Memory Safety ≠ Smart Contract Safety: Why Solana Programs Still Need Audits

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Introduction – Call Out the Myth

"Rust is safe, so audits are unnecessary."

This dangerous belief could cost you millions in lost funds. Memory safety doesn't protect you from logical flaws that can compromise your protocol's security.

You're not getting hacked because of memory issues; you're getting hacked because your logic is flawed.

In the fast-changing Solana ecosystem and various rust based ecosystems, developers often put too much trust in Rust's safety features. While Rust's memory safety is strong, it's just one layer of protection in the complex security world of blockchain protocols. The facts are clear: despite Rust's safety features, Solana has experienced over $1 billion in exploits across various protocols—none of which were due to memory corruption.

What Rust Actually Protects You From

Rust's compiler is an impressive piece of engineering. It enforces a strict ownership model that eliminates entire classes of bugs that plague other systems programming languages. To understand why Rust is widely considered "safe," let's examine what specific memory safety issues it prevents and how it compares to languages like C and C++.

Memory Safety Guarantees in Rust vs. C/C++

Buffer Overflows

Buffer overflows occur when a program writes more data to a buffer than it can hold, potentially overwriting adjacent memory.

C/C++ (Vulnerable):

Why this is dangerous: In C/C++, there's no automatic bounds checking when writing to arrays. When strcpy() copies the long string into the small buffer, it writes past the allocated 10 bytes, corrupting adjacent memory. This can overwrite other variables, return addresses, or function pointers, potentially allowing attackers to execute arbitrary code. The program might crash, produce incorrect results, or continue with corrupted memory, making the behavior unpredictable and exploitable.

Rust (Safe):

How Rust prevents it: Rust's standard library implements bounds checking for all array accesses. The copy_from_slice() method requires that the source and destination slices have the same length, enforced at compile time when possible and runtime otherwise. If you try to access an array out of bounds with indexing, Rust will panic (crash safely) rather than allowing memory corruption. This is enforced by the compiler and runtime, making buffer overflows impossible without using unsafe code.

Use-after-free

Use-after-free occurs when a program continues to use memory after it has been freed, leading to unpredictable behavior.

C++ (Vulnerable):

Why this is dangerous: When create_and_return_dangling_pointer() returns, the local variable local_var goes out of scope and its memory on the stack is reclaimed. However, the function returns a pointer to this now-invalid memory location. When main() dereferences this pointer, it's accessing memory that might now contain different data or be used by another function. This can lead to data corruption, crashes, or security vulnerabilities if an attacker can manipulate what data ends up in that memory location.

Rust (Safe):

How Rust prevents it: Rust's borrow checker tracks the lifetime of every reference to ensure it never outlives the data it points to. The compiler analyzes the code and enforces rules about how long references can exist. In this example, trying to return a reference to a local variable would cause a compile-time error because the reference would outlive the variable. The borrow checker forces you to either return an owned value (transferring ownership) or ensure the reference points to data with a lifetime at least as long as the reference itself.

Data Races

Data races occur when multiple threads access the same memory location concurrently, with at least one thread writing to it, without proper synchronization.

C++ (Vulnerable):

Why this is dangerous: The operation shared_counter++ is not atomic; it involves reading the value, incrementing it, and writing it back. When two threads perform this operation concurrently, they might both read the same initial value, increment it independently, and then both write back the same incremented value, effectively losing one of the increments. This leads to race conditions where the final result depends on the timing of thread execution. Data races can cause subtle bugs that are hard to reproduce and debug, potentially leading to data corruption or security vulnerabilities.

Rust (Safe):

How Rust prevents it: Rust's ownership system prevents data races at compile time through its ownership and borrowing rules. The type system enforces that either:

1. Multiple threads can have immutable (read-only) references to the same data, or
2. A single thread can have one mutable reference to the data

When shared mutable state is needed across threads, Rust requires explicit synchronization primitives like Mutex or RwLock. The Arc (Atomic Reference Counting) type safely shares ownership across threads, while Mutex ensures only one thread can access the data at a time. The compiler enforces that you can't access the data without acquiring the lock, making data races impossible without using unsafe code.

Null Pointer Dereferencing

Null pointer dereferencing occurs when a program attempts to access memory through a null pointer, typically causing a crash.

