Security

Property-Based Testing

A testing methodology where developers define properties (invariants) that must hold true for all valid inputs, and a test framework generates random inputs to attempt to falsify those properties. Unlike unit tests that check specific examples, property-based testing explores the input space stochastically. For Solana programs, properties might include 'total token supply never changes during transfers' or 'only the authority can modify the config account.' Tools like Trident and proptest support this approach.

IDproperty-based-testing

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A testing methodology where developers define properties (invariants) that must hold true for all valid inputs, and a test framework generates random inputs to attempt to falsify those properties. Unlike unit tests that check specific examples, property-based testing explores the input space stochastically. For Solana programs, properties might include 'total token supply never changes during transfers' or 'only the authority can modify the config account.' Tools like Trident and proptest support this approach.

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Property-Based Testing (property-based-testing)
Category: Security
Definition: A testing methodology where developers define properties (invariants) that must hold true for all valid inputs, and a test framework generates random inputs to attempt to falsify those properties. Unlike unit tests that check specific examples, property-based testing explores the input space stochastically. For Solana programs, properties might include 'total token supply never changes during transfers' or 'only the authority can modify the config account.' Tools like Trident and proptest support this approach.
Related: Invariant Testing, Fuzzing (Trident), Testing (Solana Programs)
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Invariant Testing

A property-based testing approach where developers define invariants (properties that must always hold true) and a fuzzer generates random sequences of function calls attempting to violate them. Unlike unit tests that check specific scenarios, invariant tests explore the state space stochastically. Tools like Foundry invariant testing, Echidna, and Medusa support this approach.

Branch

Fuzzing (Trident)

An automated testing technique that generates pseudo-random, mutation-based, or coverage-guided instruction sequences and account inputs to discover crashes, panics, arithmetic errors, and invariant violations in Solana programs without requiring manually written test cases. Trident is the primary Solana-specific fuzzing framework, built on top of the Honggfuzz engine and the Anchor IDL, allowing developers to define instruction sequences and account state fuzzing harnesses that run thousands of iterations per second in a simulated runtime. Fuzzing complements manual audits by exhaustively exploring edge cases in instruction orderings and boundary values that reviewers may miss.

Branch

Testing (Solana Programs)

The process of validating Solana programs through unit tests, integration tests, and fuzz testing. Common approaches: Rust tests with solana-program-test or LiteSVM (fast, in-process), TypeScript tests with Bankrun or solana-test-validator (end-to-end), and fuzz testing with Trident. Best practice is testing both happy paths and attack vectors (missing signers, wrong owners).

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Developer Tools

Invariant Testing

A property-based testing approach where developers define invariants (properties that must always hold true) and a fuzzer generates random sequences of function calls attempting to violate them. Unlike unit tests that check specific scenarios, invariant tests explore the state space stochastically. Tools like Foundry invariant testing, Echidna, and Medusa support this approach.

Security

Fuzzing (Trident)

An automated testing technique that generates pseudo-random, mutation-based, or coverage-guided instruction sequences and account inputs to discover crashes, panics, arithmetic errors, and invariant violations in Solana programs without requiring manually written test cases. Trident is the primary Solana-specific fuzzing framework, built on top of the Honggfuzz engine and the Anchor IDL, allowing developers to define instruction sequences and account state fuzzing harnesses that run thousands of iterations per second in a simulated runtime. Fuzzing complements manual audits by exhaustively exploring edge cases in instruction orderings and boundary values that reviewers may miss.

Developer Tools

Testing (Solana Programs)

The process of validating Solana programs through unit tests, integration tests, and fuzz testing. Common approaches: Rust tests with solana-program-test or LiteSVM (fast, in-process), TypeScript tests with Bankrun or solana-test-validator (end-to-end), and fuzz testing with Trident. Best practice is testing both happy paths and attack vectors (missing signers, wrong owners).

Security

Recursive Proofs

A cryptographic technique where a zero-knowledge proof verifies the correctness of another proof, enabling incremental verification of unbounded computations and proof aggregation. Recursive composition allows a single compact proof to attest to an arbitrarily long chain of computations, essential for rollup proof aggregation and reducing on-chain verification costs. Systems like Plonky2, Halo2, and Nova implement recursive proving.

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Developer Toolsinvariant-testing

Invariant Testing

A property-based testing approach where developers define invariants (properties that must always hold true) and a fuzzer generates random sequences of function calls attempting to violate them. Unlike unit tests that check specific scenarios, invariant tests explore the state space stochastically. Tools like Foundry invariant testing, Echidna, and Medusa support this approach.

Securityfuzzing

Fuzzing (Trident)

An automated testing technique that generates pseudo-random, mutation-based, or coverage-guided instruction sequences and account inputs to discover crashes, panics, arithmetic errors, and invariant violations in Solana programs without requiring manually written test cases. Trident is the primary Solana-specific fuzzing framework, built on top of the Honggfuzz engine and the Anchor IDL, allowing developers to define instruction sequences and account state fuzzing harnesses that run thousands of iterations per second in a simulated runtime. Fuzzing complements manual audits by exhaustively exploring edge cases in instruction orderings and boundary values that reviewers may miss.

Developer Toolstesting

Testing (Solana Programs)

The process of validating Solana programs through unit tests, integration tests, and fuzz testing. Common approaches: Rust tests with solana-program-test or LiteSVM (fast, in-process), TypeScript tests with Bankrun or solana-test-validator (end-to-end), and fuzz testing with Trident. Best practice is testing both happy paths and attack vectors (missing signers, wrong owners).

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Security

Missing Signer Check

A vulnerability where a program accepts an account in a privileged role (e.g., admin, authority, payer) without verifying that the account actually signed the transaction, allowing any caller to impersonate that authority by simply passing the target pubkey as an instruction account. In native Solana programs, the check requires asserting account.is_signer == true; in Anchor, the Signer<'info> type enforces this automatically. Exploitation lets an attacker bypass all access control gated on authority equality checks, making it one of the most critical and commonly audited vulnerabilities in Solana programs.

Security

Missing Owner Check

A vulnerability where a program deserializes and trusts account data without first confirming that the account is owned by the expected program, allowing an attacker to substitute a maliciously crafted account owned by a different program whose byte layout happens to satisfy the deserialization. On Solana, every account stores a 32-byte owner field set to the program that created it; native programs must assert account.owner == &expected_program_id, while Anchor's Account<'info, T> wrapper performs this check automatically. Failure to validate ownership can lead to complete auth bypass if an attacker can construct a fake account whose data parses into a struct with elevated privileges.

Security

Arbitrary CPI

A vulnerability where a program accepts an arbitrary program account from the caller and invokes it via Cross-Program Invocation (CPI) without verifying it matches a known, trusted program ID, effectively letting an attacker substitute a malicious program that executes under the victim program's authority or manipulates accounts the victim program passes to it. A common pattern is accepting a token_program account without checking it equals spl_token::ID, so the attacker passes a lookalike program that records or drains account data. Prevention requires hard-coding or explicitly checking the program ID before every CPI call.

Security

PDA Substitution Attack

A vulnerability where a program derives a PDA internally but accepts an externally supplied account as that PDA without re-deriving and comparing the address, allowing an attacker to pass a different PDA (derived from attacker-controlled seeds) that the program will treat as legitimate. Because PDAs are deterministic, the only way to guarantee account identity is to call Pubkey::find_program_address (or equivalent) with the expected seeds inside the program and assert the result equals the supplied key. Anchor's seeds and bump constraints on the Account type automate this re-derivation and equality check.