threat-modeling.md

Threat Model Analysis for hyperledger/fabric

Threat: CA Compromise (Root or Intermediate)

• Description: An attacker gains full control over a Fabric Certificate Authority (CA) server. The attacker can issue fraudulent certificates, impersonating any network participant.
• Impact: Complete network compromise. Attacker can read all data, modify the ledger, and disrupt the network. Loss of trust in the entire system.
• Affected Component: Fabric CA server (all functions related to certificate issuance and management).
• Risk Severity: Critical
• Mitigation Strategies:
  • Use Hardware Security Modules (HSMs) to protect CA private keys.
  • Implement strict multi-factor authentication and access control for CA administrators.
  • Regularly audit CA logs and configurations.
  • Implement robust intrusion detection and prevention systems specifically for the CA server.
  • Use a physically secure environment for CA servers.
  • Implement certificate revocation lists (CRLs) and Online Certificate Status Protocol (OCSP) and ensure clients validate them.
  • Use intermediate CAs; limit the scope of each CA.

Threat: Rogue Peer Enrollment

• Description: An attacker successfully enrolls a malicious peer into the Fabric network, bypassing or exploiting weaknesses in the membership service provider (MSP) and enrollment process.
• Impact: Data integrity compromise. The rogue peer can inject false data, refuse to endorse valid transactions, or disrupt consensus. The extent depends on endorsement policies.
• Affected Component: Membership Service Provider (MSP), Enrollment process, Peer joining logic.
• Risk Severity: High
• Mitigation Strategies:
  • Require multi-organization approval for new peer enrollment.
  • Implement strong authentication and authorization for peer enrollment, verifying organizational identity.
  • Use TLS for all peer communication.
  • Monitor peer behavior for anomalies (e.g., unusual endorsement patterns, connection attempts).
  • Implement robust network segmentation to limit the impact of a rogue peer.

Threat: Chaincode Vulnerability Exploitation (e.g., Integer Overflow, Injection)

• Description: An attacker crafts a malicious transaction that exploits a vulnerability within the deployed chaincode (e.g., integer overflow, injection flaw, logic error) to manipulate the ledger state in an unauthorized manner.
• Impact: Data integrity compromise, potential financial loss, unauthorized access to assets or data. The specific impact depends on the vulnerability and the chaincode's function.
• Affected Component: Specific chaincode functions, chaincode runtime environment.
• Risk Severity: High
• Mitigation Strategies:
  • Thorough chaincode security audits and penetration testing before deployment.
  • Use secure coding practices (e.g., input validation, safe arithmetic libraries, avoiding external calls).
  • Formal verification of chaincode logic where feasible.
  • Implement access control within the chaincode.
  • Regularly update chaincode to address vulnerabilities (using Fabric's upgrade mechanisms).
  • Use a linter and static analysis tools during chaincode development.

Threat: Denial of Service (DoS) on Ordering Service

• Description: An attacker floods the Fabric ordering service with a high volume of requests (valid or invalid), overwhelming its capacity and making it unavailable to legitimate users.
• Impact: Network unavailability. No new transactions can be processed, halting all business operations that rely on the Fabric network.
• Affected Component: Ordering Service (Raft or Kafka consensus mechanisms, orderer nodes).
• Risk Severity: High
• Mitigation Strategies:
  • Use a highly available and scalable ordering service configuration (multiple orderers, properly configured Raft or Kafka).
  • Implement rate limiting and request throttling specifically for the ordering service.
  • Use network firewalls and intrusion detection/prevention systems configured to protect the orderers.
  • Monitor orderer performance and scale resources as needed.
  • Implement DDoS mitigation techniques tailored to the ordering service protocol.

Threat: Private Data Leakage on Public Channel

• Description: Sensitive data is mistakenly written to a public Fabric channel, or a misconfiguration exposes a private channel to unauthorized participants. This is a direct result of incorrect Fabric configuration or chaincode logic.
• Impact: Confidentiality breach. Sensitive data is exposed to unauthorized parties.
• Affected Component: Channel configuration, chaincode logic (incorrect channel usage).
• Risk Severity: High
• Mitigation Strategies:
  • Strictly enforce the use of private channels and private data collections for sensitive data.
  • Thoroughly review channel configurations and chaincode logic before deployment.
  • Implement access control policies at the channel level.
  • Educate developers about Fabric's privacy features and require training.
  • Use automated tools to scan chaincode for potential data leakage vulnerabilities.

Threat: SideDB (CouchDB/LevelDB) Direct Access (on a Fabric Peer)

• Description: An attacker gains direct access to the state database (CouchDB or LevelDB) on a Fabric peer, bypassing the chaincode and Fabric's access controls. This is a vulnerability within the Fabric peer's deployment.
• Impact: Data integrity and confidentiality compromise. The attacker can read, modify, or delete data directly, bypassing Fabric security.
• Affected Component: Peer's state database (CouchDB or LevelDB), peer's operating system.
• Risk Severity: High
• Mitigation Strategies:
  • Securely configure the state database (strong passwords, access controls, following Fabric documentation).
  • Implement file system encryption for the peer's data directory.
  • Use network segmentation to isolate the peer's database from external access.
  • Implement intrusion detection and prevention systems on the peer itself.
  • Regularly patch and update the database software and operating system of the peer.