attack-surface.md

Attack Surface Analysis for hyperledger/fabric

Attack Surface: Chaincode Logic Errors

Description: Flaws in the business logic implemented within Fabric chaincode that lead to unintended state changes, unauthorized access, or data manipulation. This is distinct from general application logic errors. Fabric Contribution: Fabric's chaincode execution environment (containerized, isolated, and distributed across peers) is the sole execution context for this logic. The deterministic execution model and endorsement process are directly affected by these errors. Example: A chaincode function intended to update an asset's ownership has a flaw that allows bypassing the Fabric-enforced endorsement policy, leading to an unauthorized state update that is nonetheless committed to the ledger. Another example: a vulnerability in how the chaincode interacts with the Fabric state database (e.g., CouchDB or LevelDB) allows for data corruption. Impact: Data corruption, financial loss, unauthorized access to sensitive data, denial of service (if the error causes resource exhaustion), reputational damage. Risk Severity: Critical Mitigation Strategies: * Rigorous Code Reviews (Fabric-Specific): Reviews must focus on how the chaincode interacts with Fabric APIs (e.g., GetState, PutState, GetCreator), endorsement policies, and private data collections. * Extensive Unit Testing (Fabric Context): Tests should simulate Fabric's execution environment, including multiple peers, endorsement policies, and different transaction scenarios. * Formal Verification (Targeting Fabric Interactions): If feasible, verify the correctness of chaincode logic specifically in relation to Fabric's state management and transaction processing. * Input Validation (Within Chaincode): Validate all inputs within the chaincode itself, as this is the only point of control within the Fabric transaction flow. * Access Control (Using Fabric Identities): Leverage Fabric's identity management (MSP) to enforce access control within the chaincode, ensuring only authorized identities can invoke specific functions. * Penetration Testing (Fabric-Focused): Testing should specifically target the chaincode's interaction with Fabric, attempting to bypass endorsement policies, manipulate state, and exploit Fabric-specific features. * Static Analysis (for Chaincode Languages): Use tools designed to analyze Go (or other chaincode languages) for vulnerabilities, paying attention to Fabric API usage.

Attack Surface: Peer Compromise (Fabric Software/Configuration)

Description: An attacker gains control over a peer node by exploiting vulnerabilities in the Fabric peer software itself or its Fabric-specific configuration. This is distinct from general OS vulnerabilities. Fabric Contribution: The peer is a core Fabric component, responsible for maintaining the ledger, executing chaincode, and participating in endorsement. Its compromise directly impacts Fabric's security. Example: An attacker exploits a vulnerability in the Fabric peer's gRPC communication handling or a flaw in how the peer processes endorsement responses. They then inject malicious transactions or manipulate the local copy of the ledger. Another example: a misconfiguration of the peer's connection profile allows unauthorized access. Impact: Data corruption, loss of data integrity, denial of service, network disruption, reputational damage. Risk Severity: Critical Mitigation Strategies: * Fabric Software Updates: Prioritize applying security patches released by the Hyperledger Fabric project. * Secure Fabric Configuration: Follow the official Fabric documentation to securely configure the peer, paying close attention to network settings, TLS certificates, and access control. * Intrusion Detection/Prevention (Fabric-Aware): Deploy systems that can detect attacks specifically targeting Fabric components and protocols. * Secure Key Management (Fabric MSP Keys): Protect the peer's private keys (used for signing transactions and interacting with the MSP) with the utmost care, using HSMs if possible. * Regular Fabric Security Audits: Conduct audits focusing on the Fabric-specific configuration and software of the peer.

