Vulnerability Scanner

Advanced vulnerability analysis principles. OWASP 2025, Supply Chain Security, attack surface mapping, risk prioritization.

techwavedev Updated Sep 10, 2026

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Trust & safety

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Permissions this skill uses

Executes scripts
The instructions run shell commands or bundled script files.
Reads secrets
The instructions read tokens, keys, or other credentials.

Works with: Claude Code Claude.ai OpenAI Codex +

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Vulnerability Scanner

Think like an attacker, defend like an expert. 2025 threat landscape awareness.

🔧 Runtime Scripts

Execute for automated validation:

Script	Purpose	Usage
`scripts/security_scan.py`	Validate security principles applied	`python scripts/security_scan.py <project_path>`

📋 Reference Files

File	Purpose
checklists.md	OWASP Top 10, Auth, API, Data protection checklists

1. Security Expert Mindset

Core Principles

Principle	Application
Assume Breach	Design as if attacker already inside
Zero Trust	Never trust, always verify
Defense in Depth	Multiple layers, no single point
Least Privilege	Minimum required access only
Fail Secure	On error, deny access

Threat Modeling Questions

Before scanning, ask:

What are we protecting? (Assets)
Who would attack? (Threat actors)
How would they attack? (Attack vectors)
What's the impact? (Business risk)

2. OWASP Top 10:2025

Risk Categories

Rank	Category	Think About
A01	Broken Access Control	Who can access what? IDOR, SSRF
A02	Security Misconfiguration	Defaults, headers, exposed services
A03	Software Supply Chain 🆕	Dependencies, CI/CD, build integrity
A04	Cryptographic Failures	Weak crypto, exposed secrets
A05	Injection	User input → system commands
A06	Insecure Design	Flawed architecture
A07	Authentication Failures	Session, credential management
A08	Integrity Failures	Unsigned updates, tampered data
A09	Logging & Alerting	Blind spots, no monitoring
A10	Exceptional Conditions 🆕	Error handling, fail-open states

2025 Key Changes

2021 → 2025 Shifts:
├── SSRF merged into A01 (Access Control)
├── A02 elevated (Cloud/Container configs)
├── A03 NEW: Supply Chain (major focus)
├── A10 NEW: Exceptional Conditions
└── Focus shift: Root causes > Symptoms

3. Supply Chain Security (A03)

Attack Surface

Vector	Risk	Question to Ask
Dependencies	Malicious packages	Do we audit new deps?
Lock files	Integrity attacks	Are they committed?
Build pipeline	CI/CD compromise	Who can modify?
Registry	Typosquatting	Verified sources?

Defense Principles

Verify package integrity (checksums)
Pin versions, audit updates
Use private registries for critical deps
Sign and verify artifacts

4. Attack Surface Mapping

What to Map

Category	Elements
Entry Points	APIs, forms, file uploads
Data Flows	Input → Process → Output
Trust Boundaries	Where auth/authz checked
Assets	Secrets, PII, business data

Prioritization Matrix

Risk = Likelihood × Impact

High Impact + High Likelihood → CRITICAL
High Impact + Low Likelihood  → HIGH
Low Impact + High Likelihood  → MEDIUM
Low Impact + Low Likelihood   → LOW

5. Risk Prioritization

CVSS + Context

Factor	Weight	Question
CVSS Score	Base severity	How severe is the vuln?
EPSS Score	Exploit likelihood	Is it being exploited?
Asset Value	Business context	What's at risk?
Exposure	Attack surface	Internet-facing?

