Quantum Prism Extractor Attack

The Quantum Prism Extractor Attack is a spectacular attack on cryptographic applications that utilize predictable pseudorandom number generators (PRNGs) in key areas, such as generating private keys, time values, or random parameters. An attacker can “refract” a data stream through an unprotected generator and, by analyzing the resulting output, recover the random number sequence and, consequently, the secret keys or private parameters embedded in the application.

It is critical to always use cryptographically strong random number generators (CSPRNGs) for all operations involving private keys or nonces, and thoroughly audit all dependencies, libraries, and hardware to eliminate the threat of an attack against a weak PRNG. The scale of an attack and its consequences could be catastrophic for the Bitcoin ecosystem if even a small number of keys are compromised.

The Quantum Prism Extractor attack demonstrates the critical importance of using only cryptographically secure random number generators. By guaranteeing high entropy and the impossibility of predicting or reconstructing the generator’s internal state, modern CSPRNGs protect users from compromising their private secrets, preserving the trust and security of cryptographic systems.

A critical vulnerability associated with the use of weak pseudorandom number generators (PRNGs) for signatures and private key generation in Bitcoin is one of the most dangerous threats to the cryptocurrency ecosystem. The attack, known in the scientific community as the ECDSA Nonce Reuse Attack or Weak Randomness Attack on ECDSA , allows users’ private keys to be recovered by analyzing transaction signatures using repeated or predictable nonces. keyhunters+2

Historical precedents have shown that several such vulnerabilities have led to massive losses, the compromise of millions of dollars, and the undermining of trust in Bitcoin’s security. An attacker with minimal network access can automatically detect signatures with identical or weakly random nonces, instantly extract private keys, and withdraw funds from vulnerable addresses. The mathematical simplicity of the attack and the inevitability of its success in the presence of weak entropy—whether due to hardware errors, improper implementation of RFC 6979, or auditing flaws—makes the problem extremely critical for any cryptocurrency client.

A clear demonstration: an attack on Bitcoin’s weak PRNG is not just an abstract threat, but the cause of real-world thefts, documented under CVE numbers such as CVE-2025-27840 and CVE-2018-0734. Only a rigorous transition to cryptographically strong generators and continuous auditing of software and hardware can preserve the security of funds and the integrity of the Bitcoin system in the age of global digital threats. kudelskisecurity+3

Target area: generating cryptographic secrets via a legacy or insecure PRNG.
Method: Partial capture of output data to reconstruct the internal state of the generator.
Result: compromise of private keys and complete breach of cryptosystem security.

An attacker analyzes the output sequence, “splitting” the pseudo-random stream like light through a prism, to reveal internal patterns or exploit the lack of entropy to fully recover the application’s private secrets.

Quantum Prism Extractor Attack —a “prism” that filters a stream of random data, splits it into its components, and ultimately “extracts” hidden secrets from a weak source of randomness. The name evokes the vivid image of refracted light and powerful technological impact on a cryptographic system.

Critical Vulnerability in Random Number Generators: A Fatal Attack on Bitcoin Private Keys and Catastrophic Consequences for the Ecosystem

Research paper: Critical PRNG vulnerability in Bitcoin and attack on private keys

The security of the Bitcoin cryptocurrency fundamentally depends on reliable random number generation for creating private keys and signing transactions. A weak or vulnerable random number generator (PRNG) compromises wallets, transactions, and the trust in the blockchain. One of the most dangerous attacks of this class is an attack on the weak entropy of the generator, scientifically known as an ECDSA Nonce Reuse Attack or Weak Randomness Attack on ECDSA. sciencedirect+2

How does vulnerability arise?

The vulnerability occurs when a weak PRNG or a faulty generator (such as FastRandomContext) is used to generate private keys or temporary numbers (nonces). If an attacker is able to partially observe or predict the generator’s output, they can recover the private key using the mathematical properties of the signatures (ECDSA). keyhunters+1

A classic mistake is using the same nonce or insufficiently random nonces for multiple transaction signatures. In this case, by analyzing signatures, an attacker obtains all the parameters necessary to extract the address owner’s private key and subsequently steal funds.

