CAPEC-489: SSL Flood
Description
An adversary may execute a flooding attack using the SSL protocol with the intent to deny legitimate users access to a service by consuming all the available resources on the server side. These attacks take advantage of the asymmetric relationship between the processing power used by the client and the processing power used by the server to create a secure connection. In this manner the attacker can make a large number of HTTPS requests on a low provisioned machine to tie up a disproportionately large number of resources on the server. The clients then continue to keep renegotiating the SSL connection. When multiplied by a large number of attacking machines, this attack can result in a crash or loss of service to legitimate users.
- Likelihood of attack
- Not rated by MITRE
- Typical severity
- Not rated by MITRE
- Abstraction
- StandardA specific methodology or technique used in an attack.
Mechanism of attack: Abuse Existing Functionality
Prerequisites
- This type of an attack requires the ability to generate a large amount of SSL traffic to send a target server.
Mitigations
- To mitigate this type of an attack, an organization can create rule based filters to silently drop connections if too many are attempted in a certain time period.
Related weaknesses (CWE)
ATT&CK techniques (CAPEC taxonomy mapping)
Across MITRE's defensive frameworks
Linked through the 1 ATT&CK technique above.
Counter with D3FEND
Defensive techniques MITRE D3FEND maps to the same ATT&CK techniques.
- D3-ISVAInbound Session Volume Analysis1 shared
- D3-ITFInbound Traffic Filtering1 shared
- D3-APCAApplication Protocol Command Analysis1 shared
- D3-CSPPClient-server Payload Profiling1 shared
- D3-NTCDNetwork Traffic Community Deviation1 shared
- D3-NTFNetwork Traffic Filtering1 shared
- D3-NTSANetwork Traffic Signature Analysis1 shared
- D3-PHDURAPer Host Download-Upload Ratio Analysis1 shared
- D3-PMADProtocol Metadata Anomaly Detection1 shared
- D3-RTSDRemote Terminal Session Detection1 shared
- D3-UGLPAUser Geolocation Logon Pattern Analysis1 shared