# Exploiting Server Side Request Forgery

> Use when identifying and exploiting SSRF vulnerabilities to access internal services, cloud metadata, and restricted network resources during authorized penetration tests. Use when working with exploiting server side request forgery.

- Skill: `oyi77/exploiting-server-side-request-forgery` (Agent Skill)
- Install (CLI): `npx skillmds add oyi77/exploiting-server-side-request-forgery`
- Raw SKILL.md: https://api.skillmd.com/api/skills/oyi77/exploiting-server-side-request-forgery/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: DevOps & Infra
- License: Apache-2.0
- Author: oyi77 (https://skillmd.com/u/oyi77)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/oyi77/exploiting-server-side-request-forgery

---


# Exploiting Server Side Request Forgery

## Overview

Cybersecurity skill for exploiting server side request forgery. Follows industry best practices and security standards.

## When to Use
**Trigger phrases:**
- "exploiting server side request forgery"
- "Identifying and exploiting SSRF vulnerabilities to access internal services, clo"


- During authorized penetration tests when the application fetches URLs provided by users (webhooks, URL previews, file imports)
- When testing cloud-hosted applications for access to instance metadata services
- For assessing PDF generators, screenshot services, or any feature that renders external content
- When evaluating microservice architectures for internal service access via SSRF
- During security assessments of APIs that accept URL parameters for data fetching


## When NOT to Use

- When you lack proper authorization for testing
- For production systems without change management
- When the task requires legal or compliance expertise beyond technical scope


## Prerequisites

- **Authorization**: Written penetration testing agreement including SSRF testing scope
- **Burp Suite Professional**: With Collaborator for out-of-band detection
- **interactsh**: Open-source OOB interaction server (`go install github.com/projectdiscovery/interactsh/cmd/interactsh-client@latest`)
- **SSRFmap**: Automated SSRF exploitation framework (`git clone https://github.com/swisskyrepo/SSRFmap.git`)
- **curl**: For manual SSRF payload testing
- **Knowledge of target infrastructure**: Cloud provider (AWS, GCP, Azure), internal IP ranges

## Workflow

```python
# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}
```

1. **Reconnaissance** — Gather information about the target related to server side request forgery. Identify attack surface.
2. **Vulnerability Identification** — Enumerate potential server side request forgery weaknesses using automated and manual techniques.
3. **Exploit Development/Selection** — Choose or develop exploits targeting identified server side request forgery vulnerabilities.
4. **Execution** — Execute the server side request forgery test in a controlled manner with proper authorization.
5. **Post-Exploitation** — Document the impact and extent of successful exploitation.
6. **Reporting** — Write detailed findings with reproduction steps, impact assessment, and remediation guidance.

## Tools

- **Vulnerability Scanner** — Automated weakness identification
- **Exploitation Framework** — Controlled exploitation testing
- **Reporting Tool** — Findings documentation and tracking


## Process

1. **Reconnaissance** — Gather target information, identify attack surface, enumerate services
1. **Analysis/Exploitation** — Execute the technique, analyze results, document findings
1. **Reporting** — Document IOCs, write findings, provide remediation recommendations

## Verification

- [ ] All server side request forgery procedures executed completely and documented
- [ ] Findings validated against multiple data sources
- [ ] False positives identified and filtered
- [ ] Results documented with evidence and timestamps
- [ ] Recommendations provided with risk-based prioritization

## Anti-Rationalization Table

| Rationalization | Reality |
|---|---|
| "We are too small to be targeted" | Automated attacks target everyone. Size does not matter. |
| "Security slows us down" | A breach slows you down 100x more. Build security in from the start. |
| "We will fix it after launch" | Vulnerabilities in production are exploited within hours. Fix before deploy. |