Deepfake-Assisted Phishing
Sub-technique of AML.T0052 Phishing
Description
Adversaries may use deepfakes (AI-generated synthetic images, audio, or video) in phishing campaigns to impersonate trusted individuals, executives, or organizations. These attacks exploit human trust by presenting fraudulent voice or video communications as legitimate, enabling adversaries to manipulate targets into disclosing credentials, transferring funds, or granting access to systems.
Voice deepfakes (AI-cloned voices) are used in vishing [[vishing]] (voice phishing) attacks over telephone or VoIP. Adversaries can clone a target's voice using a few seconds [[valle]] of publicly available audio from speeches, earnings calls, podcasts, or social media [[voice]]. These cloned voices are then used in pre-recorded voicemail messages or live phone calls. Video deepfakes can impersonate a trusted individual's face and voice. Adversaries use publicly available video from company meetings, earnings calls, or social media to create convincing AI-generated video of target individuals. They are used in live video conference calls or recorded video messages. AI-generated content has advanced to the point that it is often difficult to identify as synthetic [[fbi]].
Adversaries may first perform Obtain Capabilities: Generative AI followed by Generate Deepfakes in preparation for their Phishing campaign. Deepfake phishing campaigns often utilize other communication channels (such as email, SMS, or instant messaging) for layered social engineering attacks [[aiid839]].
These attacks span a wide range of victims and attack types, demonstrating the breadth of deepfake-enabled fraud. Adversaries have conducted extensive deepfake-assisted phishing campaigns against the individuals, including targeted scams [[aiid564]] [[oecd1]] [[aiid1280]] [[aiid1285]], as well as large-scale credential harvesting campaigns targeting billions of users [[aiid839]] [[aiid941]]. Adversaries have used deepfakes to impersonate executives [[aiid1100]], causing business entities to suffer significant financial losses from [[aiid634]] [[aiid147]]. There are also reports of government officials being targeted in widespread campaigns [[fbi]] [[aiid927]].
The attacks span communication channels including voice deepfakes for vishing [[aiid567]] and video deepfakes in conference calls [[aiid634]], as well as multi-channel campaigns combining phone, email, and messaging platforms [[aiid839]].
- ATLAS ID
- AML.T0052.001
- Maturity
- FeasibleShown to be possible in principle (proof of concept).
- Platforms
- Enterprise
Mitigations
- AML.M0018User Training
Train users on deepfake threats, including how to recognize synthetic voice, video, and text. Recommend verification through independent channels (e.g. known call-back number) before processing sensitive requests or providing sensitive information via voice or video calls.
- AML.M0034Deepfake Detection
Deploy technical controls to detect and block synthetic audio and video. This includes AI-based analysis tools that examine media for artifacts indicative deepfakes.
Case studies that use it
No ATLAS case study records this technique yet. Browse all case studies.
Related ATT&CK technique
ATLAS references this ATT&CK technique on the parent technique.
Marked techniques are also explained, with detection notes and certification relevance, on our interactive ATT&CK map.
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-EFEmail Filtering1 shared
- D3-IAAIdentifier Activity Analysis1 shared
- D3-RERestore Email1 shared
- D3-SMRASender MTA Reputation Analysis1 shared
- D3-SRASender Reputation Analysis1 shared
- D3-UAURL Analysis1 shared
- D3-URAURL Reputation Analysis1 shared
- D3-EREmail Removal1 shared
- D3-ISVAInbound Session Volume Analysis1 shared
- D3-ITFInbound Traffic Filtering1 shared
- D3-HDHomoglyph Detection1 shared
- D3-DIData Inventory1 shared