Attachment: Fake attachment image lure
Message (or attached message) contains an image impersonating an Outlook attachment button.
Sublime rule (View on GitHub)
1name: "Attachment: Fake attachment image lure"
2description: |
3 Message (or attached message) contains an image impersonating an Outlook attachment button.
4type: "rule"
5severity: "medium"
6source: |
7 type.inbound
8 and (
9 // fake file attachment preview in original email
10 any(attachments,
11 .file_type in $file_types_images
12 and (
13 any(ml.logo_detect(.).brands, .name == "FakeAttachment")
14 or (
15 .size < 30000
16 and any(file.explode(.),
17 strings.icontains(.scan.ocr.raw, 'sent you')
18 // the attached image includes a filesize string
19 and regex.icontains(.scan.ocr.raw,
20 '\b\d+.\d{1,2}\s?(k|m)b(\s|$)'
21 )
22 )
23 )
24 )
25 )
26 // fake file attachment preview in attached EML
27 or any(attachments,
28 (.content_type == "message/rfc822" or .file_extension == "eml")
29 and any(file.parse_eml(.).attachments,
30 .file_type in $file_types_images
31 and (
32 any(ml.logo_detect(.).brands, .name == "FakeAttachment")
33 or (
34 .size < 30000
35 and any(file.explode(.),
36 strings.icontains(.scan.ocr.raw, 'sent you')
37 // the attached image includes a filesize string
38 and regex.icontains(.scan.ocr.raw,
39 '\b\d+.\d{1,2}\s?(k|m)b(\s|$)'
40 )
41 )
42 )
43 )
44 )
45 )
46 )
47
48 // negate highly trusted sender domains unless they fail DMARC authentication
49 and (
50 (
51 sender.email.domain.root_domain in $high_trust_sender_root_domains
52 and not headers.auth_summary.dmarc.pass
53 )
54 or sender.email.domain.root_domain not in $high_trust_sender_root_domains
55 )
56 and (
57 not profile.by_sender().solicited
58 or profile.by_sender().any_messages_malicious_or_spam
59 )
60tags:
61 - "Suspicious attachment"
62 - "Suspicious content"
63attack_types:
64 - "Credential Phishing"
65 - "Malware/Ransomware"
66tactics_and_techniques:
67 - "Evasion"
68 - "Image as content"
69 - "Social engineering"
70detection_methods:
71 - "File analysis"
72 - "Natural Language Understanding"
73 - "Optical Character Recognition"
74id: "96b8b285-2116-5e45-b0ca-57b81dc87b94"