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[submodule "windows/ShellcodeFluctuation"]
path = windows/ShellcodeFluctuation
url = https://github.com/mgeeky/ShellcodeFluctuation
[submodule "phishing/decode-spam-headers"]
path = phishing/decode-spam-headers
url = https://github.com/mgeeky/decode-spam-headers

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phishing/README.md
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## Phishing and Social-Engineering related scripts, tools and CheatSheets
- [**`decode-spam-headers.py`**](https://github.com/mgeeky/Penetration-Testing-Tools/tree/master/phishing/decode-spam-headers) - This tool accepts on input an `*.EML` or `*.txt` file with all the SMTP headers. It will then extract a subset of interesting headers and using **79+** tests will attempt to decode them as much as possible.
- [**`decode-spam-headers.py`**](https://github.com/mgeeky/decode-spam-headers) - This tool accepts on input an `*.EML` or `*.txt` file with all the SMTP headers. It will then extract a subset of interesting headers and using **79+** tests will attempt to decode them as much as possible.
This script also extracts all IPv4 addresses and domain names and performs full DNS resolution of them.
Resulting output will contain useful information on why this e-mail might have been blocked.

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phishing/decode-spam-headers Submodule

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phishing/decode-spam-headers/README.md
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## `decode-spam-headers.py`
This tool accepts on input an `*.EML` or `*.txt` file with all the SMTP headers. It will then extract a subset of interesting headers and using **79+** tests will attempt to decode them as much as possible.
This script also extracts all IPv4 addresses and domain names and performs full DNS resolution of them.
Resulting output will contain useful information on why this e-mail might have been blocked.
### Example screenshots
- Chain of MTA servers (nicely parsed `Received` headers):
![1.png](img/1.png)
- Various headers decoded as much as possible, according to publicly available documentation (here _Office365 ForeFront Spam Report_):
![2.png](img/2.png)
- Different custom heuristics implement to actively validate and seek for clues of spam categorization, here logic detecting _Domain Impersonation_:
![3.png](img/3.png)
- Script attempts to reverse-engineer and document some of the Office365 Anti-Spam rules, as well as collect public knowledge about other opaque Anti-Spam headers:
![4.png](img/4.png)
### Processed headers
Processed headers (more than **67+** headers are parsed):
- `X-forefront-antispam-report`
- `X-exchange-antispam`
- `X-exchange-antispam-mailbox-delivery`
- `X-exchange-antispam-message-info`
- `X-microsoft-antispam-report-cfa-test`
- `Received`
- `From`
- `To`
- `Subject`
- `Thread-topic`
- `Received-spf`
- `X-mailer`
- `X-originating-ip`
- `User-agent`
- `X-forefront-antispam-report`
- `X-microsoft-antispam-mailbox-delivery`
- `X-microsoft-antispam`
- `X-exchange-antispam-report-cfa-test`
- `X-spam-status`
- `X-spam-level`
- `X-spam-flag`
- `X-spam-report`
- `X-vr-spamcause`
- `X-ovh-spam-reason`
- `X-vr-spamscore`
- `X-virus-scanned`
- `X-spam-checker-version`
- `X-ironport-av`
- `X-ironport-anti-spam-filtered`
- `X-ironport-anti-spam-result`
- `X-mimecast-spam-score`
- `Spamdiagnosticmetadata`
- `X-ms-exchange-atpmessageproperties`
- `X-msfbl`
- `X-ms-exchange-transport-endtoendlatency`
- `X-ms-oob-tlc-oobclassifiers`
- `X-ip-spam-verdict`
- `X-amp-result`
- `X-ironport-remoteip`
- `X-ironport-reputation`
- `X-sbrs`
- `X-ironport-sendergroup`
- `X-policy`
- `X-ironport-mailflowpolicy`
- `X-remote-ip`
- `X-sea-spam`
- `X-fireeye`
- `X-antiabuse`
- `X-tmase-version`
- `X-tm-as-product-ver`
- `X-tm-as-result`
- `X-imss-scan-details`
- `X-tm-as-user-approved-sender`
- `X-tm-as-user-blocked-sender`
- `X-tmase-result`
- `X-tmase-snap-result`
- `X-imss-dkim-white-list`
- `X-tm-as-result-xfilter`
- `X-tm-as-smtp`
- `X-scanned-by`
- `X-mimecast-spam-signature`
- `X-mimecast-bulk-signature`
- `X-sender-ip`
- `X-forefront-antispam-report-untrusted`
- `X-microsoft-antispam-untrusted`
- `X-sophos-senderhistory`
- `X-sophos-rescan`
Most of these headers are not fully documented, therefore the script is unable to pinpoint all the details, but at least it collects all I could find on them.
