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Introduction:
The modern attack surface is expanding at an unprecedented rate, with API endpoints, cloud infrastructure, and AI-powered applications introducing novel vulnerability classes that traditional scanners routinely miss. SoloSec Arsenal emerges as a comprehensive, production-grade template library that bridges the gap between static analysis (SAST) and dynamic analysis (DAST), offering security researchers a unified framework to automate reconnaissance, detect high-impact vulnerabilities, and generate proof-of-concept exploits — all from a single command.
Learning Objectives:
- Master the deployment and execution of an automated bug-bounty pipeline that combines reconnaissance, authenticated scanning, deduplication, and dashboard reporting.
- Understand how to leverage custom Nuclei templates for detecting OIDC/OAuth flaws, cloud metadata leaks, API logic vulnerabilities (BOLA/BFLA), and GraphQL misconfigurations.
- Implement high-signal SAST rules using CodeQL and Semgrep to catch SSRF, command injection, and path traversal vulnerabilities before they reach production.
You Should Know:
1. Understanding the SoloSec Arsenal Architecture
SoloSec Arsenal is not merely a collection of security tools — it is a meticulously organized framework designed to cover the full vulnerability spectrum from source-code flaws to live-target exploitation. The repository is structured into specialized directories that mirror modern attack surfaces:
– `nuclei/` — Dynamic analysis (DAST) templates covering CVEs (2017–2024, KEV/EPSS), exposures (leaked files, secrets, config disclosure), vulnerabilities (SQLi, XSS, SSRF, SSTI, LFI, RCE, XXE), modern web flaws (smuggling, cache poisoning, GraphQL, JWT, prototype pollution), access control (IDOR/BOLA, mass assignment, CORS), cloud metadata SSRF, OAuth/OIDC/SAML flaws, and AI/LLM prompt injection.
– `semgrep/` — Static analysis rules for Python, JavaScript, Java, Go, PHP, Ruby, C, C++, with additional rules for CI/CD pipeline security, Infrastructure-as-Code (Docker, Terraform, Kubernetes), and secret detection.
– `codeql/` — Deep dataflow static analysis for identifying complex vulnerability chains.
– `trivy/` — IaC, container, and dependency scanning.
– `scripts/` — Runners, CI pipelines, recon automation, and an adaptive payload generator.
The toolkit ships with 285+ curated Nuclei templates and supports approximately 150 auto-installed security tools. The core automation script, secsuite.sh, orchestrates the entire pipeline: reconnaissance → authentication → scanning (both unauthenticated and authenticated) → deduplication → PoC generation → dashboard reporting.
Step‑by‑Step Guide:
To deploy SoloSec Arsenal on a Linux system:
Clone the repository git clone https://github.com/FURQANAHMAD34/security-templates.git cd security-templates Make scripts executable chmod +x scripts/.sh Run the full automation pipeline ./scripts/run-all.sh Or use the one-shot command for a complete recon-to-dashboard workflow ./scripts/oneshot.sh -u https://target.com
For Windows environments, PowerShell equivalents are provided:
PowerShell execution .\scripts\run-all.ps1 -Target "https://target.com"
The `recon-master.sh` script performs comprehensive asset discovery, subdomain enumeration, and technology fingerprinting before passing results to the scanning engine. The adaptive payload generator in `nuclei/fuzzing/` dynamically adjusts payloads based on runtime responses, significantly reducing false positives.
2. Custom Nuclei Template Development for Zero-Day Discovery
The `nuclei/_skeletons/` directory provides copy-paste starting points for every protocol, enabling rapid template development. This is particularly valuable for bug bounty hunters who need to test for logic flaws that commercial scanners overlook.
Step‑by‑Step Guide to Creating a Custom Template:
1. Copy the skeleton template:
cp nuclei/_skeletons/http.yaml nuclei/custom/my-custom-template.yaml
2. Define the request structure:
id: custom-api-bola
info:
name: API BOLA Detection
author: researcher
severity: high
description: Detects insecure direct object references in API endpoints
requests:
- method: GET
path:
- "{{BaseURL}}/api/v1/users/{{user_id}}"
headers:
Authorization: "Bearer {{token}}"
3. Add matchers for vulnerability confirmation:
matchers-condition: and matchers: - type: status status: - 200 - type: word words: - "email" - "phone" condition: or
4. Execute the custom template:
nuclei -t nuclei/custom/ -u https://target.com -o results.txt
The `nuclei/access-control/` directory contains specialized templates for IDOR/BOLA, mass assignment, forced browsing, and CORS misconfigurations. The `nuclei/api/` folder addresses API-specific flaws including Swagger/OpenAPI exposure, GraphQL introspection, JWT algorithm confusion, and rate-limiting bypasses.
3. SAST Implementation with CodeQL and Semgrep
Static analysis forms the foundation of shift-left security. SoloSec Arsenal provides high-signal SAST rules that catch critical vulnerabilities before code reaches production.
Step‑by‑Step Guide to Running SAST Scans:
For Semgrep (Python/JavaScript focused):
Install Semgrep pip install semgrep Run Python rules semgrep --config semgrep/python/ --config semgrep/secrets/ /path/to/source Run JavaScript rules semgrep --config semgrep/javascript/ /path/to/source Run all rules across multiple languages semgrep --config semgrep/ /path/to/source
For CodeQL (Deep dataflow analysis):
Create a CodeQL database codeql database create ./db --language=python --source-root=/path/to/source Run CodeQL queries codeql database analyze ./db codeql/ --format=sarif-latest --output=results.sarif
The `semgrep/cicd/` directory includes rules for detecting GitHub Actions script injection, pwn-requests, and supply-chain vulnerabilities. The `semgrep/iac/` folder covers Dockerfile misconfigurations, Terraform security issues, and Kubernetes hardening gaps.