C++ (Vulnerable):

Why this is dangerous: In C/C++, dereferencing a null pointer is undefined behavior, typically resulting in a program crash (segmentation fault). However, on some systems or in certain contexts, it might not immediately crash but instead access invalid memory, potentially leading to data corruption or security vulnerabilities. Null pointer dereferences are a common source of crashes and can be exploited by attackers to cause denial of service or, in some cases, execute arbitrary code.

Rust (Safe):

How Rust prevents it: Rust doesn't have null pointers in the traditional sense. Instead, it uses the Option<T> enum to represent the presence or absence of a value. To access the value inside an Option, you must explicitly handle both the Some case (value exists) and the None case (no value). The compiler enforces this pattern matching, making it impossible to accidentally "dereference" a None value. This eliminates an entire class of bugs and security vulnerabilities related to null pointer dereferences.

The Borrow Checker: Rust's Secret Weapon

The core of Rust's memory safety is the borrow checker, which enforces strict rules on how references are used:

1. Ownership: Each value has one owner variable.
2. Borrowing: References to a value must not last longer than the owner.
3. Mutability: You can have either one mutable reference or multiple immutable references, but not both at the same time.
   

These rules are enforced at compile time, preventing entire categories of memory safety bugs before the code even runs. The borrow checker analyzes the flow of ownership and references throughout your program, ensuring that references are always valid and that memory is properly managed.

"Rust's compiler helps you write memory-safe programs. But memory safety is only one layer of actual protocol safety."

The Solana Security Gap: Why Memory Safety Isn't Enough

While Rust prevents memory corruption, Solana smart contracts face a completely different class of vulnerabilities. The Solana programming model introduces unique security challenges that Rust's memory safety features simply don't address:

1. Account-based architecture: Solana's account model requires explicit validation of account relationships and permissions
2. Cross-Program Invocation (CPI): Interactions between programs create complex trust boundaries
3. Program Derived Addresses (PDAs): Proper derivation and validation of PDAs is critical for security
4. Serialization/deserialization: Proper handling of account data requires careful validation
5. Instruction ordering: Multi-instruction transactions can create complex state transitions
6. Token Accounts : Usage of token accounts and associated token accounts correctly

None of these Solana-specific concerns are addressed by Rust's memory safety guarantees. Let's examine the most common vulnerabilities that have led to actual exploits in the wild.

Common Solana Bugs Rust Won't Catch

Authority Mistakes

Smart contracts often implement privileged functionality that should only be accessible to authorized users. Rust's type system can't verify that you've properly checked that the correct authority signed a transaction.

A single missing authority check can lead to complete protocol compromise, allowing attackers to modify critical protocol parameters. This vulnerability has been exploited repeatedly in the wild, leading to millions in losses.

Insecure CPIs

Cross-Program Invocations (CPIs) are a fundamental part of Solana's composability. However, Rust can't verify that you're calling the correct program or passing the right accounts.

An attacker could exploit this vulnerability by passing a malicious program that mimics the expected behavior but steals funds. This is known as a "confused deputy" attack and has been responsible for several high-profile exploits in the Solana ecosystem.

Mishandled Token Accounts Authority

Token accounts in Solana require careful validation. Rust's type system doesn't verify that a token account belongs to the expected mint or owner.

Without proper validation, an attacker could pass a token account for a different (possibly worthless) token and trick your program into treating it as the expected token. This exact vulnerability led to the $52 million Cashio hack in March 2022.

Missing Signer Checks

Solana programs must explicitly verify that critical operations are authorized by the appropriate signer. Rust's compiler can't detect when you've forgotten this crucial check.

A missing signer check can allow unauthorized withdrawals, potentially draining all funds from a protocol. This vulnerability is so common that it's one of the first things to check in a Solana audit.
For example, even if the admin key was verified, there was a missing requirement that the admin needed to be the signer. Without this, anyone could simply use the admin's public key and exploit the system.

State Desync Across Instructions

When a program interacts with other programs via CPIs, account state can change. Rust doesn't automatically reload account data after CPIs, leading to state desynchronization, neither the use of anchor does it.

Without reloading, your program operates on stale data, potentially leading to incorrect calculations or security bypasses.

Why does it happen?
Solana's account model takes a snapshot of data in memory when an instruction begins. If another program changes this data through a Cross-Program Invocation (CPI), the deserialized structures don't automatically update. Therefore, in Anchor, you need to use the reload() function on Account<T> to refresh the lamports, data, and owner fields from storage to the in-memory copy. These structures use Rc<RefCell<&mut [u8]>>, but they don't automatically refresh after a CPI, so any direct reads will still show the original snapshot. Without using reload(), reading token balances or custom state will show outdated information, leading to logic errors or violations when calculating balances after transfers. When you call reload() on AccountInfo or Account<T>, it fetches the latest data, re-deserializes it, and updates the lamport and owner fields, ensuring that future operations reflect the true on-chain state.