### Usage
Help:
```
PS> py .\decode-spam-headers.py --help
usage: decode-spam-headers.py [options] <file>
optional arguments:
-h, --help show this help message and exit
Required arguments:
infile Input file to be analysed or --list tests to show available tests.
Options:
-o OUTFILE, --outfile OUTFILE
Output file with report
-f {json,text}, --format {json,text}
Analysis report format. JSON, text. Default: text
-N, --nocolor Dont use colors in text output.
-v, --verbose Verbose mode.
-d, --debug Debug mode.
-l, --list List available tests and quit. Use it like so: --list tests
Tests:
-i tests, --include-tests tests
Comma-separated list of test IDs to run. Ex. --include-tests 1,3,7
-e tests, --exclude-tests tests
Comma-separated list of test IDs to skip. Ex. --exclude-tests 1,3,7
-r, --resolve Resolve IPv4 addresses / Domain names.
-a, --decode-all Decode all =?us-ascii?Q? mail encoded messages and print their contents.
```
If you want to run only a subset of tests, you'll first need to learn Test IDs of which to pick.
Run the script with `-l tests` to grab that list.
List available test and their corresponding IDs:
```
C:\> py decode-spam-headers.py -l tests
[.] Available tests:
TEST_ID - TEST_NAME
--------------------------------------
1 - Received - Mail Servers Flow
2 - Extracted IP addresses
3 - Extracted Domains
4 - Bad Keywords In Headers
5 - From Address Analysis
6 - Subject and Thread Topic Difference
7 - Authentication-Results
8 - ARC-Authentication-Results
9 - Received-SPF
10 - Mail Client Version
11 - User-Agent Version
12 - X-Forefront-Antispam-Report
13 - X-MS-Exchange-Organization-SCL
14 - X-Microsoft-Antispam-Mailbox-Delivery
15 - X-Microsoft-Antispam Bulk Mail
16 - X-Exchange-Antispam-Report-CFA-Test
17 - Domain Impersonation
18 - SpamAssassin Spam Status
19 - SpamAssassin Spam Level
20 - SpamAssassin Spam Flag
21 - SpamAssassin Spam Report
22 - OVH's X-VR-SPAMCAUSE
23 - OVH's X-Ovh-Spam-Reason
24 - OVH's X-Ovh-Spam-Score
25 - X-Virus-Scan
26 - X-Spam-Checker-Version
27 - X-IronPort-AV
28 - X-IronPort-Anti-Spam-Filtered
29 - X-IronPort-Anti-Spam-Result
30 - X-Mimecast-Spam-Score
31 - Spam Diagnostics Metadata
32 - MS Defender ATP Message Properties
33 - Message Feedback Loop
34 - End-to-End Latency - Message Delivery Time
35 - X-MS-Oob-TLC-OOBClassifiers
36 - X-IP-Spam-Verdict
37 - X-Amp-Result
38 - X-IronPort-RemoteIP
39 - X-IronPort-Reputation
40 - X-SBRS
41 - X-IronPort-SenderGroup
42 - X-Policy
43 - X-IronPort-MailFlowPolicy
44 - X-SEA-Spam
45 - X-FireEye
46 - X-AntiAbuse
47 - X-TMASE-Version
48 - X-TM-AS-Product-Ver
49 - X-TM-AS-Result
50 - X-IMSS-Scan-Details
51 - X-TM-AS-User-Approved-Sender
52 - X-TM-AS-User-Blocked-Sender
53 - X-TMASE-Result
54 - X-TMASE-SNAP-Result
55 - X-IMSS-DKIM-White-List
56 - X-TM-AS-Result-Xfilter
57 - X-TM-AS-SMTP
58 - X-TMASE-SNAP-Result
59 - X-TM-Authentication-Results
60 - X-Scanned-By
61 - X-Mimecast-Spam-Signature
62 - X-Mimecast-Bulk-Signature
63 - X-Forefront-Antispam-Report-Untrusted
64 - X-Microsoft-Antispam-Untrusted
65 - X-Mimecast-Impersonation-Protect
66 - X-Proofpoint-Spam-Details
67 - X-Proofpoint-Virus-Version
68 - SPFCheck
69 - X-Barracuda-Spam-Score
70 - X-Barracuda-Spam-Status
71 - X-Barracuda-Spam-Report
72 - X-Barracuda-Bayes
73 - X-Barracuda-Start-Time
74 - Similar to SpamAssassin Spam Level headers
75 - SMTP Header Contained IP address
76 - Other unrecognized Spam Related Headers
77 - Other interesting headers
78 - Security Appliances Spotted
79 - Email Providers Infrastructure Clues
80 - X-Microsoft-Antispam-Message-Info
81 - Decoded Mail-encoded header values
82 - Header Containing Client IP
```
### Sample run
Sample run:
```
PS> py decode-spam-headers.py headers.txt
------------------------------------------
(1) Test: Received - Mail Servers Flow
HEADER:
Received
VALUE:
...