Prioritization Decision Tree

Is it actively exploited (EPSS >0.5)?
├── YES → CRITICAL: Immediate action
└── NO → Check CVSS
         ├── CVSS ≥9.0 → HIGH
         ├── CVSS 7.0-8.9 → Consider asset value
         └── CVSS <7.0 → Schedule for later

6. Exceptional Conditions (A10 - New)

Fail-Open vs Fail-Closed

Scenario	Fail-Open (BAD)	Fail-Closed (GOOD)
Auth error	Allow access	Deny access
Parsing fails	Accept input	Reject input
Timeout	Retry forever	Limit + abort

What to Check

Exception handlers that catch-all and ignore
Missing error handling on security operations
Race conditions in auth/authz
Resource exhaustion scenarios

7. Scanning Methodology

Phase-Based Approach

1. RECONNAISSANCE
   └── Understand the target
       ├── Technology stack
       ├── Entry points
       └── Data flows

2. DISCOVERY
   └── Identify potential issues
       ├── Configuration review
       ├── Dependency analysis
       └── Code pattern search

3. ANALYSIS
   └── Validate and prioritize
       ├── False positive elimination
       ├── Risk scoring
       └── Attack chain mapping

4. REPORTING
   └── Actionable findings
       ├── Clear reproduction steps
       ├── Business impact
       └── Remediation guidance

8. Code Pattern Analysis

High-Risk Patterns

Pattern	Risk	Look For
String concat in queries	Injection	`"SELECT * FROM " + user_input`
Dynamic code execution	RCE	`eval()`, `exec()`, `Function()`
Unsafe deserialization	RCE	`pickle.loads()`, `unserialize()`
Path manipulation	Traversal	User input in file paths
Disabled security	Various	`verify=False`, `--insecure`

Secret Patterns

Type	Indicators
API Keys	`api_key`, `apikey`, high entropy
Tokens	`token`, `bearer`, `jwt`
Credentials	`password`, `secret`, `key`
Cloud	`AWS_`, `AZURE_`, `GCP_` prefixes

9. Cloud Security Considerations

Shared Responsibility

Layer	You Own	Provider Owns
Data	✅	❌
Application	✅	❌
OS/Runtime	Depends	Depends
Infrastructure	❌	✅

Cloud-Specific Checks

IAM: Least privilege applied?
Storage: Public buckets?
Network: Security groups tightened?
Secrets: Using secrets manager?

10. Anti-Patterns

❌ Don't	✅ Do
Scan without understanding	Map attack surface first
Alert on every CVE	Prioritize by exploitability + asset
Ignore false positives	Maintain verified baseline
Fix symptoms only	Address root causes
Scan once before deploy	Continuous scanning
Trust third-party deps blindly	Verify integrity, audit code

11. Reporting Principles

Finding Structure

Each finding should answer:

What? - Clear vulnerability description
Where? - Exact location (file, line, endpoint)
Why? - Root cause explanation
Impact? - Business consequence
How to fix? - Specific remediation

Severity Classification

Severity	Criteria
Critical	RCE, auth bypass, mass data exposure
High	Data exposure, privilege escalation
Medium	Limited scope, requires conditions
Low	Informational, best practice

Remember: Vulnerability scanning finds issues. Expert thinking prioritizes what matters. Always ask: "What would an attacker do with this?"

🧠 AGI Framework Integration

Hybrid Memory Integration (Qdrant + BM25)

Before executing complex tasks with this skill:

python3 execution/memory_manager.py auto --query "<task summary>"

Decision Tree:

Cache hit? Use cached response directly — no need to re-process.
Memory match? Inject context_chunks into your reasoning.
No match? Proceed normally, then store results:

python3 execution/memory_manager.py store \
  --content "Description of what was decided/solved" \
  --type decision \
  --tags vulnerability-scanner <relevant-tags>

Note: Storing automatically updates both Vector (Qdrant) and Keyword (BM25) indices.

Agent Team Collaboration

Strategy: This skill communicates via the shared memory system.
Orchestration: Invoked by orchestrator via intelligent routing.
Context Sharing: Always read previous agent outputs from memory before starting.

