Decepticon is an autonomous red-team agent that coordinates AI agents, security tools, sandboxes, and supporting services for authorized cybersecurity assessments. Security researchers and red teams can run it through its Docker stack, cloud service, command-line interface, or Python SDK, with the catalogue entries representing its available skills.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/purpleailab/decepticon/cicdnpx skills add PurpleAILAB/Decepticon --skill cicdgit clone --depth 1 https://github.com/PurpleAILAB/DecepticonWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/purpleailab/decepticon/cicd)<a href="https://agentmods.dev/skills/purpleailab/decepticon/cicd"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/cicd.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00049 | $0.02007 |
| Opus 5 | $0.00024 | $0.01004 |
| Sonnet 5 | $0.00010 | $0.00401 |
| Haiku 4.5 | $0.00005 | $0.00201 |
Grade A, and why
cicd scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CI/CD Pipeline Exploitation — Category Overview
Routing skill for attacks against build / deployment pipelines. Pipelines run attacker-influenced code (PRs, dependencies, build scripts) with privileged tokens, cloud OIDC, and write access to artifacts that downstream consumers trust. Compromise of a single pipeline often equals compromise of every release built by it.
Sub-Skills
| Sub-Skill | Covers | When to Load |
|---|---|---|
| poisoned-pipeline-execution | Direct + Indirect PPE: injecting commands via attacker-controllable build files (Makefile, package.json scripts, build.gradle, Dangerfile, .pre-commit-config.yaml), pull_request_target abuse, fork-PR build triggers, dependency/test-script execution. |
Target builds untrusted PR code; you can land a malicious file or dependency. |
| github-actions-injection | ${{ }} template injection via untrusted context (issue/PR title, body, branch name, commit message) into run: steps, pull_request_target + PR-head checkout, GITHUB_TOKEN permission abuse, artifact/cache poisoning, action pinning (tag vs SHA). |
Target uses GitHub Actions and accepts external contributors. |
| self-hosted-runner-abuse | Non-ephemeral runner persistence, fork-PR job execution on self-hosted, runner-label targeting, secret theft from runner env, lateral movement into internal network / cloud metadata. | Target advertises self-hosted runners (workflow runs-on: label or public job logs). |
| cicd-secrets-exfil | Extracting CI secrets / OIDC tokens: echo / printenv exfil, masking bypass (base64, char-split), OIDC -> cloud role assumption, GITHUB_TOKEN / CI_JOB_TOKEN scope abuse, cache / artifact secret leakage. |
You already have code execution in a CI job; need to convert it into durable cloud / registry access. |
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 111 lines · 49 tokens per session scan A 4bae8df8bf39
cicd is a skill published in the GitHub repository PurpleAILAB/Decepticon (5,450 stars, last pushed 6d ago), licensed Apache-2.0. It adds 49 tokens to every session and 2,007 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
deployment-pipeline-design
Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use when architecting deployment workflows, setting up continuous delivery, or implementing GitOps practices.
interactive-dashboard
Interactive web dashboards: stock trackers, sector heatmaps, portfolio monitors — served via preview URL.
onboarding
First-time user onboarding to set up investment profile, watchlists, portfolio, and preferences.
meta-long-running-build-watchdog
Watches a long-running command via tmux, lets sub-agent diagnose failures and propose a fix, and records the diagnosis to memory. Designed for overnight model fine-tunes, CI image builds, or repeated regression suites that may fail intermittently.
deploying-to-staging-environment
Use when deploying changes to staging across relay, relay-dashboard, and relay-cloud repos - coordinates multi-repo branch syncing using git worktrees, automatically triggers staging deployments via GitHub Actions.
idea-generation
Stock screening and idea generation: quantitative screens, thematic analysis, shortlist.