ANALYSIS:
- List of server hops used to deliver message:
--> (1) "attacker" <attacker@attacker.com>
|_> (2) SMTP-SERVICE (44.55.66.77)
time: 01 Jan 2021 12:34:20
|_> (3) mail-wr1-f51.google.com (209.85.221.51)
time: 01 Jan 2021 12:34:20
version: fuzzy match: Exchange Server 2019 CU11; October 12, 2021; 15.2.986.9
|_> (4) SN1NAM02FT0061.eop-nam02.prod.protection.outlook.com (2603:10b6:806:131:cafe::e5)
time: 01 Jan 2021 12:34:20
version: fuzzy match: Exchange Server 2019 CU11; October 12, 2021; 15.2.986.9
|_> (5) SA0PR11CA0138.namprd11.prod.outlook.com (2603:10b6:806:131::23)
time: 01 Jan 2021 12:34:20
version: fuzzy match: Exchange Server 2019 CU11; October 12, 2021; 15.2.986.9
|_> (6) CP2PR80MB4114.lamprd80.prod.outlook.com (2603:10d6:102:3c::15)
time: 01 Jan 2021 12:34:23
|_> (7) "Victim Surname" <victim@contoso.com>
------------------------------------------
[...]
------------------------------------------
(4) Test: Mail Client Version
HEADER:
X-Mailer
VALUE:
OEM
ANALYSIS:
- X-Mailer header was present and contained value: "OEM".
------------------------------------------
(5) Test: X-Forefront-Antispam-Report
HEADER:
X-Forefront-Antispam-Report
VALUE:
CIP:209.85.167.100;CTRY:US;LANG:de;SCL:5;SRV:;IPV:NLI;SFV:SPM;H:mail-lf1-f100.google.com;PTR:mail-l
f1-f100.google.com;CAT:DIMP;SFTY:9.19;SFS:(4636009)(956004)(166002)(6916009)(356005)(336012)(19
625305002)(22186003)(5660300002)(4744005)(6666004)(35100500006)(82960400001)(26005)(7596003)(7636003)(554460
02)(224303003)(1096003)(58800400005)(86362001)(9686003)(43540500002);DIR:INB;SFTY:9.19;
ANALYSIS:
- Microsoft Office365/Exchange ForeFront Anti-Spam report
- CIP: Connecting IP address: 209.85.167.100
- CTRY: The source country as determined by the connecting IP address
- US
- LANG: The language in which the message was written
- de
- IPV: Ingress Peer Verification status
- NLI: The IP address was not found on any IP reputation list.
- SFV: Message Filtering
- SPM: The message was marked as spam by spam filtering.
- H: The HELO or EHLO string of the connecting email server.
- mail-lf1-f100.google.com
- PTR: Reverse DNS of the Connecting IP peer's address
- mail-lf1-f100.google.com
- CAT: The category of protection policy
- DIMP: Domain Impersonation
- SFTY: The message was identified as phishing
- 9.19: Domain impersonation. The sending domain is attempting to impersonate a protected domain
- DIR: Direction of email verification
- INB: Inbound email verification
- Message matched 24 Anti-Spam rules (SFS):
- (1096003)
- (166002)
- (19625305002)
- (22186003)
- (224303003)
- (26005)
- (336012)
- (356005)
- (35100500006) - (SPAM) Message contained embedded image.
