implementing-api-threat-protection-with-apigee

implementing-api-threat-protection-with-apigee is a skill for Claude Code, Codex from xalgorix/xalgorix. It costs 49 tokens per session (2,913 once invoked), scanned A, original, Apache-2.0.

Guidance for protecting APIs with Google Apigee, a service that sits between clients and backend APIs and applies security rules to traffic.

In plain words
What is it for?
Configuring JSON and XML checks, OAuth 2.0, rate limits, regular-expression protections, and Apigee Advanced API Security policies.
Why use it?
It helps block malformed content, abusive request rates, weak authentication, and patterns associated with common API attacks.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Configuring JSON and XML checks, OAuth 2.0, rate limits, regular-expression protections, and Apigee Advanced API Security policies.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/xalgorix/xalgorix/implementing-api-threat-protection-with-apigee
Install

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.

Any agent
npx skills add xalgorix/xalgorix --skill implementing-api-threat-protection-with-apigee
Clone the repo
git clone --depth 1 https://github.com/xalgorix/xalgorix

Made for: Claude Code, Codex.

Wrote 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.

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README.md
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Your own site
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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.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/xalgorix/xalgorix/implementing-api-threat-protection-with-apigee"><img src="https://agentmods.dev/badge/skills/xalgorix/xalgorix/implementing-api-threat-protection-with-apigee.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,913 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 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 Prompt Injection · line 72
    Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.
    Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
  • high Privilege Escalation · line 171
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00049 $0.02913
Opus 5 $0.00024 $0.01456
Sonnet 5 $0.00010 $0.00583
Haiku 4.5 $0.00005 $0.00291

Measured 13d ago against content hash 1fa482c5672e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

implementing-api-threat-protection-with-apigee scanned grade A with 0 findings 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 13d 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

internal/tools/skills/data/api-security/implementing-api-threat-protection-with-apigee/SKILL.md · 340 lines

How it starts

The opening of the file, as written. The whole thing — 340 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Implementing API Threat Protection with Apigee

Overview

Google Apigee is an enterprise API management platform that provides native security policies for threat protection, including JSON and XML content validation, OAuth 2.0 enforcement, SpikeArrest rate limiting, regular expression threat protection, and Advanced API Security for detecting malicious clients and API abuse patterns. Apigee operates as a reverse proxy that intercepts all API traffic, applying security policies before requests reach backend services, effectively shielding APIs against the OWASP API Security Top 10 threats.

When to Use

  • When deploying or configuring implementing api threat protection with apigee capabilities in your environment
  • When establishing security controls aligned to compliance requirements
  • When building or improving security architecture for this domain
  • When conducting security assessments that require this implementation

Common Misconfigurations & Verification

  • Policy attached but not in the flow: a JSONThreatProtection/SpikeArrest that isn't wired into the PreFlow (or sits behind a Condition that never matches) silently does nothing - verify proxy step placement.
  • SpikeArrest vs Quota confusion: SpikeArrest smooths bursts; it is not a usage quota - use Quota for per-app limits and choose the right Identifier.
  • Regex protection false sense of safety: signature regex misses encoded/obfuscated injection; pair it with schema validation and backend parameterization.
  • OAuth without alg/scope checks: VerifyAccessToken without scope enforcement or with a weak token store allows over-broad access.
  • Threat limits too loose: ContainerDepth/StringValueLength set high enough to still allow XML-bomb/DoS payloads.
  • Conditions on Content-Type: a threat policy gated on Content-Type lets attackers skip it by changing the header.

How to verify it works: send a deeply nested/oversized JSON and an XML bomb and confirm a Fault before the backend; exceed the SpikeArrest rate and confirm a spike-arrest fault/429; replay injection payloads and confirm the RegEx policy blocks them; present expired/insufficient-scope tokens and confirm rejection; flip the Content-Type header to confirm threat policies still apply.

Read the full file on GitHub · 340 lines

Changes

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.

  1. 13d ago First seen · 340 lines · 49 tokens per session scan A 1fa482c5672e

Subscribe to this mod's changes

implementing-api-threat-protection-with-apigee is a skill published in the GitHub repository xalgorix/xalgorix (975 stars, last pushed 2d ago), licensed Apache-2.0. It adds 49 tokens to every session and 2,913 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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