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 detecting-broken-object-property-level-authorizationgit 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/detecting-broken-object-property-level-authorization)<a href="https://agentmods.dev/skills/xalgorix/xalgorix/detecting-broken-object-property-level-authorization"><img src="https://agentmods.dev/badge/skills/xalgorix/xalgorix/detecting-broken-object-property-level-authorization/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/detecting-broken-object-property-level-authorization"><img src="https://agentmods.dev/badge/skills/xalgorix/xalgorix/detecting-broken-object-property-level-authorization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to medium
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 →
- medium Excessive Agency · line 95 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Data Exfiltration · line 244 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 250 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 304 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 | $0.00036 | $0.03438 |
| Opus 5 | $0.00018 | $0.01719 |
| Sonnet 5 | $0.00007 | $0.00688 |
| Haiku 4.5 | $0.00004 | $0.00344 |
Grade A, and why
detecting-broken-object-property-level-authorization 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 10d 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.
response = requests.get(url, headers=self.auth_headers, timeout=10) How it starts
The opening of the file, as written. The whole thing — 415 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Detecting Broken Object Property Level Authorization
Overview
Broken Object Property Level Authorization (BOPLA), classified as API3:2023 in the OWASP API Security Top 10, combines two related vulnerability classes: Excessive Data Exposure (API returning more data than needed) and Mass Assignment (API accepting more data than intended). Even when APIs enforce object-level authorization correctly, they may fail to control which specific properties of an object a user can read or modify. Attackers exploit this by reading sensitive properties from API responses or injecting additional properties into request bodies to modify fields they should not have access to.
When to Use
- When investigating security incidents that require detecting broken object property level authorization
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques
Detection Gaps & Validation
- Mass-assignment silently accepted: the server returns 200 and echoes only safe fields, but the privileged field (
role,is_verified) was written - confirm by re-fetching the object (GET) with the owner/victim account, never trust the write response body. - Field-name aliasing: APIs map
isAdmin,is_admin,admin,role_id,roles[], and nestedaccount.tierto the same column - testing only one casing/spelling yields false negatives. - Excessive exposure hides in nested objects and arrays: sensitive fields appear under
data.items[].owner.ssnor only on page 2; flatten recursively and check list responses, not just the top-level object. - GraphQL over-fetch: fields blocked on REST may be reachable via GraphQL aliases/fragments even with introspection disabled.
How to validate the detection fires: seed a test object with a known sensitive field and confirm the scanner's SENSITIVE_PROPERTY_PATTERNS flag it; submit a known mass-assignment payload and confirm the re-fetch verification step reports the change. Tune false positives by maintaining a per-endpoint expected-field allowlist so legitimately public fields (avatar_url, display_name) do not generate noise.
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.
- 10d ago First seen · 415 lines · 36 tokens per session scan A 3f47855758bc
detecting-broken-object-property-level-authorization is a skill published in the GitHub repository xalgorix/xalgorix (971 stars, last pushed yesterday), licensed Apache-2.0. It adds 36 tokens to every session and 3,438 once invoked, about $0.0002 per session on Opus 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.
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