- (43540500002)
- (4636009)
- (4744005)
- (55446002)
- (5660300002)
- (58800400005)
- (6666004)
- (6916009)
- (7596003)
- (7636003)
- (82960400001)
- (86362001)
- (956004)
- (9686003)
- SCL: Spam Confidence Level: 5
- SPAM: Spam filtering marked the message as Spam
More information:
- https://docs.microsoft.com/en-us/microsoft-365/security/office-365-security/anti-spam-message-headers
- https://docs.microsoft.com/en-us/exchange/antispam-and-antimalware/antispam-protection/antispam-stamps
- https://docs.microsoft.com/en-us/microsoft-365/security/office-365-security/spam-confidence-levels
- https://docs.microsoft.com/en-us/exchange/monitoring/trace-an-email-message/run-a-message-trace-and-view-results
------------------------------------------
(6) Test: X-Microsoft-Antispam-Mailbox-Delivery
HEADER:
X-Microsoft-Antispam-Mailbox-Delivery
VALUE:
ucf:0;jmr:1;auth:0;dest:J;ENG:(910001)(944506458)(944626604)(750132)(520011016);
ANALYSIS:
- This header denotes what to do with received message, where to put it.
- auth: Message originating from Authenticated sender
- 0: Not Authenticated
- dest: Destination where message should be placed
- J: JUNK directory
- Message matched 6 Anti-Spam Delivery rules:
- (520011016)
- (750132)
- (910001)
- (944506458)
- (944626604)
------------------------------------------
(7) Test: X-Microsoft-Antispam Bulk Mail
HEADER:
X-Microsoft-Antispam
VALUE:
BCL:0;
ANALYSIS:
- BCL: BULK Confidence Level: 0
The message isn't from a bulk sender.
More information:
- https://docs.microsoft.com/en-us/microsoft-365/security/office-365-security/bulk-complaint-level-values
------------------------------------------
[...]
------------------------------------------
(10) Test: MS Defender ATP Message Properties
HEADER:
X-MS-Exchange-AtpMessageProperties
VALUE:
SA|SL
ANALYSIS:
- MS Defender Advanced Threat Protection enabled following protections on this message:
- Safe Attachments Protection
- Safe Links Protection
------------------------------------------
(11) Test: Domain Impersonation
HEADER:
From
VALUE:
"attacker" <attacker@attacker.com>
ANALYSIS:
- Mail From: <attacker@attacker.com>
- Mail Domain: attacker.com
--> resolves to: 11.22.33.44
--> reverse-DNS resolves to: ec2-11-22-33-44.eu-west-3.compute.amazonaws.com
(sender's domain: amazonaws.com)
- First Hop: SMTP-SERVICE (44.55.66.77)
--> resolves to:
--> reverse-DNS resolves to: host44-55-66-77.static.arubacloud.pl
(first hop's domain: arubacloud.pl)
- Domain SPF: "v=spf1 include:_spf.google.com ~all"
- WARNING! Potential Domain Impersonation!
- Mail's domain should resolve to: amazonaws.com
- But instead first hop resolved to: arubacloud.pl
```

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#!/usr/bin/python3
import os, sys, re
import string
import argparse
import json
import textwrap
import socket
import time
import glob
import base64
rules = {}
scanned = set()
def walk(path):
global rules
global scanned
print(f'Walking {path}...')
for file in glob.glob(os.path.join(path, '**'), recursive=True):
if not file.lower().endswith('.txt'):
continue
if file in scanned: continue
scanned.add(file)
data = ''
with open(file) as f:
data = f.read()
for m in re.finditer(r'(\(\d{4,}\))', data, re.I):
rule = m.group(1)
if rule in rules.keys():
if file not in rules[rule]['files']:
rules[rule]['count'] += 1
rules[rule]['files'].add(file)
else:
rules[rule] = {}
rules[rule]['count'] = 1
rules[rule]['files'] = set([file, ])
def main(argv):
paths = []
for i in range(len(argv)):
arg = argv[i]
if i == 0: continue
if not os.path.isdir(arg):
print('[!] input path does not exist or is not a dir! ' + arg)
sys.exit(1)
walk(os.path.abspath(arg))
print(f'[.] Found {len(rules)} unique rules.:')
candidates = []
for k, v in rules.items():
if v['count'] > 1:
print(f'\n\t- {k: <15}: occurences: {v["count"]} - files: {len(v["files"])}')
if len(v['files']) < 6:
for f in v['files']:
print('\t\t- ' + str(f))
if __name__ == '__main__':
main(sys.argv)

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