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 skills add PurpleAILAB/Decepticon --skill corsgit 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/cors)<a href="https://agentmods.dev/skills/purpleailab/decepticon/cors"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/cors/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/cors"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/cors.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Prompt Injection · line 54 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00031 | $0.01261 |
| Opus 5 | $0.00015 | $0.00630 |
| Sonnet 5 | $0.00006 | $0.00252 |
| Haiku 4.5 | $0.00003 | $0.00126 |
Grade A, and why
cors 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 9d 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.
curl -s -D- -o /dev/null "https://<TARGET>/api/account" -H "Origin: $o" \ How it starts
The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CORS Misconfiguration Playbook
A permissive Access-Control-Allow-Origin (ACAO) becomes critical the moment it
is paired with Access-Control-Allow-Credentials: true (ACAC) — any origin the
server reflects can read authenticated responses (PII, API keys, CSRF tokens).
ACAO alone (no credentials) is usually Low unless the endpoint serves secrets to
unauthenticated requests.
1. Detection — probe origin reflection
# Reflected-origin + credentials = the critical case
for o in "https://evil.com" "null" "https://<TARGET>.evil.com" "https://evil.com.<TARGET>"; do
echo "== Origin: $o =="
curl -s -D- -o /dev/null "https://<TARGET>/api/account" -H "Origin: $o" \
| grep -i "access-control-allow-origin\|access-control-allow-credentials"
done
# Preflight behaviour (which methods/headers are allowed cross-origin)
curl -s -D- -o /dev/null -X OPTIONS "https://<TARGET>/api/account" \
-H "Origin: https://evil.com" \
-H "Access-Control-Request-Method: PUT" \
-H "Access-Control-Request-Headers: authorization" \
| grep -i "access-control-"
A response echoing Access-Control-Allow-Origin: https://evil.com and
Access-Control-Allow-Credentials: true confirms exploitable reflection.
2. Misconfiguration matrix
| Class | Server behaviour | Exploit origin |
|---|---|---|
| Origin reflection | ACAO echoes any Origin + ACAC true |
https://evil.com |
null allowed |
ACAO: null + ACAC true | sandboxed iframe / data:/file: (sends Origin: null) |
| Wildcard + creds (browser-blocked, but check tooling) | ACAO: * with secrets |
only if creds not required |
| Suffix match flaw | allows *target.com |
https://evil-target.com |
| Prefix match flaw | allows target.com* |
https://target.com.evil.com |
| Unescaped dot in regex | ^https://app.target.com$ |
https://appxtarget.com |
| Trusted subdomain + XSS | allows *.target.com |
XSS on any subdomain → same-site fetch |
| Pre-domain confusion | naive contains("target.com") |
https://target.com.evil.com, https://eviltarget.com |
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.
- 9d ago First seen · 100 lines · 31 tokens per session scan A 6ae3ed9cf31a
cors is a skill published in the GitHub repository PurpleAILAB/Decepticon (5,497 stars, last pushed 13d ago), licensed Apache-2.0. It adds 31 tokens to every session and 1,261 once invoked, about $0.0002 per session on Opus 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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