Attack Surface: Orderer Compromise (Fabric Software/Configuration)

Description: An attacker gains control of an orderer node by exploiting vulnerabilities in the Fabric orderer software or its Fabric-specific configuration. This focuses on Fabric-level vulnerabilities, not general infrastructure issues. Fabric Contribution: The orderer is the central component of Fabric's consensus mechanism. Its compromise allows manipulation of the transaction order, which is fundamental to Fabric's operation. Example: An attacker exploits a vulnerability in the Fabric orderer's implementation of the Raft or Kafka consensus protocol (if used). They then reorder transactions to create double-spending attacks or censor specific transactions. Another example: a misconfiguration of the orderer's TLS settings allows for man-in-the-middle attacks. Impact: Loss of data integrity, denial of service, network disruption, financial loss, reputational damage. Risk Severity: Critical Mitigation Strategies: * All Peer Compromise Mitigations (Fabric-Focused): Apply all mitigations for peer compromise, but with even greater emphasis on security due to the orderer's critical role. * Consensus Mechanism Security (Fabric-Specific): Secure the underlying consensus mechanism (Kafka, Raft) as configured for Fabric, following Fabric-specific guidelines. * Orderer Redundancy (Fabric Best Practices): Deploy multiple orderer nodes according to Fabric's recommended configurations for fault tolerance and resilience. * Monitoring of Ordering Service (Fabric Metrics): Monitor Fabric-specific metrics related to the ordering service to detect anomalies.

Attack Surface: Chaincode Denial of Service (DoS) - Fabric Resource Exhaustion

Description: Chaincode that consumes excessive Fabric-managed resources (CPU, memory allocated to the chaincode container, ledger storage) causing the peer to become unresponsive. This is specific to the resources managed by Fabric. Fabric Contribution: Fabric's chaincode execution environment provides and limits these resources. The attack exploits these limits or the mechanisms used to enforce them. Example: A chaincode function writes excessively large amounts of data to the Fabric state database, exceeding the configured limits and causing the peer to crash. Or, a chaincode makes an excessive number of calls to GetState or PutState, exhausting Fabric's internal resources. Impact: Denial of service, network disruption, potential data loss (if the peer crashes before committing data). Risk Severity: High Mitigation Strategies: * Fabric Resource Limits: Configure Fabric's core.yaml to enforce strict resource limits on chaincode execution (CPU time, memory, storage). * Code Review and Testing (Fabric Resource Usage): Review chaincode for potential resource exhaustion, and test with large inputs and high transaction volumes to measure resource consumption within the Fabric environment. * Input Validation (Within Chaincode, Fabric Context): Validate input sizes and complexity within the chaincode to prevent excessively large data from being processed, considering Fabric's storage limitations. * Timeout Mechanisms (Chaincode-Level, Fabric-Aware): Implement timeouts within the chaincode to prevent long-running operations that could exhaust Fabric resources.

Attack Surface: MSP and CA Compromise (Fabric Identity and Certificate Management)

Description: An attacker gains control of the Fabric Membership Service Provider (MSP) or the Fabric Certificate Authority (CA), allowing them to issue fraudulent Fabric certificates, revoke legitimate certificates, or manipulate Fabric identities. This is specific to the Fabric identity and certificate infrastructure. Fabric Contribution: Fabric relies entirely on the MSP and CA for identity management and authentication. These components define the trust model of the Fabric network. Example: An attacker gains access to the Fabric CA's private key and uses it to issue a certificate for a rogue peer, allowing that peer to join the network and endorse transactions with a seemingly valid identity. Impact: Loss of data integrity, unauthorized access, network disruption, reputational damage. Risk Severity: High Mitigation Strategies: * Secure Fabric CA Infrastructure: Protect the Fabric CA server with strong physical and network security, following Fabric's deployment best practices. * Hardware Security Modules (HSMs) (for Fabric CA Keys): Use HSMs to store and manage the Fabric CA's private keys, preventing their extraction. * Multi-Factor Authentication (MFA) (for Fabric CA Access): Require MFA for all administrative access to the Fabric CA. * Regular Audits (of Fabric MSP and CA Configuration): Conduct regular security audits of the Fabric CA and MSP configuration, focusing on Fabric-specific settings. * Certificate Revocation (Using Fabric's CRL): Implement and test a robust certificate revocation process using Fabric's Certificate Revocation List (CRL) mechanism. * Separation of Duties (Fabric CA and MSP Roles): Separate the roles of Fabric CA administrator and Fabric MSP administrator to limit the impact of a single compromised account.