker might want to use. This meant that it was difficult to attack Windows programs that use DCOM or RPC.
Also, because attackers were restricted to using third-party clients when carrying out attacks, it was not possible to use built-in Windows applications, like Net.exe or the Active Directory Users and Computers tool amongst others, because they asked the attacker or user to enter the cleartext password to authenticate, and not the corresponding password hash value.
The tool also introduced a new technique which allowed dumping password hashes cached in the memory of the lsass.exe process (not in persistent storage on disk), which quickly became widely used by penetration testers (and attackers). This hash harvesting technique is more advanced than previously used techniques (e.g. dumping the local Security Accounts Manager database (SAM) using pwdump and similar tools), mainly because hash values stored in memory could include credentials of domain users (and domain administrators) that logged into the machine. For example, the hashes of authenticated domain users that are not stored persistently in the local SAM can also be dumped. This makes it possible for a penetration tester (or attacker) to compromise a whole Windows domain after compromising a single machine that was a member of that domain. Furthermore, the attack can be implemented instantaneously and without any requirement for expensive computing resources to carry out a brute force attack.
Before an attacker can carry out a pass-the-hash attack, they must obtain the password hashes of the target user accounts. To this end, penetration testers and attackers can harvest password hashes using a number of different methods:
Any system using LM or NTLM authentication in combination with any communication protocol (SMB, FTP, RPC, HTTP etc.) is at risk from this attack. The exploit is very difficult to defend against, due to possible exploits in Windows and applications running on Windows that can be used by an attacker to elevate their privileges and then carry out the hash harvesting that facilitates the attack. Furthermore, it may only require one machine in a Windows domain to not be configured correctly or be missing a security patch for an attacker to find a way in. A wide range of penetration testing tools are furthermore available to automate the process of discovering a weakness on a machine.
The simplest way to crack a hash is to try first to guess the password. Each attempt is hashed and then is compared to the actual hashed value to see if they are the same, but the process can take a long time.
Additionally, there are some GUI that makes hashcat easy to use. Hashview is one of the projects. This is a tool for security professionals to help organize and automate the repetitious tasks related to password cracking. In detail, it is a web application that manages Hashcat commands.
Pedro Tavares is a professional in the field of information security working as an Ethical Hacker, Malware Analyst and a Security Evangelist. He is also Editor-in-Chief of the security computer blog seguranca-informatica.pt.In recent years, he has invested in the field of information security, exploring and analyzing a wide range of topics, such as malware, reverse engineering, pentesting (Kali Linux), hacking/red teaming, mobile, cryptography, IoT, and security in computer networks. He is also a Freelance Writer.
C++ has always had the convenient data structures std::set and std::map, which are tree data structures whose operations take time. With C++11, we finally received a hash set and hash map in std::unordered_set and std::unordered_map. Unfortunately, I've seen a lot of people on Codeforces get hacked or fail system tests when using these. In this post I'll explain how it's possible to break these data structures and what you can do in order to continue using your favorite hash maps without worrying about being hacked .
So how are they hackable? We always assume hash maps are O(1) per operation (insert, erase, access, etc.). But this depends on a key assumption, which is that each item only runs into O(1) collisions on average. If our input data is completely random, this is a reasonable assumption. But this is no longer a safe bet when the input isn't random, especially so if someone is adversarially designing inputs to our code (a.k.a. hacking phase). In particular, if they know our hash function, they can easily generate a large number of different inputs that all collide, thus causing an O(n2) blow-up.
After some searching around we run into unordered_map.h. Inside the file we can quickly see that unordered_map makes use of __detail::_Mod_range_hashing and __detail::_Prime_rehash_policy. From this we can guess that the map first hashes the input value and then mods by a prime number, and the result is used as the appropriate position in the hash table.
Some further searching for _Prime_rehash_policy leads us to hashtable_c++0x.cc. Here we can see that there is an array called __prime_list, and the hash table has a policy to resize itself when it gets too large. So we just need to find this list of primes.
One more thing: we need to know the hash function unordered_map uses before modding by these primes. It turns out to be quite simple: the map uses std::hash, which for integers is simply the identity function. Armed with this knowledge, we can insert lots of multiples of one of these primes to the map in order to get n2 blow-up. Not all of the primes work though, due to the resizing policy of the map; in order for a prime to work, we need the map to actually resize to this prime at some point in its set of operations. It turns out the right prime depends on the compiler version: for gcc 6 or earlier, 126271 does the job, and for gcc 7 or later, 107897 will work. Run the code below in Custom Invocation and see what output you get.
Note that for other hash tables like cc_hash_table or gp_hash_table (see Chilli's helpful post), it's even easier to hack them. These hash tables use a modulo power of two policy, so in order to make a lot of collisions occur we can simply insert a lot of numbers that are equivalent, say, modulo 216.
Let's look at how to safeguard these hash maps from collision attacks. To do this we can write our own custom hash function which we give to the unordered_map (or gp_hash_table, etc.). The standard hash function looks something like this:
However as we mentioned, any predictable / deterministic hash function can be reverse-engineered to produce a large number of collisions, so the first thing we should do is add some non-determinism (via high-precision clock) to make it more difficult to hack:
See my post on making randomized solutions unhackable for more details. Awesome, so our hash is perfectly safe now, right? Not so fast. All we've done is add the same fixed number to every input to the function. But if two numbers a and b satisfy a = b (mod m), then a + x = b + x (mod m) for every x as well. Similar problems occur for other very simple hash functions: multiplying by a random large odd number (and overflowing mod 264) is likely effectively modulo p, but will be problematic for gp_hash_table's power of two policy; the same situation occurs for xor-ing with a random number. 2b1af7f3a8