Scientific name of the attack

ECDSA Nonce Reuse Attack
Weak Randomness Attack on ECDSA (weak entropy/predictable nonce attack)
PRNG Attack (attack on a random number generator)
In some cases it is referred to as Cryptographic Key Leakage Attack or Birthday Attack (in case of collisions during key generation). cqr+2

Paths and consequences of attacks on the Bitcoin ecosystem

Complete compromise of users’ private keys (full access to addresses and transfers)
Mass thefts of funds from vulnerable wallets/devices (especially hardware with bad RNG)
Cryptographic weakening and mass failure of entire wallet platforms and forks due to duplicate or weakly random keys
The possibility of attacking historical signatures and old transactions with vulnerable code (example: Bitcoin wallets on ESP32, vulnerability CVE-2025-27840). keyhunters+1

Registered CVE numbers for this vulnerability

CVE-2025-27840 is a critical vulnerability in the random number generator on the ESP32 that allowed the recovery of Bitcoin wallet private keys (this vulnerability applies to hardware wallets, but is essentially equivalent for all weak entropy scenarios). bits+2
CVE-2020-28498 and CVE-2018-0734 are similar vulnerabilities involving nonce generation errors for signatures, leading to the disclosure of private keys through signature analysis .
CWE-338 is a general classification of such vulnerabilities: “Use of a Cryptographically Weak Pseudo-Random Number Generator (PRNG)”. cwe.mitre+2

Scientific mechanism of occurrence

In ECDSA, each transaction is signed with a unique random number (nonce, kkk). If the nonce is known, repeated, or has low entropy, an attacker can calculate the private key ddd using the formula: d = s⋅k−H(m)rmod nd = \frac{s \cdot k — H(m)}{r} \mod nd = rs⋅k−H(m)modn

where s, rs, rs, r are the signature elements, H(m)H(m)H(m) is the message hash, and nnn is the order of the secp256k1 curve. Thus, the entire security of the signature, and therefore the user’s funds, comes down to the security of the random number generation process. sciencedirect+1

Conclusion

Cryptographic vulnerability in the code

Summary: The vulnerability lies in the use of an insecure pseudo-random number generator FastRandomContext, which can lead to predictability of “random” values and potential leakage of sensitive data.

Detailed analysis

In the proposed code fragment, the unsafe random source is initialized with the following line:

cpp:

FastRandomContext insecure_rand(true);

– this line is located on line 49 of the file (taking into account the line count given below).

Why is it vulnerable?

Unsuitable for cryptographic tasks,
FastRandomContext the generator is not cryptographically secure. It is designed to generate high-performance but predictable pseudorandom numbers within a node. Using it for any operations involving secret keys or arbitrary values may make it possible to recover the generator’s state and predict future “random” numbers.
Predictability and Leakage
When initialized with , truethe internal entropy may be insufficient and/or fixed, allowing an attacker to gain access to part of the PRNG output and recover the remaining values, including potentially generated secret data.
Context of use
In this example, the generator is used to:
- Size definitions prevectorin the constructorPrevectorJob
- Re-initialization insecure_randwithin each benchmark run
If a similar design were to use a generator to directly generate ECDSA keys or other cryptographic parameters, it would have serious consequences for leakage and compromise of private keys.

Recommendations

For any operations involving cryptography or secret keys, a cryptographically strong generator ( GetRandBytes, CSecRandom, or wrappers over OS generators) should be used.
Never use FastRandomContextto generate secret values or unpredictable parameters.
Clearly distinguish between: FastRandomContextcrypto generators for non-security-critical tasks and crypto generators for all secret operations.

