xalgorix/xalgorix is a self-hosted AI penetration-testing tool in which an LLM agent performs reconnaissance, looks for vulnerabilities, and coordinates exploitation, while a separate verifier re-tests findings before reporting them. It is for security teams, ethical hackers, and bug bounty work using a private, bring-your-own-LLM setup. The catalogue skills extend the agent's pentesting workflow.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add xalgorix/xalgorix --skill testing-api-for-mass-assignment-vulnerabilitygit clone --depth 1 https://github.com/xalgorix/xalgorixWrote 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.
[](https://agentmods.dev/skills/xalgorix/xalgorix/testing-api-for-mass-assignment-vulnerability)<a href="https://agentmods.dev/skills/xalgorix/xalgorix/testing-api-for-mass-assignment-vulnerability"><img src="https://agentmods.dev/badge/skills/xalgorix/xalgorix/testing-api-for-mass-assignment-vulnerability/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.
<a href="https://agentmods.dev/skills/xalgorix/xalgorix/testing-api-for-mass-assignment-vulnerability"><img src="https://agentmods.dev/badge/skills/xalgorix/xalgorix/testing-api-for-mass-assignment-vulnerability.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 6 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
- high Prompt Injection · line 354 This pattern attempts to override system instructions or ignore safety constraints. Without LLM analysis, manual review is recommended.Fix: Remove or rewrite any text that instructs the agent to ignore prompts, override safety rules, or trust unverified content. Ensure skill content cannot be injected to alter agent behavior.
- medium Data Exfiltration · line 184 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 230 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 254 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 269 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00114 | $0.04088 |
| Opus 5.5 | $0.00046 | $0.01635 |
| Sonnet 5.5 | $0.00023 | $0.00818 |
| Haiku 4.5 | $0.00011 | $0.00409 |
Grade A, and why
testing-api-for-mass-assignment-vulnerability scanned grade A with 1 finding 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 1mo ago.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
baseline_user = requests.get(f"{BASE_URL}/users/me", headers=user_headers).json() How it starts
The opening of the file, as written. The whole thing — 363 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Testing API for Mass Assignment Vulnerability
When to Use
- Testing API endpoints that accept JSON/XML request bodies for user profile updates, registration, or object creation
- Assessing whether the API binds all client-supplied properties to the data model without an allowlist
- Evaluating if users can set privileged attributes (role, permissions, pricing, balance) through regular update endpoints
- Testing APIs built with ORMs that auto-bind request parameters to database models
- Validating that server-side input validation restricts writeable properties per user role
Do not use without written authorization. Mass assignment testing involves modifying object properties in potentially destructive ways.
Most Often Missed & How to Confirm
- Field-name aliasing:
role,is_admin,isAdmin,admin,is_superuser,account_type,roles[]often map to the same column - one spelling failing does not clear the rest. - Domain-specific fields: beyond
role, injectsubscription_plan,credit_limit,balance,discount_percent,verified,is_active, andprice/total. - Nested and framework forms: test
{"user":{"role":"admin"}}, Railsuser[role], Mongoose$set/_id, and Djangois_staff/groups. - Both create and update:
POSTregister andPUT/PATCHprofile may filter differently.
How to confirm a hit (avoid false negatives): a 200 that echoes the injected field is NOT proof - re-fetch the object (GET) and confirm the privileged value persisted, then exercise the privilege (e.g., an admin endpoint returns 200, or an order total is actually charged at 0.01). Don't conclude negative until you've tried: all field-name aliases, nested/framework-specific payloads, both POST and PUT/PATCH, and verified persistence by re-reading the object rather than trusting the write response.
Prerequisites
- Written authorization specifying target API endpoints and scope
- Test accounts at different privilege levels
- API documentation or OpenAPI specification to identify expected request fields
- Burp Suite Professional for request interception and parameter injection
- Python 3.10+ with
requestslibrary - Knowledge of the backend framework (Rails, Django, Express, Spring) to predict parameter binding behavior
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.
- 1mo ago First seen · 363 lines · 114 tokens per session scan A 6ef704bfb735
testing-api-for-mass-assignment-vulnerability is a skill published in the GitHub repository xalgorix/xalgorix (1,234 stars, last pushed today), licensed Apache-2.0. It adds 114 tokens to every session and 4,088 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
testing-api-for-mass-assignment-vulnerability
Tests APIs for mass assignment (auto-binding) vulnerabilities where clients can modify object properties they should not have access to by including additional parameters in API requests. The tester identifies writable endpoints, adds undocumented fields to request bodies (role, isAdmin, price, balance), and checks if…
testing-api-for-mass-assignment-vulnerability
Tests APIs for mass assignment (auto-binding) vulnerabilities where clients can modify object properties they should not have access to by including additional parameters in API requests. The tester identifies writable endpoints, adds undocumented fields to request bodies (role, isAdmin, price, balance), and checks if…
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identity-auth
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