Account Type Confusion

Solana programs often define multiple account types for different purposes. Without proper type checking, one account type could be substituted for another.

Without proper type checking, an attacker could pass an account of one type where another is expected, potentially bypassing security checks. Anchor handles this automatically with its account discriminators, but native Solana programs must implement these checks manually.

PDA Validation Failures

Program Derived Addresses (PDAs) are a fundamental concept in Solana, allowing programs to control accounts deterministically. However, Rust doesn't verify that PDAs are derived correctly or validated properly.

Without proper PDA validation, an attacker could pass a different account than expected, potentially gaining unauthorized access to program functionality. This vulnerability has been exploited in multiple Solana hacks.

Unsafe Account Reallocation

Reallocating account data requires careful memory management to avoid security issues.

Improper memory handling during reallocation can lead to data corruption, use of uninitialized memory, or leaking sensitive data from previous memory usage.

Arithmetic Safety Issues

Rust's arithmetic operations can overflow or underflow in release mode, which is what Solana uses.

Integer overflows and underflows can lead to security vulnerabilities, such as bypassing balance checks or causing incorrect calculations. Always use checked arithmetic operations in Solana programs.

Using the latest version of Anchor or creating a new Solana project with new version of can help prevent these issues by including the attribute overflow-checks=true in the Cargo.toml. However, you need to ensure this attribute is present in the codebase.

Lamports Transfer Vulnerabilities

When transferring SOL (lamports) from PDAs, you must ensure the account remains rent-exempt.

If a PDA falls below the rent-exempt threshold, it could be purged by the runtime, leading to loss of program state and potential security issues.

Instruction Ordering Vulnerabilities

Solana allows multiple instructions to be executed in a single transaction. Rust can't verify that your program handles instruction ordering correctly.

Without proper validation in each instruction, an attacker could chain instructions in unexpected ways, potentially bypassing security checks. This vulnerability has been exploited in multiple Solana hacks.

Understanding Anchor: Benefits and Limitations

What is Anchor?

Anchor is a framework for Solana program development that aims to simplify the process and reduce common security vulnerabilities. It provides a set of macros, traits, and abstractions that make writing Solana programs more ergonomic and less error-prone.

Key features of Anchor include:

1. Account validation: Automatic validation of account constraints
2. Serialization/deserialization: Simplified handling of account data
3. Error handling: Standardized error types and handling
4. Program organization: Structured approach to program architecture
5. Type safety: Enhanced type checking for Solana-specific concepts

Anchor has become the de facto standard for Solana program development, with most new projects using it instead of writing native Solana programs directly.

The Technical Details of Anchor's Account Handling

Anchor's account handling is one of its most powerful features. Let's dive into the technical details of how it works:

Account Serialization and Deserialization

In native Solana programs, you need to manually serialize and deserialize account data. Anchor automates this process through its #[account] macro:

Under the hood, the #[account] macro implements the AccountSerialize and AccountDeserialize traits for your struct, which handle the serialization and deserialization of account data. It also adds an 8-byte discriminator at the beginning of the account data to identify the account type.

Account Wrapping and Unwrapping

Anchor's Account<'info, T> type is a wrapper around Solana's AccountInfo that provides type-safe access to account data. Let's look at how this wrapper works:

When you use Account<'info, T> in your program, Anchor performs several checks:

1. It verifies that the account is owned by the expected program
2. It checks that the account data begins with the correct 8-byte discriminator
3. It deserializes the account data into the specified type
4. It provides type-safe access to the account data
5. It automatically serializes any changes back to the account when the instruction completes

This wrapping and unwrapping process happens automatically when you use Anchor's Context type, which is passed to your instruction handlers.

Account Constraints

Anchor's #[derive(Accounts)] macro allows you to specify constraints on accounts that are automatically checked before your instruction handler is called:

These constraints are expanded into code that runs before your instruction handler:

This automatic validation eliminates many common sources of bugs and security vulnerabilities in Solana programs.

Why Anchor Doesn't Fix All Security Issues

While Anchor significantly improves the development experience and eliminates many common sources of bugs, it's not a security panacea.