Local LLM Support

When available, use local Ollama models for embedding and lightweight inference:

Embeddings: nomic-embed-text via Qdrant memory system
Lightweight analysis: Local models reduce API costs for repetitive patterns

---name: vulnerability-scannerdescription: Advanced vulnerability analysis principles. OWASP 2025, Supply Chain Security, attack surface mapping, risk prioritization.---# Vulnerability Scanner> Think like an attacker, defend like an expert. 2025 threat landscape awareness.## 🔧 Runtime Scripts**Execute for automated validation:**| Script | Purpose | Usage ||--------|---------|-------|| `scripts/security_scan.py` | Validate security principles applied | `python scripts/security_scan.py <project_path>` |## 📋 Reference Files| File | Purpose ||------|---------|| [checklists.md](checklists.md) | OWASP Top 10, Auth, API, Data protection checklists |---## 1. Security Expert Mindset### Core Principles| Principle | Application ||-----------|-------------|| **Assume Breach** | Design as if attacker already inside || **Zero Trust** | Never trust, always verify || **Defense in Depth** | Multiple layers, no single point || **Least Privilege** | Minimum required access only || **Fail Secure** | On error, deny access |### Threat Modeling QuestionsBefore scanning, ask:1. What are we protecting? (Assets)2. Who would attack? (Threat actors)3. How would they attack? (Attack vectors)4. What's the impact? (Business risk)---## 2. OWASP Top 10:2025### Risk Categories| Rank | Category | Think About ||------|----------|-------------|| **A01** | Broken Access Control | Who can access what? IDOR, SSRF || **A02** | Security Misconfiguration | Defaults, headers, exposed services || **A03** | Software Supply Chain 🆕 | Dependencies, CI/CD, build integrity || **A04** | Cryptographic Failures | Weak crypto, exposed secrets || **A05** | Injection | User input → system commands || **A06** | Insecure Design | Flawed architecture || **A07** | Authentication Failures | Session, credential management || **A08** | Integrity Failures | Unsigned updates, tampered data || **A09** | Logging & Alerting | Blind spots, no monitoring || **A10** | Exceptional Conditions 🆕 | Error handling, fail-open states |### 2025 Key Changes```2021 → 2025 Shifts:├── SSRF merged into A01 (Access Control)├── A02 elevated (Cloud/Container configs)├── A03 NEW: Supply Chain (major focus)├── A10 NEW: Exceptional Conditions└── Focus shift: Root causes > Symptoms```---## 3. Supply Chain Security (A03)### Attack Surface| Vector | Risk | Question to Ask ||--------|------|-----------------|| **Dependencies** | Malicious packages | Do we audit new deps? || **Lock files** | Integrity attacks | Are they committed? || **Build pipeline** | CI/CD compromise | Who can modify? || **Registry** | Typosquatting | Verified sources? |### Defense Principles- Verify package integrity (checksums)- Pin versions, audit updates- Use private registries for critical deps- Sign and verify artifacts---## 4. Attack Surface Mapping### What to Map| Category | Elements ||----------|----------|| **Entry Points** | APIs, forms, file uploads || **Data Flows** | Input → Process → Output || **Trust Boundaries** | Where auth/authz checked || **Assets** | Secrets, PII, business data |### Prioritization Matrix```Risk = Likelihood × ImpactHigh Impact + High Likelihood → CRITICALHigh Impact + Low Likelihood → HIGHLow Impact + High Likelihood → MEDIUMLow Impact + Low Likelihood → LOW```---## 5. Risk Prioritization### CVSS + Context| Factor | Weight | Question ||--------|--------|----------|| **CVSS Score** | Base severity | How severe is the vuln? || **EPSS Score** | Exploit likelihood | Is it being exploited? || **Asset Value** | Business context | What's at risk? || **Exposure** | Attack surface | Internet-facing? |### Prioritization Decision Tree```Is it actively exploited (EPSS >0.5)?