Business email compromise detection system
An email is received that is from an email sender. From the email, the display name of the email sender, an email address of the email sender, and an email domain of the email sender, is extracted. A score is determined for the email based on at least: the extracted display name of the email sender, the extracted email address of the email sender, and the extracted email domain of the email sender, where the score indicates a probability that the email is from a legitimate sender. Message content of the email is input into multiple classifiers each corresponding to a particular message type. The message type of the email is determined based on output of the classifiers. Based on at least the determined score for the email and the determined message type of the email, a determination is made whether the email is associated with a BEC attack.
1. A method, comprising:
receiving an email that is directed to an email recipient and is from an email sender;
extracting, from the email, a triple, the extracted triple including a display name of the email sender, an email address of the email sender, and an email domain of the email sender;
identifying a triple identifier associated with the extracted triple;
determining a name score for the email based on the triple identifier by accessing the name score for the triple identifier in a database, wherein the name score indicates a probability that the email is from a legitimate sender, and wherein the name score is updated based on frequency counting;
inputting message content of the email into a plurality of classifiers, wherein each of the plurality of classifiers is machine-learned to recognize a particular message type;
determining a message type of the email based on output of the plurality of classifiers; and
determining, based on at least the determined name score for the email, the determined message type of the email, and a reputation score associated with an IP address of the email sender, whether the email is associated with a business email compromise (BEC) attack.
2. The method of claim 1 , further comprising:
wherein a result of the determining whether the email is associated with the BEC attack indicates that the email is associated with the BEC attack; and
modifying the email to include a status indicating that the email is associated with a BEC attack.
3. The method of claim 1 , further comprising:
wherein a result of the determining whether the email is associated with the BEC attack indicates that the email is not associated with the BEC attack; and
modifying the email to include a status indicating that the email is not associated with a BEC attack.
4. The method of claim 1 , further comprising:
wherein a result of the determining whether the email is associated with the BEC attack indicates that the email is associated with the BEC attack; and
blocking transmission of the email to the email recipient.
5. The method of claim 1 , wherein the message type of the email is one of: an invoice, a financial communication, a communication related to a banking account, and an automated clearinghouse (ACH) communication.
6. The method of claim 1 , wherein determining whether the email is associated with a BEC attack further is based on a reputation score associated with the email domain of the email sender.
7. A non-transitory computer-readable storage media comprising instructions which, when executed by one or more processors cause operations to be performed comprising:
receiving an email that is directed to an email recipient and is from an email sender;
extracting, from the email, a triple, the extracted triple including a display name of the email sender, an email address of the email sender, and an email domain of the email sender;
identifying a triple identifier associated with the extracted triple;
determining a name score for the email based on the triple identifier by accessing the name score for the triple identifier in a database, wherein the name score indicates a probability that the email is from a legitimate sender, and wherein the name score is updated based on frequency counting;
inputting message content of the email into a plurality of classifiers, wherein each of the plurality of classifiers is machine-learned to recognize a particular message type;
determining a message type of the email based on output of the plurality of classifiers; and
determining, based on at least the determined name score for the email, the determined message type of the email, and a reputation score associated with an IP address of the email sender, whether the email is associated with a business email compromise (BEC) attack.
8. The non-transitory computer-readable storage media of claim 7 , wherein the operations further comprise:
wherein a result of the determining whether the email is associated with the BEC attack indicates that the email is associated with the BEC attack; and
modifying the email to include a status indicating that the email is associated with a BEC attack.
9. The non-transitory computer-readable storage media of claim 7 , wherein the operations further comprise:
wherein a result of the determining whether the email is associated with the BEC attack indicates that the email is not associated with the BEC attack; and
modifying the email to include a status indicating that the email is not associated with a BEC attack.
10. The non-transitory computer-readable storage media of claim 7 , wherein the operations further comprise:
wherein a result of the determining whether the email is associated with the BEC attack indicates that the email is associated with the BEC attack; and
blocking transmission of the email to the email recipient.
11. The non-transitory computer-readable storage media of claim 7 , wherein the message type of the email is one of: an invoice, a financial communication, a communication related to a banking account, and an automated clearinghouse (ACH) communication.
12. The non-transitory computer-readable storage media of claim 7 , wherein determining whether the email is associated with a BEC attack further is based on a reputation score associated with the email domain of the email sender.
13. A system comprising:
one or more processors; and
one or more non-transitory storage media storing instructions which, when executed by the one or more processors cause the system to perform operations including:
receiving an email that is directed to an email recipient and is from an email sender;
extracting, from the email, a triple, the extracted triple including a display name of the email sender, an email address of the email sender, and an email domain of the email sender;
identifying a triple identifier associated with the extracted triple;
determining a name score for the email based on the triple identifier by accessing the name score for the triple identifier in a database, wherein the name score indicates a probability that the email is from a legitimate sender, and wherein the name score is updated based on frequency counting;
inputting message content of the email into a plurality of classifiers, wherein each of the plurality of classifiers is machine-learned to recognize a particular message type;
determining a message type of the email based on output of the plurality of classifiers; and
determining, based on at least the determined name score for the email, the determined message type of the email, and a reputation score associated with an IP address of the email sender, whether the email is associated with a business email compromise (BEC) attack.
14. The system of claim 13 , wherein the operations further comprise:
wherein a result of the determining whether the email is associated with the BEC attack indicates that the email is associated with the BEC attack; and
modifying the email to include a status indicating that the email is associated with a BEC attack.
15. The system of claim 13 , wherein the operations further comprise:
wherein a result of the determining whether the email is associated with the BEC attack indicates that the email is not associated with the BEC attack; and
modifying the email to include a status indicating that the email is not associated with a BEC attack.
16. The system of claim 13 , wherein the operations further comprise:
wherein a result of the determining whether the email is associated with the BEC attack indicates that the email is associated with the BEC attack; and
blocking transmission of the email to the email recipient.
17. The system of claim 13 , wherein the message type of the email is one of: an invoice, a financial communication, a communication related to a banking account, and an automated clearinghouse (ACH) communication.
18. The system of claim 13 , wherein determining whether the email is associated with a BEC attack further is based on a reputation score associated with the email domain of the email sender.