Misused #[account] Constraints

Anchor's account constraints are powerful but can be misused or misunderstood:

Missing the mut constraint will cause the transaction to fail at runtime when trying to modify the account, but this isn't caught at compile time.

Incomplete Validation Logic

Anchor automates many common validations, but it can't anticipate all the business logic specific to your protocol:

Anchor constraints handle basic validations, but you still need to implement comprehensive checks in your instruction handlers.

Over-trusted ctx.accounts.xyz Access

Developers often assume that if an account passes Anchor's validation, it must be safe to use:

Anchor's account constraints are a starting point, not a complete security solution.

Remaining Accounts Validation

Anchor's ctx.remaining_accounts feature allows for passing a variable number of accounts to instructions, but these accounts bypass Anchor's automatic validation:

Without proper validation, an attacker could pass malicious accounts through remaining_accounts to bypass security checks.

Initialization and Reinitialization Vulnerabilities

Anchor's init constraint helps with account initialization, but reinitialization attacks are still possible:

The init_if_needed constraint can be dangerous if not carefully validated, potentially allowing an attacker to reinitialize an account with malicious data.

What an Audit Actually Looks Like (for Solana)

A comprehensive Solana program audit goes far beyond what the Rust compiler or Anchor framework can verify:

State Machine Validation

Auditors analyze your program's state transitions to ensure they're secure and consistent:

• Identifying invalid state transitions
• Verifying state invariants are maintained
• Ensuring proper initialization and finalization of state
• Identify the correct usage of every instruction

Instruction Sequencing Logic

Auditors examine how your instructions can be combined or ordered:

• Testing instruction sequences for unintended consequences
• Identifying transaction ordering vulnerabilities
• Checking for replay attack vectors
• Verifying proper handling of concurrent transactions in case of cross-chain transfers

Many exploits involve calling instructions in an unexpected order or combining them in ways the developers didn't anticipate. Auditors simulate these scenarios to identify potential vulnerabilities.

CPI Chain Behavior

Auditors analyze how your program interacts with other programs:

• Validating program IDs in CPIs
• Checking for confused deputy vulnerabilities
• Verifying proper account validation before CPIs
• Ensuring state is properly reloaded after CPIs

Cross-program invocations are a common source of vulnerabilities in Solana programs. Auditors trace through CPI chains to identify potential attack vectors.

Simulations & Fuzzing for Multi-step Flows

Auditors use advanced testing techniques to find edge cases:

• Fuzzing instruction parameters to find unexpected behaviors
• Simulating complex transaction sequences
• Testing boundary conditions and error paths
• Identifying economic attack vectors

These techniques can uncover vulnerabilities that are difficult to find through manual code review, such as the complex price manipulation attack that led to the Mango Markets exploit.

Case Studies: Real Solana Exploits

Loopscale Hack (April 2025)

In April 2025, the Loopscale protocol was exploited for $5.8 million due to a critical flaw in how the protocol calculated the value of RateX PT tokens. This exploit demonstrates how even in 2025, logical vulnerabilities in smart contracts continue to plague Solana programs despite the memory safety guarantees of Rust.

Loopscale is a DeFi lending protocol on Solana designed to enhance capital efficiency by directly matching lenders and borrowers through an order book model. The protocol supports specialized lending markets, including structured credit and undercollateralized lending.

The vulnerability stemmed from a fundamental error in the protocol's price oracle implementation. Let's examine the vulnerable code:

The critical vulnerability was in the calculate_token_value function, which failed to properly validate that:

1. The price oracle was the correct one for the specific token type
2. The price calculation didn't account for the unique characteristics of RateX PT tokens
3. There was no validation of price staleness or manipulation resistance

The attacker exploited this vulnerability by:

1. Creating a position with RateX PT tokens as collateral
2. Manipulating the perceived value of these tokens due to the incorrect price calculation
3. Taking out undercollateralized loans worth more than the actual value of the collateral
4. Withdrawing approximately 5.7 million USDC and 1,200 SOL from the protocol's Genesis Vaults

Here's what a more secure implementation would look like:

This exploit highlights several critical lessons for Solana developers:

1. Proper price oracle validation: Always verify that price oracles are appropriate for the specific token type and implement safeguards against manipulation.
2. Token-specific valuation logic: Different token types may require specialized valuation formulas, especially for derivative tokens like RateX PT.
3. Comprehensive account validation: Ensure all accounts passed to your program are validated for correctness and ownership.
4. Safety margins: Implement conservative haircuts and safety margins when calculating collateral values to account for market volatility and potential oracle inaccuracies.
5. Thorough testing of economic assumptions: Test your protocol's economic model under various market conditions and edge cases to identify potential vulnerabilities.