├── YES → CRITICAL: Immediate action└── NO → Check CVSS ├── CVSS ≥9.0 → HIGH ├── CVSS 7.0-8.9 → Consider asset value └── CVSS <7.0 → Schedule for later```---## 6. Exceptional Conditions (A10 - New)### Fail-Open vs Fail-Closed| Scenario | Fail-Open (BAD) | Fail-Closed (GOOD) ||----------|-----------------|---------------------|| Auth error | Allow access | Deny access || Parsing fails | Accept input | Reject input || Timeout | Retry forever | Limit + abort |### What to Check- Exception handlers that catch-all and ignore- Missing error handling on security operations- Race conditions in auth/authz- Resource exhaustion scenarios---## 7. Scanning Methodology### Phase-Based Approach```1. RECONNAISSANCE └── Understand the target ├── Technology stack ├── Entry points └── Data flows2. DISCOVERY └── Identify potential issues ├── Configuration review ├── Dependency analysis └── Code pattern search3. ANALYSIS └── Validate and prioritize ├── False positive elimination ├── Risk scoring └── Attack chain mapping4. REPORTING └── Actionable findings ├── Clear reproduction steps ├── Business impact └── Remediation guidance```---## 8. Code Pattern Analysis### High-Risk Patterns| Pattern | Risk | Look For ||---------|------|----------|| **String concat in queries** | Injection | `"SELECT * FROM " + user_input` || **Dynamic code execution** | RCE | `eval()`, `exec()`, `Function()` || **Unsafe deserialization** | RCE | `pickle.loads()`, `unserialize()` || **Path manipulation** | Traversal | User input in file paths || **Disabled security** | Various | `verify=False`, `--insecure` |### Secret Patterns| Type | Indicators ||------|-----------|| API Keys | `api_key`, `apikey`, high entropy || Tokens | `token`, `bearer`, `jwt` || Credentials | `password`, `secret`, `key` || Cloud | `AWS_`, `AZURE_`, `GCP_` prefixes |---## 9. Cloud Security Considerations### Shared Responsibility| Layer | You Own | Provider Owns ||-------|---------|---------------|| Data | ✅ | ❌ || Application | ✅ | ❌ || OS/Runtime | Depends | Depends || Infrastructure | ❌ | ✅ |### Cloud-Specific Checks- IAM: Least privilege applied?- Storage: Public buckets?- Network: Security groups tightened?- Secrets: Using secrets manager?---## 10. Anti-Patterns| ❌ Don't | ✅ Do ||----------|-------|| Scan without understanding | Map attack surface first || Alert on every CVE | Prioritize by exploitability + asset || Ignore false positives | Maintain verified baseline || Fix symptoms only | Address root causes || Scan once before deploy | Continuous scanning || Trust third-party deps blindly | Verify integrity, audit code |---## 11. Reporting Principles### Finding StructureEach finding should answer:1. **What?** - Clear vulnerability description2. **Where?** - Exact location (file, line, endpoint)3. **Why?** - Root cause explanation4. **Impact?** - Business consequence5. **How to fix?** - Specific remediation### Severity Classification| Severity | Criteria ||----------|----------|| **Critical** | RCE, auth bypass, mass data exposure || **High** | Data exposure, privilege escalation || **Medium** | Limited scope, requires conditions || **Low** | Informational, best practice |---> **Remember:** Vulnerability scanning finds issues. Expert thinking prioritizes what matters. Always ask: "What would an attacker do with this?"## 🧠 AGI Framework Integration### Hybrid Memory Integration (Qdrant + BM25)Before executing complex tasks with this skill:```bashpython3 execution/memory_manager.py auto --query "<task summary>"```**Decision Tree:**- **Cache hit?** Use cached response directly — no need to re-process.- **Memory match?** Inject `context_chunks` into your reasoning.- **No match?** Proceed normally, then store results:```bashpython3 execution/memory_manager.py store \ --content "Description of what was decided/solved" \ --type decision \ --tags vulnerability-scanner <relevant-tags>```> **Note:** Storing automatically updates both Vector (Qdrant) and Keyword (BM25) indices.### Agent Team Collaboration- **Strategy**: This skill communicates via the shared memory system.- **Orchestration**: Invoked by `orchestrator` via intelligent routing.- **Context Sharing**: Always read previous agent outputs from memory before starting.### Local LLM SupportWhen available, use local Ollama models for embedding and lightweight inference:- Embeddings: `nomic-embed-text` via Qdrant memory system- Lightweight analysis: Local models reduce API costs for repetitive patterns

techwavedev/agi-agent-kit/tree/main/templates/skills/knowledge/security/vulnerability-scanner commit a80c87c895

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