Detection: PHP Session Upload Progress Serialized Payload in Upload Filename

Created: 2026-10-22 Last Updated: 2026-10-22 ID: 47b3ff26-c4cc-4413-9bf3-f44dbac36785 Author: Raven Tait, Onur Mustafa Erdogan, Nasreddine Bencherchali, Splunk Type: Anomaly Product: Splunk Enterprise Security

Description

This analytic detects multipart POST requests containing the "PHP_SESSION_UPLOAD_PROGRESS" form field and a serialized PHP structure in an uploaded filename. This combination may indicate an attempt to exploit PHP session upload-progress handling and can be associated with PHP2Shell activity.

Search

 1`zeek_http`
 2method="POST"
 3request_headers="*"
 4
 5
 6| eval src=coalesce(src, src_ip, 'id.orig_h'),
 7       dest=coalesce(dest, dest_ip, 'id.resp_h'),
 8       dest_port=coalesce(dest_port, 'id.resp_p')
 9
10
11| eval has_upload_progress_field=if(match(request_headers, "(?im)\s*form-data;\\s*name=\\\"PHP_SESSION_UPLOAD_PROGRESS\\\""), 1, 0)
12
13
14| rex max_match=0 field=request_headers "(?im)\s*form-data;(?<part_disposition>[^\\r\\n]*)"
15
16
17| eval serialized_filename_headers=mvfilter(match(part_disposition, "(?i)\\bfilename\\s*=.*(?:\\
18|?O:\\d+:
19|C:\\d+:
20|a:\\d+:\\{
21|s:\\d+:
22|E:\\d+:
23|R:\\d+;
24|i:-?\\d+;
25|d:(?:[-+]?(?:\\d+(?:\\.\\d*)?
26|\\.\\d+)(?:[eE][-+]?\\d+)?
27|INF
28|NAN);
29|b:[01];
30|N;)"))
31
32
33| where has_upload_progress_field=1 AND mvcount(serialized_filename_headers)>0
34
35
36| stats count min(_time) as firstTime
37              max(_time) as lastTime
38              values(method) as method
39              values(status_code) as status_code
40              values(user_agent) as user_agent
41              values(serialized_filename_headers) as serialized_filename_headers
42
43  by src dest dest_port uri
44
45
46| `security_content_ctime(firstTime)`
47
48| `security_content_ctime(lastTime)`
49
50| `php_session_upload_progress_serialized_payload_in_upload_filename_filter`

Data Source

Name	Platform	Sourcetype	Source
Zeek HTTP	Web	`'zeek:http'`	`'http.log'`

Macros Used

Name	Value
security_content_ctime	`convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)`
php_session_upload_progress_serialized_payload_in_upload_filename_filter	`search *`

php_session_upload_progress_serialized_payload_in_upload_filename_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK

+ Kill Chain Phases

+ NIST

+ CIS

- Threat Actors

ID	Technique	Tactic
T1190	Exploit Public-Facing Application	Initial Access

Delivery

DE.AE

CIS 13

CVE

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting	Value
Disabled	true
Cron Schedule	`0 * * * *`
Earliest Time	`-70m@m`
Latest Time	`-10m@m`
Schedule Window	`auto`
Creates Finding (Notable)	No
Creates Intermediate Finding (Risk Event)	Yes

Anomaly detections generate Intermediate Findings (Risk Events). They do not generate a Finding (Notable) directly.

Implementation

Zeek HTTP logs must be ingested into Splunk using the latest version of Splunk Add-on for Zeek (https://splunkbase.splunk.com/app/5466). Configure the zeek_http macro to match the sourcetype used by your Zeek add-on.

Known False Positives

Applications may upload files with names containing serialized-looking text as part of testing or unusual workflows. Review the complete request headers, source, destination, and application context before determining intent.

Associated Analytic Story

PHP2Shell

Intermediate Findings

Message	Entity Field	Entity Type	Risk Score
A multipart POST request from [$src$] to [$dest$] included PHP_SESSION_UPLOAD_PROGRESS and a serialized PHP structure in an upload filename.	dest	system	40

Threat Objects

Field	Type
src	ip_address
serialized_filename_headers	file_name

References

Detection Testing

Test Type	Status	Dataset	Source	Sourcetype
Validation	✅ Passing	N/A	N/A	N/A
Unit	✅ Passing	Dataset	`http.log`	`zeek:http`
Integration	✅ Passing	Dataset	`http.log`	`zeek:http`

Replay any dataset to Splunk Enterprise by using our replay.py tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

Source: GitHub |

Version: 1