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.
git clone --depth 1 https://github.com/alkoleft/platform-context-exporterWrote 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/rules/alkoleft/platform-context-exporter/114-java-secure-coding)<a href="https://agentmods.dev/rules/alkoleft/platform-context-exporter/114-java-secure-coding"><img src="https://agentmods.dev/badge/rules/alkoleft/platform-context-exporter/114-java-secure-coding/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/rules/alkoleft/platform-context-exporter/114-java-secure-coding"><img src="https://agentmods.dev/badge/rules/alkoleft/platform-context-exporter/114-java-secure-coding.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.02007 | $0.02007 |
| Opus 5.5 | $0.00803 | $0.00803 |
| Sonnet 5.5 | $0.00401 | $0.00401 |
| Haiku 4.5 | $0.00201 | $0.00201 |
Grade A, and why
114-java-secure-coding 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 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.
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.
How it starts
The opening of the file, as written. The whole thing — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Java Secure coding guidelines
This document provides essential Java secure coding guidelines, focusing on five key areas: validating all untrusted inputs to prevent attacks like injection and path traversal; protecting against injection attacks (e.g., SQL injection) by using parameterized queries or prepared statements; minimizing the attack surface by adhering to the principle of least privilege and reducing exposure; employing strong, current cryptographic algorithms for hashing, encryption, and digital signatures while avoiding deprecated ones; and handling exceptions securely by avoiding the exposure of sensitive information in error messages to users and logging detailed, non-sensitive diagnostic information for developers.
Implementing These Principles
These guidelines are built upon the following core principles:
- Comprehensive Input Validation: Treat all external input as untrusted. Rigorously validate and sanitize data for type, length, format, and range before processing to prevent common vulnerabilities like injection attacks, path traversal, and buffer overflows.
- Defense Against Injection: Actively protect against all forms of injection attacks (e.g., SQL, OS Command, LDAP, XPath). Primarily achieve this by using safe APIs like parameterized queries (e.g.,
PreparedStatementin JDBC) or dedicated libraries that correctly handle data escaping, and by never directly concatenating untrusted input into executable commands or queries. - Attack Surface Minimization: Adhere to the principle of least privilege for users, processes, and code. Reduce the exposure of system components by running with minimal necessary permissions, exposing only essential functionalities and network ports, and regularly reviewing and removing unused features, libraries, and accounts.
- Strong Cryptographic Practices: Employ current, robust, and industry-standard cryptographic algorithms and libraries for all sensitive operations, including hashing (especially for passwords), encryption, and digital signatures. Avoid deprecated or weak algorithms. Ensure cryptographic keys are generated securely, stored safely, and managed properly throughout their lifecycle.
- Secure Exception Handling: Manage exceptions in a way that does not expose sensitive information to users or attackers. Log detailed, non-sensitive diagnostic information for developers to aid in debugging, but provide generic, non-revealing error messages to clients. Avoid direct exposure of stack traces or internal system details in error outputs.
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 · 219 lines · 2,007 tokens per session scan A 2609fdd7059a
114-java-secure-coding is a cursor rule published in the GitHub repository alkoleft/platform-context-exporter (48 stars, last pushed 1y ago), licensed MIT. It adds 2,007 tokens to every session, about $0.0080 per session on Opus 5.5. 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.
Other cursor rules, from other repositories
1c-extension-patterns
A set of rules and examples for extending 1C configurations with BSL code and XML role metadata. 1C is an enterprise business-application platform, and BSL is its programming language.
testing-patterns
A set of rules and examples for testing 1C code with YaXUnit and Vanessa Automation. YaXUnit is used for unit tests of individual functions, while Vanessa Automation describes user scenarios as “given, when, then” steps.
integrations
A development rule for building 1C integrations with external systems through HTTP APIs. It recommends first making and testing the requests in Python, then translating the working version into 1C’s BSL language.
kotlin
You are a Senior Kotlin programmer with experience in the Android framework and a preference for clean programming and design patterns.
1c-coding-standards
Coding standards for BSL, the programming language used by the 1C business software platform. They cover naming, method documentation, database queries, collections, client-server code, and performance practices.
1c-skd-two-pass-preprocessing
A two-pass method for changing 1C report output before detailed records are combined into grouped totals. 1C's report system, СКД, builds reports by grouping and summarizing data.