BEC/Fraud - Student loan callback phishing
This rule detects phishing emails that attempt to engage the recipient by soliciting a callback under the guise of student loan forgiveness or assistance. The messages often come from free email providers, lack a proper HTML structure, and include suspicious indicators such as phone numbers embedded in the text. These emails typically contain language urging the recipient to respond or take immediate action, leveraging urgency around student loan repayment to entice engagement.
Sublime rule (View on GitHub)
1name: "BEC/Fraud - Student loan callback phishing"
2description: "This rule detects phishing emails that attempt to engage the recipient by soliciting a callback under the guise of student loan forgiveness or assistance. The messages often come from free email providers, lack a proper HTML structure, and include suspicious indicators such as phone numbers embedded in the text. These emails typically contain language urging the recipient to respond or take immediate action, leveraging urgency around student loan repayment to entice engagement."
3type: "rule"
4severity: "medium"
5source: |
6 type.inbound
7 // there is no HTML body
8 and body.html.raw is null
9
10 // but the current thread contains what's most likely an html tag
11 // (eg. <>'s' followed by a closing </> )
12 and regex.contains(body.current_thread.text, '<[^>]+>.*?</[^>]+>')
13
14 // and the body mentions student loans
15 and strings.icontains(body.current_thread.text, "Student Loan")
16
17 // sourced from a free mail provider
18 and sender.email.domain.root_domain in $free_email_providers
19
20 // contains a phone number
21 and (
22 regex.contains(strings.replace_confusables(body.current_thread.text),
23 '\+?(\d{1}.)?\(?\d{3}?\)?.\d{3}.?\d{4}'
24 )
25 or regex.contains(strings.replace_confusables(body.current_thread.text),
26 '\+\d{1,3}[0-9]{10}'
27 )
28 or // +12028001238
29 regex.contains(strings.replace_confusables(body.current_thread.text),
30 '[0-9]{3}\.[0-9]{3}\.[0-9]{4}'
31 )
32 or // 202.800.1238
33 regex.contains(strings.replace_confusables(body.current_thread.text),
34 '[0-9]{3}-[0-9]{3}-[0-9]{4}'
35 )
36 or // 202-800-1238
37 regex.contains(strings.replace_confusables(body.current_thread.text),
38 '\([0-9]{3}\)\s[0-9]{3}-[0-9]{4}'
39 )
40 or // (202) 800-1238
41 regex.contains(strings.replace_confusables(body.current_thread.text),
42 '\([0-9]{3}\)-[0-9]{3}-[0-9]{4}'
43 )
44 or // (202)-800-1238
45 regex.contains(strings.replace_confusables(body.current_thread.text),
46 '1 [0-9]{3} [0-9]{3} [0-9]{4}'
47 ) // 8123456789
48 or regex.contains(strings.replace_confusables(body.current_thread.text),
49 '8\d{9}'
50 )
51 )
52
53 // contains a request
54 and any(ml.nlu_classifier(body.current_thread.text).entities,
55 .name == "request"
56 )
57
58 // sender is unsolicited
59 and not profile.by_sender().solicited
60
61
62attack_types:
63 - "BEC/Fraud"
64tactics_and_techniques:
65 - "Free email provider"
66 - "Out of band pivot"
67 - "Social engineering"
68detection_methods:
69 - "Content analysis"
70 - "Natural Language Understanding"
71 - "Sender analysis"
72id: "a71f82c3-36fe-54ca-ac72-ac65997525f5"