Callback phishing via Intuit service abuse
Callback phishing campaigns have been observed abusing Intuit Quickbooks services to send fraudulent invoices with callback phishing contents.
Sublime rule (View on GitHub)
1name: "Callback phishing via Intuit service abuse"
2description: "Callback phishing campaigns have been observed abusing Intuit Quickbooks services to send fraudulent invoices with callback phishing contents."
3type: "rule"
4severity: "medium"
5source: |
6 type.inbound
7
8 // Legitimate Intuit sending infratructure
9 and (
10 sender.email.domain.root_domain in ('intuit.com', 'intuit.co.uk')
11 // check for SPF or DMARC passed
12 and (headers.auth_summary.spf.pass or headers.auth_summary.dmarc.pass)
13 )
14 and (
15 // Callback Phishing in body (brand names required)
16 (
17 length(attachments) == 0
18
19 // brand names are required.
20 and regex.icontains(body.current_thread.text,
21 (
22 "mcafee|norton|geek.{0,5}squad|paypal|ebay|symantec|best buy|lifelock"
23 )
24 )
25 and 3 of (
26 strings.ilike(body.current_thread.text, '*purchase*'),
27 strings.ilike(body.current_thread.text, '*payment*'),
28 strings.ilike(body.current_thread.text, '*transaction*'),
29 strings.ilike(body.current_thread.text, '*subscription*'),
30 strings.ilike(body.current_thread.text, '*antivirus*'),
31 strings.ilike(body.current_thread.text, '*order*'),
32 strings.ilike(body.current_thread.text, '*support*'),
33 strings.ilike(body.current_thread.text, '*help line*'),
34 strings.ilike(body.current_thread.text, '*receipt*'),
35 strings.ilike(body.current_thread.text, '*invoice*'),
36 strings.ilike(body.current_thread.text, '*call*'),
37 strings.ilike(body.current_thread.text, '*cancel*'),
38 strings.ilike(body.current_thread.text, '*renew*'),
39 strings.ilike(body.current_thread.text, '*refund*')
40 )
41 // phone number regex
42 and any([body.current_thread.text, subject.subject],
43 regex.icontains(., '\b\+?(\d{1}.)?\(?\d{3}?\)?.\d{3}.?\d{4}\b')
44 )
45 )
46 // Callback Phishing in the "billtoContent"
47 or
48 // icontains a phone number
49 (
50 regex.icontains(strings.replace_confusables(body.html.inner_text),
51 '(?:Sold|Bill)[\s\xa0]To(?:\:\s+|\n)[^\n]+\+?(\d{1}.)?\(?\d{3}?\)?.\d{3}.?\d{4}.*\n'
52 )
53 or regex.icontains(strings.replace_confusables(body.html.inner_text),
54 '(?:Sold|Bill)[\s\xa0]To(?:\:\s+|\n)[^\n]+\+\d{1,3}[0-9]{10}.*\n'
55 )
56 or // +12028001238
57 regex.icontains(strings.replace_confusables(body.html.inner_text),
58 '(?:Sold|Bill)[\s\xa0]To(?:\:\s+|\n)[^\n]+[0-9]{3}\.[0-9]{3}\.[0-9]{4}.*\n'
59 )
60 or // 202-800-1238
61 regex.icontains(strings.replace_confusables(body.html.inner_text),
62 '(?:Sold|Bill)[\s\xa0]To(?:\:\s+|\n)[^\n]+[0-9]{3}-[0-9]{3}-[0-9]{4}.*\n'
63 )
64 or // (202) 800-1238
65 regex.icontains(strings.replace_confusables(body.html.inner_text),
66 '(?:Sold|Bill)[\s\xa0]To(?:\:\s+|\n)[^\n]+\([0-9]{3}\)\s[0-9]{3}-[0-9]{4}.*\n'
67 )
68 or // (202)-800-1238
69 regex.icontains(strings.replace_confusables(body.html.inner_text),
70 '(?:Sold|Bill)[\s\xa0]To(?:\:\s+|\n)[^\n]+\([0-9]{3}\)-[0-9]{3}-[0-9]{4}.*\n'
71 )
72 or // 202 800 1238