KeyCracker: Exploiting PRNG Weakness for Bitcoin Private Key Extraction

KeyCracker is a specialized cryptanalytic tool designed to automate the identification, analysis, and exploitation of critical vulnerabilities in weak or predictable pseudorandom number generators (PRNGs) utilized within Bitcoin wallet systems. By leveraging mathematical methods to detect ECDSA signatures with reused or low-entropy nonces, KeyCracker enables attackers or forensic analysts to extract private keys from compromised wallets, directly addressing the catastrophic consequences outlined in the Quantum Prism Extractor Attack. This article details the tool’s operating principles, its interaction with core Bitcoin vulnerabilities, and the impact such exploits can have on large-scale cryptocurrency security.

Introduction

Modern Bitcoin wallet security fundamentally depends on the unpredictability and entropy of random numbers used during cryptographic operations. The Quantum Prism Extractor Attack demonstrates that exploitation of weak PRNGs can lead to full compromise of private keys, jeopardizing the security, integrity, and trust of the Bitcoin ecosystem. KeyCracker is engineered to target precisely these scenarios, providing a robust framework for mathematical extraction of secrets from weak randomness in ECDSA-based Bitcoin systems.

Mechanism of Operation

KeyCracker automates the following workflow:

Collection and indexing of raw transaction data, focusing on signatures produced by potentially vulnerable clients or hardware platforms.
Signature correlation analysis, robustly identifying cases of nonce reuse or weak entropy where the underlying random generator fails to provide cryptographic security.
Mathematical key recovery, applying algebraic attacks (e.g., solving for discrete logarithms in ECDSA under nonce repetition) to determine the private key from signature parameters: d=s⋅k−H(m)r mod nd = \frac{s \cdot k – H(m)}{r} \bmod nd=rs⋅k−H(m)modn where sss, kkk, H(m)H(m)H(m), rrr, and nnn are signature and curve parameters as described in quantum PRNG vulnerability literature.

Cryptographic Vulnerability Context

Bitcoin’s security model is catastrophically undermined by any reuse or predictability of ECDSA nonces. KeyCracker exploits several real-world weaknesses, including:

PRNG design flaws (FastRandomContext and similar generators in wallet software);
Hardware entropy failures (e.g., ESP32 vulnerabilities, CVE-2025-27840);
Implementation mistakes, especially in RFC6979-based deterministic nonce algorithms.

These lead to repeated nonces, low entropy, and ultimately, to analytically recoverable keys for attackers with network access and mathematical tooling.

Recovery of Lost Wallets

KeyCracker’s practical impact lies in its ability to:

Scan blockchain data for signatures with repeated or weak nonces;
Recover the original private key for each compromised wallet, facilitating forensic recovery or illicit withdrawals;
Enable security researchers to demonstrate the scope of vulnerability and accelerate remediation by quantifying the risk profile for affected users.

This capability is especially poignant for owners of “lost” Bitcoin wallets compromised by historic bugs or entropy failures, providing a pathway for lawful restoration (upon proof of ownership) or improving forensics in theft cases.

Implications for Bitcoin Security

A single PRNG vulnerability, if widespread, can be exploited at scale by automated tools like KeyCracker, resulting in:

Mass theft events and erasure of trust in the system;
Emergence of large-scale wallet failure across forks or platforms sharing the same flawed generator;
Urgent requirement for wallet maintainers to adopt robust CSPRNGs and continuously audit their codebases.

The historical track record, documented under critical CVEs, highlights the urgent need for cryptographic diligence.

Recommendations and Future Scope

Developers and maintainers must rigorously enforce:

Exclusive use of OS-based or hardware-secure CSPRNGs for any cryptographic secret generation;
Explicit rejection of classic PRNGs (e.g., std::rand, FastRandomContext) in any security-critical context;
Regular auditing with tools such as KeyCracker for early detection and mitigation of impending cryptographic disaster.

KeyCracker embodies the technical response to Quantum Prism Extractor vulnerabilities and should be a staple in any wallet security audit.

Conclusion

KeyCracker’s design directly answers the Quantum Prism Extractor Attack’s challenge: in a world where PRNG flaws threaten entire cryptocurrencies, automated detection and recovery through targeted mathematical attacks are an essential asset. The tool’s deployment is a call to action for the Bitcoin security community, underlining the catastrophic consequences of neglected randomness and offering a scientific roadmap for mitigation, recovery, and continuous improvement.

