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    You are at:Home»Technology»Releasing rainbow tables to accelerate Net-NTLMv1 protocol deprecation
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    Releasing rainbow tables to accelerate Net-NTLMv1 protocol deprecation

    TechAiVerseBy TechAiVerseJanuary 17, 2026No Comments5 Mins Read2 Views
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    Releasing rainbow tables to accelerate Net-NTLMv1 protocol deprecation

    Introduction

    Mandiant is publicly releasing a comprehensive dataset of Net-NTLMv1 rainbow tables to underscore the urgency of migrating away from this outdated protocol. Despite Net-NTLMv1 being deprecated and known to be insecure for over two decades—with cryptanalysis dating back to 1999—Mandiant consultants continue to identify its use in active environments. This legacy protocol leaves organizations vulnerable to trivial credential theft, yet it remains prevalent due to inertia and a lack of demonstrated immediate risk.

    By releasing these tables, Mandiant aims to lower the barrier for security professionals to demonstrate the insecurity of Net-NTLMv1. While tools to exploit this protocol have existed for years, they often required uploading sensitive data to third-party services or expensive hardware to brute-force keys. The release of this dataset allows defenders and researchers to recover keys in under 12 hours using consumer hardware costing less than $600 USD. This initiative highlights the amplified impact of combining Mandiant’s frontline expertise with Google Cloud’s resources to eliminate entire classes of attacks.

    This post details the generation of the tables, provides access to the dataset for community use, and outlines critical remediation steps to disable Net-NTLMv1 and prevent authentication coercion attacks.

    Background

    Net-NTLMv1 has been widely known to be insecure since at least 2012, following presentations at DEFCON 20, with cryptanalysis of the underlying protocol dating back to at least 1999. On Aug. 30, 2016, Hashcat added support for cracking Data Encryption Standard (DES) keys using known plaintext, further democratizing the ability to attack this protocol. Rainbow tables are almost as old, with the initial paper on rainbow tables published in 2003 by Philippe Oechslin, citing an earlier iteration of a time-memory trade-off from 1980 by Martin Hellman.

    Essentially, if an attacker can obtain a Net-NTLMv1 hash without Extended Session Security (ESS) for the known plaintext of 1122334455667788, a cryptographic attack, referred to as a known plaintext attack (KPA), can be applied. This guarantees recovery of the key material used. Since the key material is the password hash of the authenticating Active Directory (AD) object—user or computer—the attack results can quickly be used to compromise the object, often leading to privilege escalation.

    A common chain attackers use is authentication coercion from a highly privileged object, such as a domain controller (DC). Recovering the password hash of the DC machine account allows for DCSync privileges to compromise any other account in AD.

    Dataset Release

    The unsorted dataset can be downloaded using gsutil -m cp -r gs://net-ntlmv1-tables/tables . or through the Google Cloud Research Dataset portal. 

    The SHA512 hashes of the tables can be checked by first downloading the checksums gsutil -m cp gs://net-ntlmv1-tables/tables.sha512 . then checked by sha512sum -c tables.sha512. The password cracking community has already created derivative work and is also hosting the ready to use tables.

    Use of the Tables

    Once a Net-NTLMv1 hash has been obtained, the tables can be used with historical or modern reinventions of rainbow table searching software such as rainbowcrack (rcrack), or RainbowCrack-NG on central processing units (CPUs) or a fork of rainbowcrackalack on graphics processing units (GPUs). The Net-NTLMv1 hash needs to be preprocessed to the DES components using ntlmv1-multi as shown in the next section.

    Obtaining a Net-NTLMv1 Hash

    Most attackers will use Responder with the --lm and --disable-ess flags and set the authentication to a static value of 1122334455667788 to only allow for connections with Net-NTLMv1 as a possibility. Attackers can then wait for incoming connections or coerce authentication using a tool such as PetitPotam or DFSCoerce to generate incoming connections from DCs or lower privilege hosts that are useful for objective completion. Responses can be cracked to retrieve password hashes of either users or computer machine accounts. A sample workflow for an attacker is shown below in Figure 1, Figure 2, and Figure 3.

    Figure 1: DFSCoerce against a DC

    Figure 2: Net-NTLMv1 hash obtained for DC machine account

    Figure 3: Parse Net-NTLMv1 hash to DES parts

    Figure 4 illustrates the processing of the Net-NTLMv1 hash to the DES ciphertexts.

    Figure 4: Net-NTLMv1 hash to DES ciphertexts

    An attacker then takes the split-out ciphertexts to crack the keys used based on the known plaintext of 1122334455667788 with the steps of loading the tables shown in Figure 5 and cracking results in Figure 6 and Figure 7.

    Figure 5: Loading DES components for cracking

    Figure 6: First hash cracked

    Figure 7: Second hash cracked and run statistics

    An attacker can then calculate the last remaining key with ntlmv1-multi once again, or look it up with twobytes, to recreate the full NT hash for the DC account with the last key part shown in Figure 8.

    Figure 8: Calculate remaining key

    The result can be checked with hashcat’s NT hash shucking mode, -m 27000, as shown in Figure 9.

    Figure 9: Keys checked with hash shucking

    An attacker can then use the hash to perform a DCSync attack targeting a DC and authenticating as the now compromised machine account. The attack flow uses secretsdump.py from the Impacket toolsuite and is shown in Figure 10.

    Figure 10: DCSync attack performed

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    Jonathan is a tech enthusiast and the mind behind Tech AI Verse. With a passion for artificial intelligence, consumer tech, and emerging innovations, he deliver clear, insightful content to keep readers informed. From cutting-edge gadgets to AI advancements and cryptocurrency trends, Jonathan breaks down complex topics to make technology accessible to all.

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