After detecting the exploit, Loopscale temporarily halted lending markets and withdrawals. The team sent on-chain messages to the exploiter offering a 10% bug bounty in exchange for immunity from prosecution. Remarkably, the attacker accepted the offer and returned the stolen funds to the protocol, resulting in no permanent losses to Loopscale users.

This incident demonstrates that even in 2025, with years of ecosystem maturity, logical vulnerabilities in smart contracts remain a significant threat. Rust's memory safety features couldn't prevent this exploit because it was a flaw in the business logic rather than a memory corruption issue.

Wormhole Bridge Exploit (February 2022)

Wormhole Bridge Exploit (February 2022)

On February 2, 2022, the Wormhole bridge on Solana was exploited for 120,000 ETH (worth approximately $320 million at the time), making it one of the largest DeFi hacks in history. The vulnerability stemmed from a critical developer mistake in the signature verification process.

The root cause was a logical flaw: the contract used load_instruction_at—a deprecated helper that doesn’t verify the account’s program ID—to check that Secp256k1 signature verification was invoked, allowing the attacker to substitute a fake Sysvar account. As a result, verify_signatures was never truly validated against the real Sysvar::instructions account, and the attacker could bypass signature checks entirely.

The remedy is twofold:

(1) use load_instruction_at_checked to ensure the account is the genuine Instructions sysvar

(2) perform an explicit guardian‐set‐quorum check before minting.

load_instruction_at simply reads an instruction at a given index but does not verify that the account is actually the Sysvar::instructions account ([Halborn][1]).

The code delegated signature checks via verify_signatures, but never enforced that enough guardian signatures (2/3 of the set) were processed. An attacker could skip this entirely if the prior sysvar check is subverted.

Vulnerable Snippet

• What it does wrong:
  • Uses load_instruction_at instead of a checked variant
  • Omits any call to verify_signatures on the VAA

Secure Snippet

Here's the transaction where the attacker exploited the vulnerability: Solana transaction details | Solscan

Developer Mistakes and Lessons Learned

This exploit highlights several critical lessons for Solana developers:

1. Always validate account ownership and identity: The primary mistake was failing to verify that the sysvar account was actually the legitimate system sysvar. Always validate that accounts are owned by the expected program and have the expected address.
2. Be cautious with deprecated functions: The load_current_index function was deprecated but still in use. When using deprecated functions, ensure they're still secure or replace them with more secure alternatives.

The Wormhole exploit demonstrates that even a single missing validation check in a security-critical function can lead to catastrophic losses. This vulnerability had nothing to do with Rust's memory safety features—it was a logical flaw in the program's security model.

Cashio Hack (March 2022)

In March 2022, the Solana-based stablecoin protocol Cashio suffered a catastrophic exploit, resulting in the unauthorized minting of approximately 2 billion $CASH tokens and a loss exceeding$52 million. The root cause was a critical flaw in the protocol's collateral validation mechanism, which allowed an attacker to mint unlimited $CASH tokens and a loss exceeding $52 million. The root cause was a critical flaw in the protocol's collateral validation mechanism, which allowed an attacker to mint unlimited CASH tokens using worthless collateral.

Cashio's architecture comprised two primary programs:

• Bankman: Manages collateral types and tracks banks.
• Brrr: Handles the minting and burning of $CASH tokens

To mint $CASH, users were required to deposit Saber LP tokens (specifically, USDC-USDT LP tokens) as collateral. The protocol was supposed to validate the authenticity of these tokens and ensure they matched the expected collateral type.

However, the attacker identified critical flaws in the validation process:

• Fake Bank Creation: The attacker created a counterfeit bank account using the crate_mint function. This fake bank was associated with a worthless token controlled by the attacker.
• Bypassing Collateral Checks: The crate_collateral_tokens function lacked proper validation to ensure that the deposited collateral matched the expected token type. Specifically, it failed to verify the mint field within the saber_swap.arrow account.
• Infinite $CASH Minting: By depositing the worthless tokens into the fake bank, the attacker could mint an unlimited supply of $CASH tokens without any real collateral.

This function was intended to validate the relationship between the bank and collateral accounts.

The function failed to verify the authenticity of the bank account, allowing the attacker to supply a fake bank associated with a counterfeit token.

This function was responsible for validating the Saber swap accounts.

