mal-2026-14587
Vulnerability from ossf_malicious_packages
-= Per source details. Do not edit below this line.=-
Source: amazon-inspector (fdef1a055b3059d56581d5c0d33538e7799cfde5e42d596eb50094d06d984f54)
setup.py registers a custom install command that forks a daemonized child during pip install and executes a base64-encoded Python payload via exec(compile(...)). The decoded payload connects to a hardcoded C2 host at 5uj0a8ziyu.localto.net:3900 and provides an interactive reverse shell by duplicating the socket onto stdin/stdout/stderr of /bin/bash (via pty.spawn) or /bin/sh -i, with a 15-second reconnect loop. It also enumerates environment variables matching API, TOKEN, KEY, SECRET, PASS, CRED, AUTH, AWS, AZURE, GCP, OPENAI, ANTHROPIC, and MANUS, reads /etc/passwd, /etc/sudoers, /etc/shadow, ~/.bash_history, and /opt/.manus/current/config, and sends the collected data over TCP to the same host framed with [EXFIL]/[ENDEXFIL] markers. Persistence is established by writing /tmp/.rk_recon.py, installing a per-minute crontab entry, dropping a renderkit.service systemd user unit with Restart=always, and writing /etc/sudoers.d/.renderkit granting the current user NOPASSWD: ALL. The payload is stored as a base64-encoded template with %%HOST%%/%%PORT%% placeholders and the installer forks with start_new_session=True to hide from pip output. The package presents as a pygame utility; none of this behavior matches that stated purpose.
Source: kam193 (5856daeb3070a9b2a6ffc42d8999ff49c63706ccb27ee683e5fcc4ff175f78f9)
During installation, the package attempts to exfiltrate sensitive environment variables and files, establish persistence and open reverse shell.
Category: MALICIOUS - The campaign has clearly malicious intent, like infostealers.
Campaign: 2026-08-pygame-renderkit
Reasons (based on the campaign):
-
persistence
-
The package overrides the install command in setup.py to execute malicious code during installation.
-
The package contains code to create a reverse shell, allowing an attacker to execute any commands on the victim's machine.
-
files-exfiltration
-
exfiltration-env-variables
- CWE-506 - The product contains code that appears to be malicious in nature.
{
"affected": [
{
"database_specific": {
"cwes": [
{
"cweId": "CWE-506",
"description": "The product contains code that appears to be malicious in nature.",
"name": "Embedded Malicious Code"
}
],
"indicators": {
"evidence_files": [
{
"path": "setup.py",
"sha256": "83c3b28f0de6d30aceaf2fac3b115a37590aae1414484cc23a26999a5b485500",
"tlsh": "86f1b696c9891134d7d38677201a9541169bb4279f0768b47ffc8340dfce37911b93ba"
}
],
"package_integrity": [
{
"filename": "pygame_renderkit-1.2.0-py3-none-any.whl",
"hashes": {
"blake2b_256": "4c8dd740c2ea9776c89c059449e28d532c505823e02b9ad8265c320fc17bdc36",
"md5": "88fd83e2478825d7f07f68f7bf23fe7e",
"sha256": "3dfb0db9f896161286b54dcd498f487caa79d5cee1499654e84991dff73ac2e6"
}
},
{
"filename": "pygame_renderkit-1.2.0.tar.gz",
"hashes": {
"blake2b_256": "92b64748449078ce86e6f7d88fbb56965078d39bc41e852c6b34776373904f65",
"md5": "2159afa43a753fea6577d1cfcedec980",
"sha256": "2bea5d7ee5dd2eef24485a804bc0badc240157b14a67e5f3c6e3765eb6675a69"
}
}
]
}
},
"package": {
"ecosystem": "PyPI",
"name": "pygame-renderkit"
},
"versions": [
"1.2.0"
]
}
],
"credits": [
{
"contact": [
"inspector-research@amazon.com"
],
"name": "Amazon Inspector",
"type": "FINDER"
},
{
"contact": [
"https://github.com/kam193",
"https://bad-packages.kam193.eu/"
],
"name": "Kamil Ma\u0144kowski (kam193)",
"type": "REPORTER"
