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-command-and-control-communicationgit 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-command-and-control-communication)<a href="https://agentmods.dev/skills/mukul975/anthropic-cybersecurity-skills/analyzing-command-and-control-communication"><img src="https://agentmods.dev/badge/skills/mukul975/anthropic-cybersecurity-skills/analyzing-command-and-control-communication/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-command-and-control-communication"><img src="https://agentmods.dev/badge/skills/mukul975/anthropic-cybersecurity-skills/analyzing-command-and-control-communication.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to critical
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 →
- critical YARA Match · line 186 YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).Fix: Remove the malware payload or compromised file entirely. Investigate how it entered the skill and audit all other artifacts for additional indicators of compromise.
- medium Data Exfiltration · line 243 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 | $0.00081 | $0.03573 |
| Opus 5 | $0.00041 | $0.01786 |
| Sonnet 5 | $0.00016 | $0.00715 |
| Haiku 4.5 | $0.00008 | $0.00357 |
Grade A, and why
analyzing-command-and-control-communication 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 11d 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.
resp = requests.get(f"https://api.shodan.io/shodan/host/{ip}?key={api_key}") Copies of this mod
7 near-identical copies found in the catalogue:
- analyzing-command-and-control-communication — 100% identical, 0 lines differ
- analyzing-command-and-control-communication — 94% identical, 11 lines differ
- analyzing-command-and-control-communication — 89% identical, 16 lines differ
- analyzing-command-and-control-communication — 86% identical, 32 lines differ
- analyzing-command-and-control-communication — 86% identical, 32 lines differ
- analyzing-command-and-control-communication — 86% identical, 32 lines differ
- analyzing-command-and-control-communication — 86% identical, 32 lines differ
How it starts
The opening of the file, as written. The whole thing — 406 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyzing Command-and-Control Communication
When to Use
- Reverse engineering a malware sample has revealed network communication that needs protocol analysis
- Building network-level detection signatures for a specific C2 framework (Cobalt Strike, Metasploit, Sliver)
- Mapping C2 infrastructure including primary servers, fallback domains, and dead drops
- Analyzing encrypted or encoded C2 traffic to understand the command set and data format
- Attributing malware to a threat actor based on C2 infrastructure patterns and tooling
Do not use for general network anomaly detection; this is specifically for understanding known or suspected C2 protocols from malware analysis.
Prerequisites
- PCAP capture of malware network traffic (from sandbox, network tap, or full packet capture)
- Wireshark/tshark for packet-level analysis
- Reverse engineering tools (Ghidra, dnSpy) for understanding C2 code in the malware binary
- Python 3.8+ with
scapy,dpkt, andrequestsfor protocol analysis and replay - Threat intelligence databases for C2 infrastructure correlation (VirusTotal, Shodan, Censys)
- JA3/JA3S fingerprint databases for TLS-based C2 identification
Workflow
Step 1: Identify the C2 Channel
Determine the protocol and transport used for C2 communication:
C2 Communication Channels:
━━━━━━━━━━━━━━━━━━━━━━━━━
HTTP/HTTPS: Most common; uses standard web traffic to blend in
Indicators: Regular POST/GET requests, specific URI patterns, custom headers
DNS: Tunneling data through DNS queries and responses
Indicators: High-volume TXT queries, long subdomain names, high entropy
Custom TCP/UDP: Proprietary binary protocol on non-standard port
Indicators: Non-HTTP traffic on high ports, unknown protocol
ICMP: Data encoded in ICMP echo/reply payloads
Indicators: ICMP packets with large or non-standard payloads
WebSocket: Persistent bidirectional connection for real-time C2
Indicators: WebSocket upgrade followed by binary frames
Cloud Services: Using legitimate APIs (Telegram, Discord, Slack, GitHub)
Indicators: API calls to cloud services from unexpected processes
Email: SMTP/IMAP for C2 commands and data exfiltration
Indicators: Automated email operations from non-email processes
What ships with it
3 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.
- 11d ago First seen · 406 lines · 81 tokens per session scan A 6ca6ca2373b4
analyzing-command-and-control-communication is a skill published in the GitHub repository mukul975/Anthropic-Cybersecurity-Skills (32,541 stars, last pushed 11d ago), licensed Apache-2.0. It adds 81 tokens to every session and 3,573 once invoked, about $0.0004 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.
Other skills, from other repositories
analyzing-command-and-control-communication
Use when analyzing malware command-and-control (C2) communication protocols to understand beacon patterns, command structures, data encoding, and infrastructure. Covers HTTP, HTTPS, DNS, and custom protocol C2 analysis for detection development and threat intelligence. Activates for requests involving C2 analysis…
analyzing-command-and-control-communication
Analyzes malware command-and-control (C2) communication protocols to understand beacon patterns, command structures, data encoding, and infrastructure. Covers HTTP, HTTPS, DNS, and custom protocol C2 analysis for detection development and threat intelligence. Activates for requests involving C2 analysis, beacon…
analyzing-command-and-control-communication
Analyzes malware command-and-control (C2) communication protocols to understand beacon patterns, command structures, data encoding, and infrastructure. Covers HTTP, HTTPS, DNS, and custom protocol C2 analysis for detection development and threat intelligence. Activates for requests involving C2 analysis, beacon…
analyzing-command-and-control-communication
A method for examining how malware communicates with its command-and-control server, the system that sends it instructions and receives data.
analyzing-command-and-control-communication
Analyzes malware command-and-control (C2) communication protocols to understand beacon patterns, command structures, data encoding, and infrastructure. Covers HTTP, HTTPS, DNS, and custom protocol C2 analysis for detection development and threat intelligence. Activates for requests involving C2 analysis, beacon…
analyzing-command-and-control-communication
Analyzes malware command-and-control (C2) communication protocols to understand beacon patterns, command structures, data encoding, and infrastructure. Covers HTTP, HTTPS, DNS, and custom protocol C2 analysis for detection development and threat intelligence. Activates for requests involving C2 analysis, beacon…