73 regex.icontains(strings.replace_confusables(body.html.inner_text),
74 '(?:Sold|Bill)[\s\xa0]To(?:\:\s+|\n)[^\n]+1\s?[0-9]{3} [0-9]{3} [0-9]{4}.*\n'
75 ) // 8123456789
76 or (
77 regex.icontains(strings.replace_confusables(body.html.inner_text),
78 '(?:Sold|Bill)[\s\xa0]To(?:\:\s+|\n)[^\n]+8\d{9}.*\n'
79 )
80 and regex.icontains(strings.replace_confusables(body.html.inner_text),
81 '\+1'
82 )
83 )
84 )
85 // all attachments are PDFs with callback phishing indicators Brands Required
86 or (
87 length(attachments) < 3
88 and all(attachments, .file_extension == "pdf")
89 // the attachment is a pdf with 1 page, and at least 60 ocr chars
90 and any(attachments,
91 (
92 .file_extension == "pdf"
93 and any(file.explode(.), .scan.exiftool.page_count < 3)
94 and any(file.explode(.), length(.scan.ocr.raw) > 60)
95
96 // 4 of the following strings are found
97 and (
98 any(file.explode(.),
99 4 of (
100 strings.icontains(.scan.ocr.raw, "purchase"),
101 strings.icontains(.scan.ocr.raw, "payment"),
102 strings.icontains(.scan.ocr.raw, "transaction"),
103 strings.icontains(.scan.ocr.raw, "subscription"),
104 strings.icontains(.scan.ocr.raw, "antivirus"),
105 strings.icontains(.scan.ocr.raw, "order"),
106 strings.icontains(.scan.ocr.raw, "support"),
107 strings.icontains(.scan.ocr.raw, "help line"),
108 strings.icontains(.scan.ocr.raw, "receipt"),
109 strings.icontains(.scan.ocr.raw, "invoice"),
110 strings.icontains(.scan.ocr.raw, "call"),
111 strings.icontains(.scan.ocr.raw, "helpdesk"),
112 strings.icontains(.scan.ocr.raw, "cancel"),
113 strings.icontains(.scan.ocr.raw, "renew"),
114 strings.icontains(.scan.ocr.raw, "refund"),
115 strings.icontains(.scan.ocr.raw, "amount"),
116 strings.icontains(.scan.ocr.raw, "crypto"),
117 strings.icontains(.scan.ocr.raw, "wallet address"),
118 regex.icontains(.scan.ocr.raw, '\$\d{3}\.\d{2}\b'),
119 regex.icontains(.scan.ocr.raw,
120 '(\+\d|1.(\()?\d{3}(\))?\D\d{3}\D\d{4})'
121 ),
122 regex.icontains(.scan.ocr.raw,
123 '\+?(\d{1,2})?\s?\(?\d{3}\)?[\s\.\-⋅]{0,5}\d{3}[\s\.\-⋅]{0,5}\d{4}'
124 )
125 )
126
127 // 1 of the following strings is found, representing common Callback brands
128 and (
129 1 of (
130 strings.icontains(.scan.ocr.raw, "geek squad"),
131 strings.icontains(.scan.ocr.raw, "lifelock"),
132 strings.icontains(.scan.ocr.raw, "best buy"),
133 strings.icontains(.scan.ocr.raw, "mcafee"),
134 strings.icontains(.scan.ocr.raw, "norton"),
135 strings.icontains(.scan.ocr.raw, "ebay"),
136 strings.icontains(.scan.ocr.raw, "paypal"),
137 )
138 // add additional logic for common language for paypal, which is a valid payment method
139 and not regex.icontains(.scan.ocr.raw, "paypal[^\n]+accepted")
140 )
141 )
142 or any(ml.logo_detect(.).brands,
143 .name in ("PayPal", "Norton", "GeekSquad", "Ebay")
144 )
145 )
146 )
147 )
148 )
149 )
150attack_types:
151 - "Callback Phishing"
152tactics_and_techniques:
153 - "Evasion"
154 - "Free email provider"
155 - "Impersonation: Brand"
156 - "Social engineering"
157detection_methods:
158 - "Computer Vision"
159 - "Content analysis"
160 - "Header analysis"
161 - "Optical Character Recognition"
162id: "f2fe1294-ca43-5290-84fd-02f8149c5de7"