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 autohandai/community-skills --skill analyzing-cobalt-strike-malleable-profilesgit clone --depth 1 https://github.com/autohandai/community-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/autohandai/community-skills/analyzing-cobalt-strike-malleable-profiles)<a href="https://agentmods.dev/skills/autohandai/community-skills/analyzing-cobalt-strike-malleable-profiles"><img src="https://agentmods.dev/badge/skills/autohandai/community-skills/analyzing-cobalt-strike-malleable-profiles/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/autohandai/community-skills/analyzing-cobalt-strike-malleable-profiles"><img src="https://agentmods.dev/badge/skills/autohandai/community-skills/analyzing-cobalt-strike-malleable-profiles.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 | $0.00080 | $0.00457 |
| Opus 5 | $0.00040 | $0.00229 |
| Sonnet 5 | $0.00016 | $0.00091 |
| Haiku 4.5 | $0.00008 | $0.00046 |
Grade A, and why
analyzing-cobalt-strike-malleable-profiles 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 12d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run( What it actually says
Analyzing Cobalt Strike Malleable Profiles
Instructions
Parse malleable C2 profiles to extract IOCs and detection opportunities using the pyMalleableC2 library. Combine with JARM fingerprinting to identify C2 servers.
from malleablec2 import Profile
# Parse a malleable profile from file
profile = Profile.from_file("amazon.profile")
# Extract global options (sleep, jitter, user-agent)
print(profile.ast.pretty())
# Access HTTP-GET block URIs and headers for network signatures
# Access HTTP-POST block for data exfiltration patterns
# Generate JARM fingerprints for known C2 infrastructure
Key analysis steps:
- Parse the malleable profile to extract HTTP-GET/POST URI patterns
- Extract User-Agent strings and custom headers for IDS signatures
- Identify sleep time and jitter for beaconing detection thresholds
- Scan suspect IPs with JARM to match known C2 fingerprint hashes
- Cross-reference extracted IOCs with network traffic logs
Examples
# Parse profile and extract detection indicators
from malleablec2 import Profile
p = Profile.from_file("cobaltstrike.profile")
print(p) # Reconstructed source
# JARM scan a suspect C2 server
import subprocess
result = subprocess.run(
["python3", "jarm.py", "suspect-server.com"],
capture_output=True, text=True
)
print(result.stdout)
# Compare fingerprint against known CS JARM hashes
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.
- 12d ago First seen · 61 lines · 80 tokens per session scan A f785745e7547
analyzing-cobalt-strike-malleable-profiles is a skill published in the GitHub repository autohandai/community-skills (11 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 80 tokens to every session and 457 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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analyzing-cobalt-strike-malleable-profiles
A security-analysis tool for reading Cobalt Strike configuration files and identifying how its command-and-control traffic is shaped. Cobalt Strike is a penetration-testing platform that can also be misused by attackers.
analyzing-cobalt-strike-malleable-profiles
Parses Cobalt Strike malleable C2 profiles using pyMalleableC2 to extract beacon configuration, HTTP communication patterns, and sleep/jitter settings. Combines with JARM TLS fingerprinting to detect C2 servers on the network. Use when investigating suspected Cobalt Strike infrastructure or building detection…
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