Anthropic Cybersecurity Skills is a library of structured cybersecurity procedures for AI agents, covering security domains and mappings to established security frameworks. It is for authorized security analysis, penetration testing, incident response, research, defense, and education across compatible AI platforms. The catalogue entries package parts of this library as agent skills, instructions, or a plugin.
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 mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-golang-malware-with-ghidragit clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-SkillsWrote 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/mukul975/anthropic-cybersecurity-skills/analyzing-golang-malware-with-ghidra)<a href="https://agentmods.dev/skills/mukul975/anthropic-cybersecurity-skills/analyzing-golang-malware-with-ghidra"><img src="https://agentmods.dev/badge/skills/mukul975/anthropic-cybersecurity-skills/analyzing-golang-malware-with-ghidra/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/mukul975/anthropic-cybersecurity-skills/analyzing-golang-malware-with-ghidra"><img src="https://agentmods.dev/badge/skills/mukul975/anthropic-cybersecurity-skills/analyzing-golang-malware-with-ghidra.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk fail
- NVIDIA SkillSpector pass
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 | $0.00095 | $0.02883 |
| Opus 5 | $0.00048 | $0.01442 |
| Sonnet 5 | $0.00019 | $0.00577 |
| Haiku 4.5 | $0.00010 | $0.00288 |
Grade A, and why
analyzing-golang-malware-with-ghidra 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- analyzing-golang-malware-with-ghidra — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 321 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyzing Golang Malware with Ghidra
Overview
Go (Golang) has become a popular language for malware authors due to its cross-compilation capabilities, static linking that produces self-contained binaries, and the complexity it introduces for reverse engineering. Go binaries contain the entire runtime, standard library, and all dependencies statically linked, resulting in large binaries (often 5-15MB) with thousands of functions. Ghidra struggles with Go-specific string formats (non-null-terminated), stripped function names, and goroutine concurrency patterns. Specialized tools like GoResolver (Volexity, 2025) use control-flow graph similarity to automatically deobfuscate and recover function names in stripped or obfuscated Go binaries.
When to Use
- When investigating security incidents that require analyzing golang malware with ghidra
- 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
Prerequisites
- Ghidra 11.0+ with JDK 17+
- GoResolver plugin (for function name recovery)
- Go Reverse Engineering Tool Kit (go-re.tk)
- Python 3.9+ for helper scripts
- Understanding of Go runtime internals (goroutines, channels, interfaces)
- Familiarity with Go binary structure (pclntab, moduledata, itab)
Key Concepts
Go Binary Structure
Go binaries embed rich metadata in the pclntab (PC Line Table) structure, which maps program counters to function names, source files, and line numbers. Even stripped binaries retain this metadata. The moduledata structure contains pointers to type information, itabs (interface tables), and the pclntab itself. Go strings are stored as a pointer-length pair rather than null-terminated C strings.
Function Recovery in Stripped Binaries
Despite stripping symbol tables, Go binaries retain function names within the pclntab. However, obfuscation tools like garble rename functions to random strings. GoResolver addresses this by computing control-flow graph signatures of obfuscated functions and matching them against a database of known Go standard library and third-party package functions.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 13d ago First seen · 321 lines · 95 tokens per session scan A 36258341ae6c
analyzing-golang-malware-with-ghidra is a skill published in the GitHub repository mukul975/Anthropic-Cybersecurity-Skills (32,631 stars, last pushed 12d ago), licensed Apache-2.0. It adds 95 tokens to every session and 2,883 once invoked, about $0.0005 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.
Other skills, from other repositories
analyzing-golang-malware-with-ghidra
Reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go binaries.
analyzing-golang-malware-with-ghidra
Use when reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go binaries. Use when reverseing engineer go-compiled malware using ghidra with specialized scripts for.
analyzing-golang-malware-with-ghidra
Reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go binaries.
analyzing-golang-malware-with-ghidra
A malware-analysis workflow for examining Go programs with Ghidra, a reverse-engineering tool, including stripped or obfuscated compiled files.
analyzing-golang-malware-with-ghidra
Reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go binaries.
analyzing-golang-malware-with-ghidra
Reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go binaries.