The function did not verify that the saber_swap.mint matched the expected mint, enabling the attacker to use a fake Saber swap account with a counterfeit mint.

The Cashio exploit demonstrates that missing validation checks in collateral handling can lead to catastrophic losses in DeFi protocols. This vulnerability had nothing to do with Rust's memory safety features—it was a logical flaw in the protocol's security model.

Solend Exploit (November 2, 2022)

On November 2, 2022, the Solend lending protocol suffered a $1.26 million exploit due to a vulnerability in its price oracle implementation. The attacker manipulated the price of the USDH stablecoin, allowing them to borrow assets against inflated collateral value.

Technical Details of the Vulnerability

Solend's price oracle for USDH relied solely on data from the Saber decentralized exchange (DEX). This single-source dependency created a vulnerability, as it allowed an attacker to manipulate the USDH price without interference from other market data sources.

Execution Steps

1. Initial Attempt (October 28, 2022): The attacker injected 200,000 USDC into the Saber pool to inflate USDH's price. However, arbitrageurs corrected the price within the same slot, nullifying the attempt.
2. Successful Exploit (November 2, 2022):
   • Price Inflation: The attacker used 100,000 USDC to inflate USDH's price on Saber.
   • Slot Spamming: They flooded the Saber account with transactions, preventing arbitrageurs from correcting the price within the same slot.
   • Oracle Update: The manipulated price was captured by Switchboard, Solend's oracle provider.
   • Asset Borrowing: Using the inflated USDH as collateral, the attacker borrowed assets from Solend's Stable, Coin98, and Kamino pools.

A more secure implementation would have included multiple price sources and safeguards against manipulation:

Developer Mistakes and Lessons Learned

The Solend exploit highlights several critical lessons for Solana developers:

1. Never rely on a single price source: The primary mistake was relying solely on Saber's pool for USDH pricing. Always use multiple independent price sources and implement mechanisms like median pricing to resist manipulation or use oracles like pyth.
2. Implement price bounds for stablecoins: Stablecoins should have strict price bounds (e.g., $0.95 to $1.05) to prevent extreme price movements from being accepted by the protocol.

The Solend exploit demonstrates that even sophisticated DeFi protocols can be vulnerable to oracle manipulation if proper safeguards aren't implemented. This vulnerability had nothing to do with Rust's memory safety features—it was a design flaw in the protocol's oracle implementation.

Conclusion – Rust Is a Tool, Not a Shield

Rust is an excellent language for blockchain development. Its memory safety guarantees eliminate entire classes of vulnerabilities that plague other systems programming languages. But memory safety is just one aspect of smart contract security.

Anchor further improves the development experience by providing a structured framework and automating common validations. However, it can't anticipate all the specific security requirements of your unique protocol.

Logic safety, permission design, and state guarantees still require human review. The most dangerous vulnerabilities in Solana programs aren't memory corruption issues but logical flaws in the protocol design and implementation:

• Missing authority checks
• Improper account validation
• Insecure cross-program invocations
• Flawed business logic
• State synchronization issues

These vulnerabilities can only be identified through comprehensive security audits conducted by experts who understand both the Solana programming model and common blockchain security patterns.

Don't rely solely on Rust's compiler or Anchor's constraints to secure your protocol. Invest in thorough testing, code reviews, and professional security audits before deploying your Solana program. Your users' funds depend on it.

Remember: Memory safety ≠ smart contract safety. The most secure Solana programs combine Rust's powerful safety features with rigorous security reviews and comprehensive testing.

References

• Immunebytes. (2022). "Wormhole Bridge Hack – Feb 2, 2022 – Detailed Hack Analysis"
• CertiK. (2022). "Wormhole Bridge Exploit Incident Analysis"
• Extropy.IO. (2022). "Solana's Wormhole Hack Post-Mortem Analysis"
• Halborn. (2022). "Explained: The Cashio Hack (March 2022)"
• CertiK. (2022). "Cashio App Incident Analysis."
• Ackee Blockchain. (2023). "2022 Solana Hacks Explained: Cashio."
• Immunebytes. (2022). "Mango Markets Exploit—Oct 11, 2022—Detailed Analysis."
• CollinsDeFiPen. (2025). "History of Solana Security Incidents: A Deep Dive."
• Messari. (2025). "Analyzing the Loopscale Hack."
• Halborn. (2025). "Explained: The Loopscale Hack (April 2025)."
• Cointelegraph. (2025). "Solana's Loopscale pauses lending after $5.8M hack."
  

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