Research paper: The Quantum Prism Extractor vulnerability in cryptographic systems and recommendations for its elimination

Introduction

In today’s world of cryptocurrency and financial technology security, the quality of random number generators (PRNGs) used plays a key role. Flaws in PRNG implementations can lead to the compromise of private keys and complete system compromise. A striking example is the “Quantum Prism Extractor” attack, which exploits weaknesses in insecure PRNGs within critical functions in applications such as Bitcoin Core (see the generated image above). cryptobook.nakov+1

Description of the vulnerability occurrence

The vulnerability occurs when a non-cryptographic or weak random number generator (such as FastRandomContext) is used to generate private keys, temporary data, or other secret parameters. This allows an attacker to use partial observable outputs of the generator to predict future values or reconstruct the PRNG’s internal state, which in many cases allows the recovery of the user’s private keys. wikipedia+1

Example of unsafe code

cppFastRandomContext insecure_rand(true);
privateKey = insecure_rand.rand256(); // Генерация приватного ключа с некриптостойким генератором

A classic PRNG, lacking sufficient entropy and security, is unable to resist targeted analysis of its output, which is exploited in the “Quantum Prism Extractor” attack. This type of attack is based on “refraction” (analysis and decomposition) of the PRNG output stream, allowing one to determine or reconstruct its initial state, thereby fully identifying private data, such as cryptographic wallet keys.

Consequences of exploitation

Compromise of user’s private keys and wallets.
Possibility of unauthorized transactions.
Loss of funds and confidence in infrastructure.
Distribution of vulnerable libraries and development tools.

A safe way to fix the vulnerability

To eliminate this class of vulnerabilities, all operations involving the generation of sensitive data must use only cryptographically secure pseudorandom number generators (CSPRNGs). These utilize the operating system’s entropy sources and special algorithms that ensure that their internal state cannot be reconstructed even if the data is partially disclosed .

Safe code example for C++

cpp#include <random>
#include <array>
#include <fstream>

// Использование /dev/urandom или /dev/random для генерации ключа
std::array<uint8_t, 32> generateSecurePrivateKey() {
    std::array<uint8_t, 32> key {};
    std::ifstream urandom("/dev/urandom", std::ios::in|std::ios::binary);
    if (!urandom) throw std::runtime_error("Не удалось открыть /dev/urandom");
    urandom.read(reinterpret_cast<char*>(key.data()), key.size());
    if (urandom.gcount() != key.size()) throw std::runtime_error("Ошибка чтения");
    return key;
}

This method ensures that the private key or other secret values are generated by sources of true (or near-true) entropy, which is impossible to predict. paragonie+3

Recommendations for developers

Always use a CSPRNG to generate cryptographic keys and secrets.
Never rely on standard library generators (e.g. std::rand, FastRandomContext) unless they are specifically stated to be cryptographically secure.
Regularly audit your source code and third-party dependencies for CSPRNG use.
Follow recommendations on PRNG cryptographic strength in current standards and whitepapers. cryptobook.nakov+1

Conclusion

The Quantum Prism Extractor attack demonstrates the critical importance of using only cryptographically secure random number generators. By guaranteeing high entropy and the impossibility of predicting or reconstructing the generator’s internal state, modern CSPRNGs protect users from compromising private secrets, preserving the trust and security of cryptographic systems.

The final conclusion of the scientific article

Links:
– Secure PRNG principle cryptobook.nakov
– Requirements for crypto-resistant PRNGs wikipedia
– Modern design of secure generators nature
– Criteria for crypto-resistant generators for cryptocurrencies reddit
– An example of secure random number generation in C/C++ paragonie

Key links:
— ECDSA weak randomness in Bitcoin sciencedirect
— ECDSA Private Key Recovery Attack via Nonce Reuse keyhunters
— CWE-338 (Use of Cryptographically Weak PRNG) cwe.mitre
— CVE-2025-27840 (hardware implementation, applies to Bitcoin wallets, esp32) cryptorank+2
— Random number generator attack classification feedly+2