4. Cloud Security and Exposure Scanning
Cloud misconfigurations remain one of the leading causes of data breaches. SoloSec Arsenal includes dedicated templates for detecting exposed Kubernetes APIs, misconfigured Docker engines, and cloud credential leaks.
Step‑by‑Step Guide to Cloud Exposure Scanning:
1. Detect cloud metadata endpoints (SSRF to cloud):
nuclei -t nuclei/cloud/ -u https://target.com
2. Check for exposed K8s APIs:
nuclei -t nuclei/cloud/kubernetes-api.yaml -u https://target.com:6443
3. Scan for misconfigured Docker daemons:
nuclei -t nuclei/cloud/docker-exposed.yaml -u https://target.com:2375
- Detect public S3 buckets and Azure Blob exposures:
nuclei -t nuclei/exposures/bucket-takeover.yaml -u https://target.com
The `nuclei/auth/` directory provides comprehensive testing for OAuth/OIDC/SAML flaws, 2FA bypass techniques, and JWT kid injection vulnerabilities. The `nuclei/modern/` folder addresses emerging threats including HTTP smuggling, cache poisoning, GraphQL introspection, and prototype pollution.
5. AI/LLM Security Testing
With the proliferation of AI-powered applications, the `nuclei/ai/` directory addresses prompt injection attacks, exposed AI keys and endpoints, framework debug modes, and AI-specific SSRF vulnerabilities.
Step‑by‑Step Guide to AI Security Testing:
1. Test for prompt injection:
nuclei -t nuclei/ai/prompt-injection.yaml -u https://ai-target.com
2. Detect exposed AI endpoints:
nuclei -t nuclei/ai/exposed-endpoints.yaml -u https://target.com
3. Check for framework debug mode exposure:
nuclei -t nuclei/ai/framework-debug.yaml -u https://target.com
6. Reconnaissance and Attack Surface Mapping
The reconnaissance pipeline, orchestrated by recon-master.sh, automates subdomain enumeration, technology detection, and asset discovery.
Step‑by‑Step Guide to Running Recon:
Run full reconnaissance pipeline ./scripts/recon-master.sh -d target.com The script performs: - Subdomain enumeration (Subfinder, Assetfinder) - Port scanning (Nmap) - Technology fingerprinting (Wappalyzer, WhatWeb) - Endpoint discovery (Gospider, Katana) - Screenshotting (Gowitness)
The results feed directly into the scanning engine, ensuring that all discovered assets are tested against the full template library.
What Undercode Say:
- SoloSec Arsenal represents a paradigm shift in how security researchers approach bug bounty and penetration testing. By combining SAST and DAST into a unified pipeline, it eliminates the fragmentation that plagues traditional security workflows. The inclusion of AI/LLM-specific templates demonstrates a forward-thinking approach to emerging threats.
-
The emphasis on authenticated scanning and adaptive payload generation addresses the single biggest criticism of automated scanners: false positives. The `oneshot.sh` script’s ability to authenticate and then scan both unauthenticated and authenticated endpoints ensures comprehensive coverage while minimizing noise.
Analysis: The toolkit’s structure reveals a deep understanding of modern attack surfaces. The separation of templates into cves/, exposures/, vulnerabilities/, modern/, access-control/, headers/, api/, cloud/, auth/, and `ai/` directories mirrors the OWASP Top 10 and beyond. The inclusion of `_skeletons/` for rapid template development empowers researchers to quickly operationalize new findings. The adaptive fuzzing engine in `nuclei/fuzzing/` represents a significant advancement over static payload lists, dynamically adjusting based on runtime responses. The CI/CD rules in `semgrep/cicd/` acknowledge that modern security must extend into the development pipeline. The author’s background in reverse engineering, CTF competitions, and Black Hat MEA appearances lends credibility to the toolkit’s practical applicability. The 285+ templates and 150+ auto-installed tools position SoloSec Arsenal as a comprehensive solution for both beginners and experienced practitioners.
Prediction:
- +1 SoloSec Arsenal will accelerate the democratization of advanced security testing, enabling smaller security teams to achieve enterprise-grade coverage without massive tooling budgets.
-
+1 The adaptive payload generation and authenticated scanning capabilities will set a new standard for DAST tools, pushing commercial vendors to evolve their offerings.
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-1 The increasing accessibility of sophisticated attack templates may lead to a rise in script-kiddie activity, as less-skilled actors leverage the toolkit for unauthorized scanning.
-
+1 The AI/LLM security templates will become increasingly critical as organizations rush to deploy generative AI applications without adequate security controls.
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-1 Organizations that fail to implement proper API security, cloud hardening, and SAST practices will face increased exposure as bug bounty hunters leverage these templates to discover vulnerabilities faster.
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+1 The open-source nature of SoloSec Arsenal will foster community-driven template development, ensuring rapid coverage of newly disclosed CVEs and emerging attack vectors.
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+1 The integration of SAST and DAST into a single pipeline will promote a more holistic approach to application security, bridging the gap between developers and security teams.
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