}
],
"database_specific": {
"iocs": {
"domains": [
"5uj0a8ziyu.localto.net"
]
},
"malicious-packages-origins": [
{
"id": "pypi/2026-08-pygame-renderkit/pygame-renderkit",
"import_time": "2026-08-28T10:38:59.563679787Z",
"modified_time": "2026-08-28T09:55:47.226508Z",
"sha256": "5856daeb3070a9b2a6ffc42d8999ff49c63706ccb27ee683e5fcc4ff175f78f9",
"source": "kam193",
"versions": [
"1.2.0"
]
},
{
"id": "IN-MAL-2026-018804",
"import_time": "2026-08-28T19:33:50.163054566Z",
"modified_time": "2026-08-28T16:43:31Z",
"sha256": "fdef1a055b3059d56581d5c0d33538e7799cfde5e42d596eb50094d06d984f54",
"source": "amazon-inspector",
"versions": [
"1.2.0"
]
},
{
"id": "pypi/2026-08-pygame-renderkit/pygame-renderkit",
"import_time": "2026-08-29T12:23:15.012408983Z",
"modified_time": "2026-08-28T09:55:47.226508Z",
"sha256": "039ea05d12048144a31dfde021c4b725fbceb2634d816cca4a97776bc2c55140",
"source": "kam193",
"versions": [
"1.2.0"
]
}
]
},
"details": "\n---\n_-= Per source details. Do not edit below this line.=-_\n\n## Source: amazon-inspector (fdef1a055b3059d56581d5c0d33538e7799cfde5e42d596eb50094d06d984f54)\nsetup.py registers a custom install command that forks a daemonized child during pip install and executes a base64-encoded Python payload via exec(compile(...)). The decoded payload connects to a hardcoded C2 host at 5uj0a8ziyu.localto.net:3900 and provides an interactive reverse shell by duplicating the socket onto stdin/stdout/stderr of /bin/bash (via pty.spawn) or /bin/sh -i, with a 15-second reconnect loop. It also enumerates environment variables matching API, TOKEN, KEY, SECRET, PASS, CRED, AUTH, AWS, AZURE, GCP, OPENAI, ANTHROPIC, and MANUS, reads /etc/passwd, /etc/sudoers, /etc/shadow, ~/.bash_history, and /opt/.manus/current/config, and sends the collected data over TCP to the same host framed with [EXFIL]/[ENDEXFIL] markers. Persistence is established by writing /tmp/.rk_recon.py, installing a per-minute crontab entry, dropping a renderkit.service systemd user unit with Restart=always, and writing /etc/sudoers.d/.renderkit granting the current user NOPASSWD: ALL. The payload is stored as a base64-encoded template with %%HOST%%/%%PORT%% placeholders and the installer forks with start_new_session=True to hide from pip output. The package presents as a pygame utility; none of this behavior matches that stated purpose.\n\n## Source: kam193 (5856daeb3070a9b2a6ffc42d8999ff49c63706ccb27ee683e5fcc4ff175f78f9)\nDuring installation, the package attempts to exfiltrate sensitive environment variables and files, establish persistence and open reverse shell.\n\n\n---\n\nCategory: MALICIOUS - The campaign has clearly malicious intent, like infostealers.\n\n\nCampaign: 2026-08-pygame-renderkit\n\n\nReasons (based on the campaign):\n\n\n - persistence\n\n\n - The package overrides the install command in setup.py to execute malicious code during installation.\n\n\n - The package contains code to create a reverse shell, allowing an attacker to execute any commands on the victim\u0027s machine.\n\n\n - files-exfiltration\n\n\n - exfiltration-env-variables\n",
"id": "MAL-2026-14587",
"modified": "2026-08-29T12:25:04.083227376Z",
"published": "2026-08-28T09:55:47Z",
"references": [
{
"type": "WEB",
"url": "https://bad-packages.kam193.eu/pypi/package/pygame-renderkit"
},
{
"type": "PACKAGE",
"url": "https://pypi.org/project/pygame-renderkit/1.2.0/"
}
],
"schema_version": "1.7.4",
"summary": "Malicious code in pygame-renderkit (PyPI)"
}
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.