Phoenix Studio

Convert indexed Sigma rules into analyst-ready detections.

This studio is built around Phoenix's own rule corpus, not a blank editor. Search by title or rule id, choose a local pySigma backend, then reveal pipelines only when you actually need them.

Indexed Rules

3,779

Ready to search

Backends

3

Loaded from pysigma-node

pySigma Versions

2

Newest: 2.0.1

Translation Workspace

Shape the rule before it leaves Phoenix

Tune Translation

Active Rule

Shell Spawned by Celery Worker Process

Backends follow their supported pySigma version. Select 1.5.1 for Elasticsearch, Kusto, and other 1.x plugins.

Target Profile

Splunk

Splunk through pysigma-backend-splunk.

Format Mode

Default

Default pySigma output mode for this backend.

Conversion Output

Shell Spawned by Celery Worker Process

Using Splunk · Default · pySigma 2.0.1

Translation controls

Adjust the rule on the left, then regenerate when you want a fresh backend-native query.

BackendSplunkFormatDefaultVersion2.0.1
title: Shell Spawned by Celery Worker Process
id: 904f6442-3b57-4b3f-987c-1559f58ce8d8
status: experimental
description: |
    Detects a system shell interpreter being spawned directly by a Celery worker process.
    This behavior indicates a Python background task execution framework is evaluating raw string input through a shell execution context,
    which is highly indicative of successful command or prompt injection exploitation against an LLM agent task.
references:
    - https://docs.celeryq.dev/en/stable/userguide/tasks.html
    - https://genai.owasp.org/llmrisk/llm01-prompt-injection/
    - https://labs.cloudsecurityalliance.org/research/csa-research-note-promptware-c2-agent-exploitation-20260406/
    - https://nvd.nist.gov/vuln/detail/CVE-2021-23727
    - https://owasp.org/www-project-top-10-for-large-language-model-applications/
    - https://security.snyk.io/vuln/SNYK-PYTHON-CELERY-2314953
    - https://snyk.io/blog/python-rce-vulnerability/
    - https://unit42.paloaltonetworks.com/ai-agent-prompt-injection/
    - https://www.microsoft.com/en-us/security/blog/2026/05/07/prompts-become-shells-rce-vulnerabilities-ai-agent-frameworks
author: Jennifer Batina
date: 2026-10-17
tags:
    - attack.execution
    - attack.t1059.004
logsource:
    category: process_creation
    product: linux
detection:
    selection_img:
        Image|endswith:
            - '/ash'
            - '/bash'
            - '/busybox'
            - '/csh'
            - '/dash'
            - '/fish'
            - '/ksh'
            - '/sh'
            - '/tcsh'
            - '/zsh'
        ParentCommandLine|contains: 'celery'
    selection_parent:
        - ParentImage|endswith:
              - '/python'
              - '/python3'
        - ParentImage|contains: '/python3.'
    condition: all of selection_*
falsepositives:
    - Legacy or custom administrative tasks deliberately hardcoded with shell=True or os.system execution inside Celery task functions.
    - Media processing, deployment, or reporting pipelines that intentionally shell out to external tools (e.g. ffmpeg, git) from within a task.
level: medium

CLI command

Sigma CLI 4.0.0 · Install matching versions, then run from the Phoenix project directory.

python -m pip install 'sigma-cli==4.0.0' 'pysigma==2.0.1' 'pysigma-backend-splunk==3.0.0' sigma convert --without-pipeline -t splunk -f default 'sigma/rules/linux/process_creation/proc_creation_lnx_celery_worker_shell_spawn.yml'