Data Manipulation: Transmitted Data Manipulation
Other sub-techniques of Data Manipulation (3)
Adversaries may alter data en route to storage or other systems in order to manipulate external outcomes or hide activity, thus threatening the integrity of the data.(Citation: FireEye APT38 Oct 2018)(Citation: DOJ Lazarus Sony 2018) By manipulating transmitted data, adversaries may attempt to affect a business process, organizational understanding, and decision making. Manipulation may be possible over a network connection or between system processes where there is an opportunity deploy a tool that will intercept and change information. The type of modification and the impact it will have depends on the target transmission mechanism as well as the goals and objectives of the adversary. For complex systems, an adversary would likely need special expertise and possibly access to specialized software related to the system that would typically be gained through a prolonged information gathering campaign in order to have the desired impact.
Procedure Examples |
|
| Name | Description |
|---|---|
| Melcoz |
Melcoz can monitor the clipboard for cryptocurrency addresses and change the intended address to one controlled by the adversary.(Citation: Securelist Brazilian Banking Malware July 2020) |
| APT38 |
APT38 has used DYEPACK to manipulate SWIFT messages en route to a printer.(Citation: FireEye APT38 Oct 2018) |
| LightNeuron |
LightNeuron is capable of modifying email content, headers, and attachments during transit.(Citation: ESET LightNeuron May 2019) |
| Metamorfo |
Metamorfo has a function that can watch the contents of the system clipboard for valid bitcoin addresses, which it then overwrites with the attacker's address.(Citation: Fortinet Metamorfo Feb 2020)(Citation: ESET Casbaneiro Oct 2019) |
Mitigations |
|
| Mitigation | Description |
|---|---|
| Encrypt Sensitive Information |
Protect sensitive information at rest, in transit, and during processing by using strong encryption algorithms. Encryption ensures the confidentiality and integrity of data, preventing unauthorized access or tampering. This mitigation can be implemented through the following measures: Encrypt Data at Rest: - Use Case: Use full-disk encryption or file-level encryption to secure sensitive data stored on devices. - Implementation: Implement BitLocker for Windows systems or FileVault for macOS devices to encrypt hard drives. Encrypt Data in Transit: - Use Case: Use secure communication protocols (e.g., TLS, HTTPS) to encrypt sensitive data as it travels over networks. - Implementation: Enable HTTPS for all web applications and configure mail servers to enforce STARTTLS for email encryption. Encrypt Backups: - Use Case: Ensure that backup data is encrypted both during storage and transfer to prevent unauthorized access. - Implementation: Encrypt cloud backups using AES-256 before uploading them to Amazon S3 or Google Cloud. Encrypt Application Secrets: - Use Case: Store sensitive credentials, API keys, and configuration files in encrypted vaults. - Implementation: Use HashiCorp Vault or AWS Secrets Manager to manage and encrypt secrets. Database Encryption: - Use Case: Enable Transparent Data Encryption (TDE) or column-level encryption in database management systems. - Implementation: Use MySQL’s built-in encryption features to encrypt sensitive database fields such as social security numbers. |
Detection
Detecting the manipulation of data as at passes over a network can be difficult without the appropriate tools. In some cases integrity verification checks, such as file hashing, may be used on critical files as they transit a network. With some critical processes involving transmission of data, manual or out-of-band integrity checking may be useful for identifying manipulated data.
References
- FireEye. (2018, October 03). APT38: Un-usual Suspects. Retrieved November 17, 2024.
- Department of Justice. (2018, September 6). Criminal Complaint - United States of America v. PARK JIN HYOK. Retrieved March 29, 2019.
- GReAT. (2020, July 14). The Tetrade: Brazilian banking malware goes global. Retrieved November 9, 2020.
- Faou, M. (2019, May). Turla LightNeuron: One email away from remote code execution. Retrieved June 24, 2019.
- ESET Research. (2019, October 3). Casbaneiro: peculiarities of this banking Trojan that affects Brazil and Mexico. Retrieved September 23, 2021.
- Zhang, X. (2020, February 4). Another Metamorfo Variant Targeting Customers of Financial Institutions in More Countries. Retrieved July 30, 2020.
Связанные риски
Каталоги
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